The highlighted passage "Examples." appears in the section discussing the challenges of teaching software design and the rarity of educational resources on the topic. In context, the author is emphasizing the difficulty of finding well-documented examples that illustrate good software design practices, especially within engineering education. The author notes that engineering studies often focus on how things should be done rather than how they have been done historically, leading to a lack of collected, recognized, and explicated design examples. This absence of concrete examples hinders the development of a culture of good design among software engineers. Therefore, the mention of "Examples." underscores a critical gap in software design education: the scarcity of instructive, well-analyzed case studies that demonstrate effective software design in practice.

Q. Bret Victor's criticism of the state of examples in software design education?
A. We don't recognize, collect, and explicate great designs, or suggest that great designers teach. Students need to study great work, as they do in other artistic fields.

The prompt directly captures the core insight behind the user's highlight: Bret Victor's point that software design lacks recognized, collected, and explicated examples of great work, unlike other artistic fields where students study masters. It is meaningful because it isolates exactly what the user engaged with—the educational gap around design exemplars—rather than a trivial fragment. It is stable and self-contained: the question names the author and the specific topic ('examples in software design education'), so it remains clear and retrievable months later without the original document. It is also essentially atomic, testing one coherent causal claim (the absence of curated/explicated examples and mentorship hinders design culture). Fidelity is maintained: the answer matches the interpretation's account of the source material without introducing external claims.


Summary: Victor argues that most software should be designed as information software rather than manipulation software, and that information software design is fundamentally a graphic design problem, not an interactive one. He critiques the overreliance on interactivity in modern software and proposes a new approach focused on context-sensitive information graphics that infer user needs from environment and history. The paper presents a vision for software that requires minimal interaction, instead presenting relevant information through thoughtful graphic design.

Magic Ink: Information Software and the Graphical Interface

Q. What is crucial for the development of any artistic field?
A. A corpus

The prompt isolates the core, durable insight behind the user's highlight: that the development of any artistic or design field depends on having a corpus of exemplary works to study—precisely the gap Bret Victor identifies in software design education. It is atomic (tests one concept), uses the distinctive term 'corpus' which anchors recall even out of context, and faithfully captures the principle the user engaged with rather than a trivial fragment. While the framing is somewhat general ('any artistic field'), this generality mirrors the source's own claim and keeps the prompt self-explanatory on long review intervals.


Q. In what fields do students study the works of the masters?
A. Painting, writing, music, and architecture

The prompt tests a peripheral detail—the list of fields (painting, writing, music, architecture) where students study the masters' works—while omitting the core insight the user actually engaged with: that software engineering education, unlike these fields, focuses on how things should be done rather than how they have been done, leaving no collected or explicated design examples. Stripped of this contrast, the isolated list becomes a trivial, decontextualized fact that reinforces little of what the highlight was meant to capture. Additionally, the generic framing ('students,' 'works of the masters') lacks the built-in context needed for stable retrieval months later, since the question could plausibly belong to any number of sources.


Q. What should be done for outstanding designs and designers?
A. They should be recognized, collected, and explicated

The prompt successfully targets the core insight behind the highlight: the scarcity of instructive design 'Examples' stems from the fact that outstanding designs and designers are not recognized, collected, and explicated—a gap that hinders software design education and culture. It is atomic (tests one coherent idea), faithful to the highlighted passage as interpreted, and uses specific, concrete language ('recognized, collected, and explicated') that remains retrievable and unambiguous even months later when reviewed in isolation.


Q. What must be recognized, collected, and explicated?
A. Outstanding designs

This prompt is pluckable. It targets the core insight behind the user's highlight: the author's argument that a culture of good software design depends on exemplary case studies, which requires that outstanding designs be recognized, collected, and explicated. The prompt is atomic—it tests exactly one coherent idea—and uses precise, source-faithful language ('recognized, collected, and explicated') that anchors retrieval even when the original reading context has faded. The distinctive triad of verbs makes the question self-explanatory in isolation, and the answer ('outstanding designs') completes the highlighted thought faithfully rather than testing a trivial fragment or importing external material. While adding explicit context about software design education could marginally improve stability, the prompt as written remains clear, durable, and directly tied to what the user found interesting.


Q. What is lacking in software engineering schools according to the text?
A. Examples of great works

The prompt successfully transforms the bare highlighted word 'Examples.' into its complete, coherent unit of knowledge: the scarcity of exemplary works/case studies in software engineering education, exactly as framed by the user's interpretation. It is atomic (tests a single concept), faithful to the core insight the user engaged with rather than a trivial fragment, and stable—the concrete subject ('software engineering schools') and concise answer ('examples of great works') remain self-explanatory when reviewed in isolation months later, without needing the original document for context.


The highlight "interactivity has even worse problems" refers to a critical observation made within the context of software design, particularly for information software. In the broader discussion, the author emphasizes that designing software which primarily focuses on presenting information is essentially an exercise in graphic design—arranging and showing data effectively. However, "interactivity" introduces additional, more severe challenges beyond those involved in simply displaying information.

Unpacking this, the author likely means that while software that displays static or dynamic data needs good graphic design to be effective, the introduction of user interaction complicates matters significantly. Interactivity demands that software not only present data but also respond to user input in context-sensitive ways, requiring navigation, state management, prediction, and responsiveness. These factors make software design exponentially more difficult because the designer must consider usability, user goals, feedback loops, correctness, and preventing user confusion or errors.

Furthermore, the phrase hints at the author's stance that interactivity is a “number-one problem” or even worse than other common software design challenges. Interaction can easily become a source of frustration, inefficiency, or cognitive overload if not managed carefully—a situation described by terms like “interactivity considered harmful” in the text. The problems exacerbate because interaction is not just mechanical input but involves navigating complex data spaces and contexts that vary over time.

In summary, the author is communicating that while presenting information visually is challenging but manageable (akin to graphic design), layering interactivity on top of that creates a suite of more severe problems that make software design much harder, often leading to poor user experiences if not thoughtfully addressed.

Q. Besides wasting time, what three cognitive problems does Bret Victor list with interactivity in information software?
A. 1) you have to know what you want to ask for it; 2) you have to learn how to ask; 3) navigation implies statefulness

The highlight 'interactivity has even worse problems' is a fragment that serves as the lead-in to Bret Victor's enumeration of interactivity's specific drawbacks. The memory prompt correctly completes this highlighted thought into a whole, durable insight by recalling exactly what those problems are (knowing what to ask for, learning how to ask, and navigation implying statefulness)—so it is faithful to the source rather than introducing external material. It is also specific and stable: naming the author, the domain ('information software'), and anchoring with 'besides wasting time' gives built-in context that remains self-explanatory months later without the original document. While it recalls three items at once, they form a single coherent enumeration—the complete answer to the highlighted claim—rather than two unrelated concepts, so the compound structure reflects the natural atomic unit of the insight. The 'cognitive problems' framing is defensible since each burden (knowing what you want, learning the query language, tracking state through navigation) falls on the user's mind.


Q. What makes current software interaction models fundamentally challenging?
A. They fail to address the complex contextual needs of users beyond simple task completion.

The prompt is unpluckable primarily due to a fidelity failure. The highlight 'interactivity has even worse problems' anchors to Bret Victor's specific argument in 'Magic Ink': compared to designing static information displays (an exercise in graphic design), interactivity introduces strictly worse problems—e.g., the designer loses predictability and control over what the user sees, and the user is burdened with manually navigating and extracting information that could otherwise be inferred and presented graphically. The proposed answer ('They fail to address the complex contextual needs of users beyond simple task completion') does not capture this insight at all; it reads as a generic, hand-wavy claim about software usability that could apply to almost any critique of UX. Additionally, the question itself ('What makes current software interaction models fundamentally challenging?') is too abstract and context-dependent to remain stable across long review intervals—without the original document, both the question and answer are ambiguous enough that consistent retrieval would be unlikely. A pluckable version would target the concrete contrast Victor draws, such as asking why Victor considers interactivity problematic relative to purely graphical information presentation.


Q. How does the text describe the problems of interactivity compared to navigation?
A. Even worse

This prompt is not pluckable. It reduces the highlighted insight to a near-contentless comparative ('Even worse') without capturing any of the substantive reasoning behind it—why interactivity is more problematic than mere display or navigation (e.g., added cognitive burden, state management, forced manual manipulation). The answer 'Even worse' is trivially guessable and encodes no durable knowledge, failing the meaningfulness criterion. Additionally, the framing 'How does the text describe...' is generic and loses stability when reviewed in isolation months later, since 'the text' and the comparison target lack precise anchoring. A pluckable version would isolate the core principle—e.g., that Bret Victor argues interactivity compounds design problems beyond those of static presentation, making information software better treated as graphic design.


Q. What is considered the number-one software problem according to the text?
A. Navigation

The prompt directly targets the core insight anchored by the highlight: in 'Magic Ink,' the line 'interactivity has even worse problems' immediately leads into the claim that 'Navigation is the number-one software problem, and interactivity is its cause.' The prompt isolates this single, well-defined, quotable claim ('Navigation') in an atomic question, which is both meaningful (it is a central thesis of Victor's argument against gratuitous interactivity) and stable (a crisp, unambiguous fact retrievable months later). A minor improvement would be folding in the causal link—that interactivity is the cause of the navigation problem—to make the remembered concept whole, but the prompt remains faithful to and clearly tied to the highlighted idea.


Q. What has even worse problems than being a frustrating waste of time?
A. Interactivity

The prompt is essentially a verbatim fill-in-the-blank of the highlighted sentence, testing only the label 'Interactivity' while omitting the substantive insight the user engaged with—what those 'worse problems' actually are (e.g., interaction demanding user input, state management, and cognitive overhead). This leaves the claim decontextualized and hollow for long-term retention. Additionally, the comparative baseline 'being a frustrating waste of time' is unanchored: reviewed in isolation months later, the question is ambiguous about what that phrase refers to, undermining stability. A pluckable version would target the concrete content of the worse problems rather than a bare attribution.


The highlighted passage—"I believe that ideal candidates for software design are those who have achieved mastery of information graphics in other mediums"—occurs in a broader discussion that treats software design, especially the design of information software, as fundamentally a form of graphic design. Within the text, there is an emphasis on information software being primarily about presenting, arranging, and manipulating data visually to aid understanding. This situates software design not just as a technical or engineering task but as a creative, visual communication challenge that draws heavily on principles of graphic and information design.

By stating that ideal software designers are those with mastery in information graphics in "other mediums," the author implicitly claims that expertise in visual communication—developed outside of traditional software development—is crucial for effective software design, particularly for information-centric applications. Mastery in other mediums likely refers to fields such as print graphic design, data visualization, cartography, and other disciplines that deal with the clear and compelling graphical representation of information.

This suggests a few key ideas:
1. **Software design is closely linked to visual and information design.** It’s not merely about code or algorithms but about how data is represented graphically to enable comprehension and decision-making.
2. **Cross-disciplinary skills enrich software design.** Those who have developed their skills in non-software contexts of information graphics bring valuable insights, sensitivity to layout, context, visual hierarchy, and information clarity that software engineers might lack.
3. **Visual mastery informs better user experiences for information software.** Since software increasingly involves context-sensitive, interactive graphics, professionals skilled in graphic design can better navigate the complexities of presenting data visually and interactively.
4. **Software design is an extension of a longstanding tradition of graphical communication.** This positions software design as an evolutionary development of graphic arts, rather than a wholly new or isolated discipline.

In sum, the author is asserting that the best software designers are not solely those with programming or engineering backgrounds but rather those who bring a deep understanding of how to present and manipulate information graphically, leveraging skills honed in established information graphic arts outside software. This underscores a more holistic view of software design as an interdisciplinary craft merging technology with visual communication expertise.

Q. What primary barrier prevents visual artists from entering software design?
A. Perception of software design as a purely technological field, requiring specialized programming skills.

The prompt fails the fidelity criterion: the user's highlight asserts a positive claim—that ideal software designers are those who have mastered information graphics in other mediums—but the prompt instead tests a different, externally introduced claim about 'the primary barrier preventing visual artists from entering software design.' This reframing shifts focus away from the core insight the user engaged with and injects a causal claim ('perception of software design as purely technological') that was not part of the highlighted idea. Additionally, the phrase 'primary barrier' implies a single definitive cause, which risks instability and overgeneralization when reviewed in isolation months later. A pluckable prompt would directly target the highlighted insight, e.g., asking who Bret Victor considers the ideal candidates for software design.


The highlighted sentence, "This is how the behavior in the original example might come about," appears in a section that discusses a detailed explanation or demonstration of a particular software behavior or interaction—likely related to the train schedule widget or the programming-by-demonstration tool described in the text.

In context, the author has presented a complex example involving the inference of a function or mapping (possibly f(x,y) = ax + by + c) based on several snapshots or constraints derived from user input or graphical elements on screen. The section walks through how the tool can derive coefficients for a linear combination that models the relationship between visual components (e.g., time labels on a timeline) and their corresponding data properties (e.g., minutes since a starting time).

By stating "This is how the behavior in the original example might come about," the author is clarifying that the preceding mathematical or logical explanation shows the mechanism by which the observed interactive behavior is generated. The sentence bridges the theoretical or inferred model with the real-world user interface behavior users see, grounding the abstract inference process in a practical example.

Implicitly, this indicates the author's stance that such software behaviors—which might appear intricate or magical to users—can be systematically understood, modeled, and engineered via principled methods like programming by demonstration and constraint inference. It serves to demystify the origin of certain dynamic graphical behaviors in information software, emphasizing that careful design and algorithmic inference are responsible, rather than arbitrary programming.

Q. Sketch how Bret Victor's proposed architecture would implement his example of viewing an email saying "wanna get some pizza?", then seeing pizza locations on a map.
A. Email view nominates the current Email; "email digester" transformer emits a Text object with the body (and a "person" object with the sender, etc); "text digester" transformer extracts Keyword objects from Text—here, "pizza"; epicuriocity.com digester finds Restaurants for food-related Keywords; the map view, which has requested topics with a "location" property near the user, is given the Restaurant.

The memory prompt fails fidelity to the highlighted concept. The user's highlight ('This is how the behavior in the original example might come about') anchors to the programming-by-demonstration section, where Bret Victor explains how the system infers relationships (e.g., deriving coefficients for a mapping like f(x,y) = ax + by + c) from demonstrated constraints on the train schedule graphic—demystifying 'magical' UI behavior as principled constraint inference. The prompt instead tests an entirely different passage: the email/pizza-map example and its multi-component architecture of views, transformers, and digesters. Beyond missing the user's actual point of interest, the prompt is also a compound question requiring recall of many interlocking components (email view, email digester, text digester, keyword extraction, external site digester, map view), violating atomicity and making stable retrieval after months unlikely.


Summary: This article details Alberta's successful Rat Control Program, which has kept the province free of breeding rat populations for over 70 years. It chronicles how Norway rats first entered Alberta in 1950, the government's immediate response to prevent their spread, and the evolution of control measures from arsenic tracking powder to modern prevention methods. The program's success is attributed to legislation, public education, municipal cooperation, and vigilant border monitoring along the Saskatchewan border.

History of Rat Control in Alberta

The Norway rat (Rattus norvegicus) is unique because it must live with humans or in their structures. It cannot survive in natural areas and cannot overwinter in cultivated fields in Canada.

The author is emphasizing a distinctive ecological and behavioral trait of the Norway rat (Rattus norvegicus). Specifically, this species is not capable of living independently in natural environments; instead, it depends on human habitation or human-made structures to survive. Moreover, the author highlights the rat's inability to endure cold Canadian winters in open, cultivated fields, which underscores its reliance on human-associated shelter for survival in this region. This insight helps explain why the Norway rat’s distribution and proliferation are closely linked to human settlements and why human intervention—such as Alberta’s rat control program—is effective in limiting their spread.

Q. What type of rats were eradicated in Alberta?
A. The Norway Rat (Rattus norvegicus)

The memory prompt fails to capture the core insight of the highlighted text. The user highlighted the Norway rat's distinctive ecological trait—its obligate dependence on human habitation and structures, its inability to survive in natural areas, and its inability to overwinter in cultivated fields in Canada. Instead, the prompt tests an adjacent, trivial fact ('which rats were eradicated in Alberta?') that merely identifies the species by name without engaging the meaningful concept the user cared about. A pluckable prompt would target the causal insight itself—for example, asking why the Norway rat cannot survive independently of humans or why it cannot overwinter in Canadian fields—and connect that to why control programs like Alberta's are effective. As written, the prompt decontextualizes the species name and leaves the user's actual interest untested.


History of Rat Control in Alberta

Q. Why can't Norway rats survive winter and establish populations in Canadian cultivated fields?
A. They cannot overwinter (survive winter) in cultivated fields.

This prompt is not pluckable for two main reasons. First, it is circular: the question asks 'Why can't Norway rats survive winter in Canadian cultivated fields?' and the answer merely restates 'They cannot overwinter in cultivated fields.' There is no distinct piece of knowledge being retrieved—the answer adds nothing beyond rephrasing the question, so reviewing it months later would teach nothing durable. Second, it misses the core insight of the highlight: the user emphasized that the Norway rat is *unique because it must live with humans or in their structures* and cannot survive in natural areas. That dependence on human-associated shelter is the meaningful, self-contained concept worth retaining (and what makes Alberta's control program effective). The prompt instead isolates a trivial fragment ('cannot overwinter') while also being compound—asking about both surviving winter and establishing populations—but answering neither substantively.


History of Rat Control in Alberta

Q. What environmental limitation prevents Norway rats from establishing in Canadian fields?
A. They cannot overwinter (survive winter) in cultivated fields

The prompt isolates a single, well-defined ecological fact drawn directly from the user's highlighted text: Norway rats cannot overwinter in cultivated fields in Canada. It is atomic (tests one concept), faithful to the highlighted material without introducing external information, and meaningful rather than trivial—this overwintering limitation is the concrete mechanism underlying the broader insight about the species' dependence on human structures and the effectiveness of Alberta's rat control program. The language is specific and self-explanatory ('Norway rats,' 'overwinter,' 'cultivated fields,' 'Canada'), so it remains clear and consistently retrievable even when reviewed in isolation months or years later.


History of Rat Control in Alberta

Q. Why are Norway rats considered obligate human commensals?
A. They must live with humans or in human structures to survive.

The prompt captures the core insight of the highlight: the Norway rat's obligate dependence on humans or human structures for survival. It is atomic (tests one well-defined concept), uses precise terminology ('obligate human commensal') that frames the idea memorably, and its answer is drawn directly and faithfully from the highlighted text ('must live with humans or in their structures'). The question remains self-explanatory and stably retrievable in isolation months later, making it well-suited for long-term retention.


History of Rat Control in Alberta

Q. In what types of environments can Norway rats successfully overwinter in Canada?
A. Only in human structures or buildings

The memory prompt is pluckable. It isolates the core insight from the user's highlight—the Norway rat's inability to survive Canadian winters outside of human-made structures—and frames it as a single, atomic question. The question is meaningful because it directly targets the distinctive ecological trait the user cared about (the species' dependence on human habitation), rather than testing trivia. It is also stable: 'overwinter,' 'Canada,' and 'Norway rats' are precise, self-explanatory terms that remain clear when reviewed in isolation months later, without requiring the original document context. The answer faithfully matches the source material's claim that the rat cannot overwinter in cultivated fields and must rely on human structures.


History of Rat Control in Alberta

Q. What is the scientific name for the Norway rat?
A. Rattus norvegicus

The memory prompt fails to capture the core insight of the highlighted text. The user's highlight centers on the Norway rat's distinctive ecological trait—its obligate dependence on human habitation and structures, including its inability to survive in natural areas or overwinter in cultivated Canadian fields. Instead, the prompt tests a trivial surface detail (the binomial name 'Rattus norvegicus'), which serves merely as a label within the passage rather than the idea the user found interesting. While the question is atomic and stable in isolation, it is not meaningful relative to the highlighted concept, making it unpluckable.


History of Rat Control in Alberta

Since the early 1950s, Alberta has maintained a Rat Control Zone (RCZ) along the eastern border with Saskatchewan. This 600-km long and 29-km wide swath of land runs from Cold Lake in the north to the Montana border in the south (Figure 2)

The author explains that, starting in the early 1950s as a response to the threat posed by Norway rats spreading westward, Alberta established a designated Rat Control Zone (RCZ) along its eastern border adjacent to Saskatchewan. This zone is a defined geographic area specifically set aside for intensive rat control efforts. It is notably large, stretching 600 kilometers from north to south—from Cold Lake down to the Montana border—and spans 29 kilometers in width. This strategic, long and narrow zone was created to act as a buffer to halt or limit the invasion and westward expansion of rat populations into Alberta, allowing focused monitoring and control measures within this manageable corridor. The passage highlights how the province structured a physical containment area that remains central to Alberta’s ongoing rat control strategy.

Q. What are the northern and southern boundaries of Alberta's Rat Control Zone?
A. Cold Lake (north) to the Montana border (south)

The prompt is atomic, asking for a single well-defined piece of knowledge (the north–south endpoints of the Rat Control Zone) drawn directly from the highlighted sentence. It is faithful to the user's interest in the RCZ's geography, using precise terms from the source (Cold Lake, Montana border) rather than vague abstractions. The question embeds sufficient context by naming 'Alberta's Rat Control Zone,' so it remains self-explanatory when reviewed in isolation months later. The fact itself is stable—a fixed historical-geographic boundary unlikely to change—making it reliably retrievable on long review intervals.


History of Rat Control in Alberta

Q. What are the dimensions of Alberta's Rat Control Zone?
A. 600 km long and 29 km wide

The prompt targets a single, concrete fact—the dimensions of Alberta's Rat Control Zone—that appears verbatim in the user's highlighted text, so it is directly tied to what the user engaged with. It is atomic (tests one well-defined piece of knowledge), uses precise and unambiguous language ('Alberta's Rat Control Zone' is a clearly identifiable entity even without the original document context), and the answer is stable and verifiable (600 km long, 29 km wide). While it is a numeric detail, the user explicitly highlighted the sentence containing these figures, indicating genuine interest in the scale of this containment corridor, making it both meaningful and durable for spaced repetition.


History of Rat Control in Alberta

The highlighted passage "Figure 7. Confirmed infestations in the Rat Control Zone since 1959" refers to a data representation within the text that charts the number of rat infestations detected over time in Alberta’s designated Rat Control Zone (RCZ). Within the broader historical and programmatic context of Alberta’s efforts against the Norway rat, this figure is significant because it documents the outcome of sustained rat control measures that began in the 1950s. The text explains that after a rapid increase in infestations during the early 1950s, the numbers peaked around 1955 then dramatically decreased after 1959, showcasing the effectiveness of the control program. This decline illustrates how ongoing public education, legislative enforcement, pest control inspection, and community cooperation combined to bring the rat problem under control. The figure essentially provides empirical evidence supporting the narrative that Alberta’s rat control initiatives successfully contained and minimized rat infestations for decades, maintaining the province’s rat-free status. This emphasizes the critical role of continuous vigilance and cooperative action in managing invasive pests over the long term.

Q. How many confirmed rat infestations occur annually in Alberta's Control Zone after the program became successful?
A. 1 to 5 infestations per year

The prompt fails on both fidelity and stability grounds. The user's highlight anchors to Figure 7, whose core insight—as captured in the interpretation—is the *trend*: infestations rose through the early 1950s, peaked around 1955, then declined dramatically after 1959, evidencing the control program's effectiveness. The prompt instead isolates a precise numeric fragment ('1 to 5 infestations per year') that is never stated in the highlight or interpretation, effectively introducing external information beyond what the user demonstrably engaged with. Additionally, the vague temporal qualifier 'after the program became successful' lacks a concrete anchor (e.g., 'since ~1959'), making the question ambiguous in isolation, and a narrow numeric range like '1 to 5' is highly prone to recall distortion (confusion with 'under 10', 'a few', etc.) across months-long review intervals. A pluckable version would target the durable causal/trend insight rather than this unverifiable annual count.


History of Rat Control in Alberta

Q. How many confirmed rat infestations typically occur annually in Alberta's Control Zone since the program's success?
A. 1 to 5 infestations per year

This prompt is not pluckable because it fails the fidelity criterion: the user's highlight was a figure caption documenting the long-term trend of confirmed infestations (rapid rise in the early 1950s, peak around 1955, sharp decline after 1959), and the interpretation centers on this trajectory as evidence of the control program's effectiveness. The prompt instead isolates a specific annual statistic ('1 to 5 infestations per year') that is never mentioned in the highlight or its interpretation, testing a granular number detached from the core insight the user engaged with. Additionally, it has stability weaknesses: 'typically occur annually' is vague, the answer's precision invites doubt on isolated review months later, and it uses 'Control Zone' rather than the source's precise term 'Rat Control Zone.' A more pluckable prompt would target the durable takeaway—e.g., that infestations peaked around 1955 and declined dramatically after 1959 due to sustained control measures—rather than an unanchored annual count.


History of Rat Control in Alberta

Q. What has become more common than full rat infestations in Alberta's Control Zone?
A. Individual rats hitching rides on vehicles

This prompt is not pluckable because it fails fidelity to the highlighted concept. The user highlighted Figure 7, whose significance—per the interpretation—is the empirical documentation of confirmed infestations peaking around 1955 and dramatically declining after 1959, evidencing the effectiveness of Alberta's sustained control program. The memory prompt instead tests a tangential detail (individual rats hitching rides on vehicles becoming more common than full infestations) that is neither mentioned in the highlight nor in the interpretation, introducing external information disconnected from the core insight. Additionally, the question's framing ('has become more common') is temporally vague, which weakens stability for isolated review months or years later. A pluckable prompt would have targeted the actual takeaway of the figure, such as what happened to confirmed infestations in the Rat Control Zone after 1959 and why.


Summary: In his seventh annual message to Congress, President James Monroe outlined what would become known as the Monroe Doctrine, a cornerstone of American foreign policy. The doctrine declared that the American continents were no longer open to European colonization, that the United States would not interfere with existing European colonies, and that the U.S. would view any European intervention in the newly independent nations of the Americas as a hostile act. Monroe also emphasized America's policy of non-interference in European affairs while asserting a special interest in the Western Hemisphere.

Monroe Doctrine (President Monroe's Seventh Annual Message to Congress)

The highlighted passage "President Monroe Outlines the Monroe Doctrine, 1823" refers to President James Monroe's formal declaration, presented to Congress in 1823, establishing a key principle of American foreign policy. Within the broader context of this document, Monroe—guided by Secretary of State John Quincy Adams—articulates that the Western Hemisphere (the American continents) is no longer open to European colonization. This doctrine asserts that the United States would view any European attempts to control or oppress newly independent nations in the Americas as threats to U.S. peace and security.

The Monroe Doctrine is rooted in the recognition of the Americas as politically distinct and free from European systems, in contrast to the monarchic and alliance-driven political systems of European powers. Additionally, Monroe clarifies that the U.S. aims to stay neutral in European internal conflicts unless its own rights or safety are jeopardized. Importantly, the doctrine differentiates between interfering with existing European colonies (which the U.S. avoids) and opposing European intervention in independent American nations, which the U.S. actively discourages.

Thus, in asserting the Monroe Doctrine, Monroe is signaling a protective stance toward the sovereignty of American nations and a warning to European powers against further colonial ambitions in the hemisphere. This policy reflects the emergent American spirit of Manifest Destiny and the desire to establish the United States as the dominant power in the Western Hemisphere.

Q. In what year was the Monroe Doctrine first outlined?
A. 1823

The prompt is atomic, precise, and stable: it asks a single, unambiguous question ('In what year was the Monroe Doctrine first outlined?') whose answer (1823) is a fixed historical fact that remains clear even when reviewed in isolation years later. It is also directly faithful to the user's highlight, since the highlighted title itself embeds the year 1823, making the date the concrete anchor of the saved material. While the prompt captures only a fragment of the broader insight described in the interpretation (the doctrine's principles), the year is not a trivial or decorative detail—it is the defining temporal anchor of the Monroe Doctrine, and the question supplies enough built-in context ('Monroe Doctrine,' 'first outlined') to remain self-explanatory without the original document.


Summary: Brian Potter analyzes the feasibility and economics of meeting large fractions of US electricity demand with large-scale solar photovoltaic (PV) systems, focusing on the need for overbuilding, storage, and backup infrastructure. He finds that while supplying 100% of demand with solar PV and batteries alone is infeasible due to diminishing returns and intermittency, supplying 70-80% is achievable and cost-effective if solar and battery costs continue to fall. The need for parallel backup systems (like gas turbines) is less burdensome than often assumed, especially if batteries are used flexibly. The article relies on simulations using California electricity data and explores how cost declines in solar and storage could enable much higher solar penetration.

Can We Afford Large-scale Solar PV?

The highlighted term, "levelized cost of electricity (LCOE)," appears in the context of analyzing the economic feasibility of meeting 100% of electricity demand with varying combinations of solar photovoltaic (PV) systems, battery storage, and backup gas turbines.

In the passage, LCOE is used as a key metric to compare the cost-effectiveness of different energy infrastructure setups. The author explains that as the fraction of demand met by solar PV increases, especially beyond around 40%, the LCOE rises significantly, indicating substantially higher costs for high penetrations of solar energy due to the need for extensive overbuilding of solar panels and large battery storage capacities to manage intermittency.

The LCOE is essentially a measure that averages the total lifetime costs of electricity generation (including capital, maintenance, and fuel) divided by the total electricity produced, producing a cost per unit of electricity (e.g., per megawatt-hour) that allows for comparison across different technologies and configurations.

Importantly, the author notes that current US costs for solar PV and batteries are relatively high, but worldwide averages and potential future cost reductions (such as solar panels at $400/kW and batteries at $100/kWh, which are roughly current Chinese costs) could bring the LCOE of large-scale solar PV systems down to levels comparable with current gas turbine plants. This makes achieving 70-80% solar penetration more economically feasible.

Furthermore, the author points out that the simulations of LCOE here only examine generation costs and exclude other economic factors like transmission costs, market dynamics, or electricity pricing. Still, LCOE serves as a foundational economic indicator to understand the viability and scalability of solar PV deployment.

In sum, the author uses LCOE as a central analytical tool to demonstrate that while it is currently costly to meet very high fractions of electricity demand solely with solar PV and batteries, ongoing cost reductions in these technologies could make large-scale solar a cost-effective strategy for power generation. This underscores the importance of considering both technical feasibility and economic metrics like LCOE in energy planning.

Q. According to the universal consensus among experts, what is the economic feasibility of 100% solar PV supply?
A. The LCOE is competitive (at parity) with fossil fuels when combined with battery storage and gas turbines.

This prompt is not pluckable because it fundamentally misrepresents the source material and introduces fabricated context. The user's highlight was simply the term 'levelized cost of electricity (LCOE)', indicating interest in the metric itself and how the article uses it to assess solar PV economics. However, the prompt invents a claim of 'universal consensus among experts' that 100% solar PV supply is at cost parity with fossil fuels—this contradicts the article, which explicitly states that LCOE rises significantly as solar penetration increases beyond ~40% due to overbuilding and battery storage requirements, and that parity is only a *potential future* outcome contingent on cost reductions (e.g., $400/kW panels and $100/kWh batteries). The answer also frames battery storage and gas turbines as making LCOE competitive, when the article treats them as drivers of higher costs at high penetration. Additionally, the vague appeal to 'universal consensus' fails the stability criterion—it is imprecise, unverifiable from the source, and would produce confusion rather than durable recall months later. A pluckable prompt would instead target the core insight the user engaged with, such as what LCOE measures or why LCOE climbs sharply at high solar penetration.


Can We Afford Large-scale Solar PV?

Q. What does the _Levelized Cost of Electricity (LCOE)_ describe?
A. The average cost per unit of electricity generated over a plant’s lifetime, including capital, operating, fuel, and financing costs, adjusted for time value.

The user's highlight anchors on the term 'levelized cost of electricity (LCOE)' itself, indicating their interest was in understanding this concept. The memory prompt faithfully targets that exact unit of knowledge: a single, atomic definition of LCOE. It is meaningful because LCOE is a foundational, reusable metric in energy economics (relevant far beyond this one article), and it is stable because the question is self-explanatory in isolation and the answer is precise, concrete, and consistent with the source's framing (total lifetime costs—including capital, operating, fuel, and financing—divided by total electricity produced, with discounting for time value). It avoids testing trivial fragments or importing unrelated claims, and its clarity will hold up over long review intervals.


Can We Afford Large-scale Solar PV?

Current worldwide average costs for solar and battery storage let us get to around 50% of total electricity demand with solar PV for around the current LCOE of gas turbines in the US. If we can hit $400 kw solar and $100 kw-h storage, we can push that percentage to around 80%.

The author is discussing the economic feasibility of large-scale solar photovoltaic (PV) power paired with battery storage in meeting a significant portion of electricity demand. The highlighted passage emphasizes that, on a global average cost basis for solar PV and battery storage today, it is possible to supply around 50% of total electricity demand with solar at a levelized cost of electricity (LCOE) comparable to the current costs of combined cycle gas turbines in the US. This establishes a baseline for competitiveness: solar-plus-storage is already able to supply a substantial fraction of demand at a cost similar to conventional gas power plants in many parts of the world.

Further, the author projects a future scenario where the capital costs of solar PV drop to about $400 per kilowatt and battery storage costs to around $100 per kilowatt-hour—costs that China is likely already achieving. At these reduced costs, solar and batteries could feasibly meet approximately 80% of total electricity demand at a cost still comparable to current US gas turbine costs. This suggests a tipping point where very high solar penetration becomes economically viable, moving solar-plus-storage from partial contributor to dominant electricity source.

Thus, the core idea is that cost reductions in both solar panels and battery storage are crucial enablers for expanding solar PV’s share of electricity supply from around 50% (current global costs) to roughly 80% (future lower costs). The passage reinforces the author’s overall argument that large-scale solar power combined with storage is increasingly affordable and scalable, and that continued cost declines can make solar a major component of electricity generation without prohibitively high expenses.

Q. [Brian Potter's Large-Scale Solar PV Analysis] What solar and battery cost targets could enable solar PV to meet around 80% of electricity demand, according to Brian Potter (2024)?
A. $400 per kW for solar and $100 per kWh for battery storage.

The prompt directly targets the core quantitative insight the user highlighted: the specific cost thresholds ($400/kW solar, $100/kWh storage) that enable solar-plus-storage to reach ~80% of electricity demand. It is atomic (tests one well-defined cost-target pair), faithful to the highlighted concept, and stable—the 80% anchor and explicit attribution make it self-explanatory in isolation, months after the original reading. While it omits the complementary 50%-at-current-costs baseline, that detail forms a separate coherent unit better served by its own prompt; this prompt cleanly captures the future-scenario half without triviality or external additions.


Can We Afford Large-scale Solar PV?

Q. [Brian Potter's Large-Scale Solar PV Analysis] What are the required solar PV and battery storage cost targets for solar to economically meet up to 80% of electricity demand?
A. $400/kW solar PV and $100/kWh battery storage

The prompt directly targets the core quantitative insight of the highlighted passage: the specific cost thresholds ($400/kW solar PV and $100/kWh battery storage) that would enable solar-plus-storage to economically supply roughly 80% of electricity demand. These figures are exactly what the user highlighted, making the prompt faithful to their interest. It is atomic—testing one coherent unit of knowledge (the paired cost targets for the 80% scenario)—and stable, since the question is self-contained with clear source attribution ('Brian Potter's Large-Scale Solar PV Analysis') and a precise, unambiguous answer that can be reliably recalled months or years later without the original article. While it omits the secondary detail about the 50% baseline and gas turbine LCOE comparison, those are separate facets of the same passage rather than essential context for answering this specific question.


Can We Afford Large-scale Solar PV?

Q. [Brian Potter's Large-Scale Solar PV Analysis] What share of electricity demand can solar and batteries meet at current global average costs, relative to U.S. gas turbine LCOE?
A. Around 50% — at that point, solar plus storage matches the LCOE of U.S. gas turbines.

The prompt isolates a single, well-defined quantitative insight drawn directly from the highlighted text: at current global average costs, solar plus storage can supply roughly 50% of total electricity demand at an LCOE comparable to U.S. gas turbines. It is atomic (tests one fact), uses precise source terminology ('current global average costs,' 'U.S. gas turbine LCOE'), and is self-explanatory in isolation, making it stable for long-interval spaced repetition. While it omits the companion scenario from the same highlight (80% penetration at $400/kW solar and $100/kWh storage), that omission reflects good atomicity rather than infidelity—that projection could form its own separate card. The tested fact is meaningful (a headline finding of the article's affordability argument) rather than a trivial detail, so the prompt satisfies both the meaningfulness and stability criteria.


Can We Afford Large-scale Solar PV?

We see here the exact same diminishing returns that we saw when simulating a single family home. Each additional watt of solar PV capacity and watt-hour of battery storage gets used less and less frequently, and contributes a smaller amount to meeting overall electricity demand.

The highlighted passage explains a key observation about the scalability of solar PV and battery storage systems when trying to meet electricity demand, using California's grid data as an example. The author is emphasizing that as solar and battery capacity increases, the incremental benefit from each additional unit of capacity decreases—a phenomenon known as diminishing returns.

This means that while initially adding solar panels and batteries significantly increases the fraction of demand met by solar power, over time each extra watt of panel or extra watt-hour of storage is used less often and has a smaller impact on improving the overall electricity supply. This happens because the easiest and most frequent periods of demand matching are covered by the initial capacity additions, but handling the rare, extreme demand peaks or extended cloudy periods requires disproportionately large increases in infrastructure that get used only occasionally.

The author supports this point by showing that the pattern observed at the scale of an individual household—a diminishing return on investment as solar and battery capacity grow—also applies across a whole state’s electricity grid. Thus, adding more infrastructure to approach 100% solar energy supply becomes exponentially more challenging and expensive due to rare but critical demand-supply mismatches that require large amounts of capacity that mostly remain idle.

In essence, this passage clarifies a fundamental limitation in relying solely on solar PV and batteries for electricity: beyond a certain point, further capacity expansions yield progressively smaller benefits, making it impractical or very costly to meet all demand with just solar and storage. This sets the stage for the article’s later argument that other technologies (like gas turbines) and operational strategies (like allowing turbines to charge batteries) are necessary complements to manage these edge cases economically.

Q. [Brian Potter's Large-Scale Solar PV Analysis] What happens as more panel capacity and storage are added?
A. Diminishing returns — each added unit contributes less and is used less often, especially when nearing full demand coverage.

The prompt successfully isolates the core insight the user highlighted: diminishing returns on incremental solar PV and battery capacity. It is atomic (tests one concept), faithful to the source text ('each added unit contributes less and is used less often' directly mirrors the highlighted passage), and captures the meaningful takeaway rather than a trivial detail. The article tag '[Brian Potter's Large-Scale Solar PV Analysis]' anchors the context for isolated review, and the answer's qualifier 'especially when nearing full demand coverage' adds the key condition from the source material, keeping the prompt self-explanatory months later. A minor weakness is that the question stem could specify the goal (meeting overall electricity demand) more explicitly, but the tag and answer compensate, making the cue-response pair reliably retrievable.


Can We Afford Large-scale Solar PV?

Q. According to widely accepted principles among solar energy experts, what happens to the contribution of each additional large-scale solar PV unit as overall electricity supply approaches 100%?
A. The contribution diminishes.

The prompt fails on both fidelity and stability. First, it fabricates framing absent from the source: 'widely accepted principles among solar energy experts' misrepresents what was actually an empirical simulation finding from the article, introducing external context the user never engaged with. Second, the answer ('The contribution diminishes') is far too vague to be stably retrievable or verifiable—it captures only the label of the phenomenon while discarding the substantive mechanism the user highlighted: each additional watt of solar PV capacity and watt-hour of battery storage gets used less and less frequently (because initial capacity covers the easy, frequent demand-matching periods, leaving rare peaks and extended cloudy stretches requiring disproportionately large, mostly idle capacity). A pluckable version would test that specific causal mechanism—e.g., why incremental capacity contributes less (it sits idle except during rare mismatch events)—rather than a tautological restatement of 'diminishing returns.' As written, the prompt reduces a rich, self-contained insight into a trivially generic claim.


Can We Afford Large-scale Solar PV?

We found that due to solar’s intermittency, supplying large fractions of electricity demand requires a fair degree of “overbuilding” (solar panel capacity well in excess of total electricity demand), as well as a fair amount of storage. For a single family home where power demand never exceeds 10 kilowatts (and most of the time is below 2 kilowatts), supplying 80% of annual electricity consumption requires at least 13.7 kilowatts of solar panels, and 40 kilowatt-hours of storage. And supplying even higher fractions of electricity demand — 90%, 95%, 99% — the infrastructure requirements gets even more burdensome. Going from 80 to 90% of electricity supplied requires nearly doubling solar panel capacity.

The highlighted passage explains a key challenge with relying heavily on solar photovoltaic (PV) power due to its intermittent nature—solar panels only generate electricity when the sun is shining, which doesn’t always align perfectly with electricity demand. To compensate for this variability and ensure a reliable supply, it’s necessary to build much more solar panel capacity than the peak or average power demand and also to have substantial energy storage (like batteries) to smooth out periods without sun.

Specifically, the author provides a concrete example of a single-family home with typical power demands: although the peak demand never exceeds 10 kW—and often stays below 2 kW—to supply 80% of the home's annual electricity needs from solar requires installing at least 13.7 kW of solar panels and 40 kWh of storage. This means the solar capacity exceeds the home's maximum instantaneous power demand by a significant margin (overbuilding).

Moreover, as one tries to supply an even larger fraction of electricity demand—moving from 80% to 90%, 95%, or 99% reliance on solar—the infrastructure requirements become “even more burdensome.” For example, increasing supply from 80% to 90% demands nearly doubling the solar panel capacity. This shows sharply diminishing returns: getting closer to full solar supply requires disproportionately more hardware, making higher penetration levels of solar PV progressively more challenging and expensive.

In essence, the author is highlighting the tradeoff between how much solar energy can directly meet demand versus the substantial extra capacity and storage needed to handle solar’s intermittency, emphasizing that the infrastructure to reliably supply very high fractions of electricity via solar PV grows steeply and nonlinearly. This sets the stage for later discussions about costs, complementary technologies, and system design needed for large-scale solar adoption.

Q. [Brian Potter's Large-Scale Solar PV Analysis] What is the effect of increasing electricity supply from 80% to 90% on solar panel capacity requirements?
A. Results in a near doubling of solar panel capacity.

This prompt is pluckable. It is atomic, testing a single well-defined fact drawn directly from the highlighted passage: moving from 80% to 90% of electricity supplied by solar requires nearly doubling panel capacity. This fact is not a trivial fragment—it is the most striking quantitative embodiment of the core insight the user engaged with, namely that solar intermittency forces steeply nonlinear 'overbuilding' as penetration rises (sharply diminishing returns approaching full solar supply). The phrasing is specific and concrete ('80% to 90%', 'solar panel capacity', 'near doubling'), which supports stable retrieval months later even without the original article. The only minor weakness is that the question body relies on the '[Brian Potter's Large-Scale Solar PV Analysis]' tag to clarify that 'electricity supply' refers to the share met by solar PV, but this contextual anchor adequately resolves the ambiguity.


Can We Afford Large-scale Solar PV?

Q. According to Brian Potter's analysis, what is the effect of increasing electricity supply from 80% to 90% on solar panel capacity requirements?
A. Increasing electricity supply from 80% to 90% of demand requires nearly doubling solar panel capacity.

This prompt is pluckable. It targets the exact quantitative insight the user highlighted—that moving from 80% to 90% solar-supplied electricity requires nearly doubling panel capacity—which encapsulates the core principle of sharply diminishing returns due to intermittency. The prompt is atomic (tests one fact), uses precise language ('nearly doubling', '80% to 90%'), and anchors to Brian Potter's analysis for context, making it stable and self-explanatory even when reviewed in isolation months or years later. It faithfully reflects the highlighted material without introducing external information or testing trivial fragments.


Can We Afford Large-scale Solar PV?

Q. [Brian Potter's Large-Scale Solar PV Analysis] How much solar capacity is needed for a household with a steady 2 kW load and 10 kW peak demand?
A. At least 13.7 kW of solar panels, along with about 40 kWh of battery storage.

The prompt tests a specific figure (13.7 kW panels, 40 kWh storage) but strips away the essential context that makes it meaningful: these numbers apply specifically to supplying 80% of annual electricity consumption. Without that anchor, the answer is arbitrary—the whole point of the highlighted passage is how infrastructure requirements scale with the fraction of demand supplied (e.g., going from 80% to 90% nearly doubles panel capacity). Additionally, the prompt inaccurately describes the home as having a 'steady 2 kW load,' whereas the source states demand 'most of the time is below 2 kilowatts'—a variable load peaking at 10 kW. This misrepresentation harms fidelity and stability, since a reviewer months later would encounter a distorted version of the insight rather than the durable concept of overbuilding driven by intermittency.


Can We Afford Large-scale Solar PV?

Q. What minimum solar panel capacity, according to Brian Potter, is required to supply 80% of electricity demand for a single-family home?
A. At least 13.7 kilowatts

This prompt targets a single illustrative statistic (13.7 kW) rather than the core insight the user highlighted: that solar intermittency requires overbuilding capacity well beyond actual demand plus substantial storage, with sharply diminishing returns as supply fraction increases (e.g., 80%→90% nearly doubling panel capacity). Stripped of its anchoring context—the home's ~10 kW peak demand and mostly-below-2-kW usage—the bare number becomes a decontextualized trivia item whose meaning isn't self-evident on isolated review months later. A pluckable prompt would test the underlying principle (why overbuilding occurs, or how requirements scale non-linearly), which is the durable, meaningful unit of knowledge the user engaged with.


Can We Afford Large-scale Solar PV?

Q. [Brian Potter's Large-Scale Solar PV Analysis] What economic thresholds for large-scale solar PV deployment are considered feasible for meeting significant electricity demand?
A. Potter concludes that solar can economically supply 30-40% of electricity demand at current US costs, but up to 80% with continued cost decreases.

This prompt is not pluckable because it fails the fidelity criterion: it tests economic feasibility thresholds (30-40% at current costs, up to 80% with cost decreases) that do not appear in or relate to the user's highlighted passage. The highlight centers on a distinct, concrete insight—solar's intermittency forces massive 'overbuilding' and storage, illustrated by the example that a home with sub-10 kW peak demand needs 13.7 kW of panels plus 40 kWh of storage for just 80% coverage, and that moving from 80% to 90% supply nearly doubles panel capacity. A pluckable prompt would target this nonlinearity/overbuilding insight directly. Additionally, the prompt's generic framing ('economic thresholds... considered feasible') is vague and would feel disconnected when reviewed months later without the article context.


Can We Afford Large-scale Solar PV?

Q. [Brian Potter's Large-Scale Solar PV Analysis] What does Potter conclude about the economic feasibility of large-scale solar PV for meeting electricity demand?
A. At current U.S. costs, solar PV can economically supply about 30–40% of electricity demand. With continued cost declines (following historical learning curves), it could feasibly support up to 80%, but beyond that, sharply rising infrastructure demands make higher penetration increasingly costly.

The prompt fails fidelity to the highlighted concept. The user's highlight anchors on a specific, self-contained insight about solar intermittency: meeting high fractions of demand requires massive overbuilding plus storage (e.g., 13.7 kW of panels and 40 kWh of storage for a home whose peak demand never exceeds 10 kW), and requirements rise steeply and nonlinearly—going from 80% to 90% supply nearly doubles panel capacity. Instead of testing this core idea, the prompt targets the article's broader economic-feasibility conclusion and introduces specific figures (30–40% economical today, 80% feasible with cost declines) that do not appear in the highlighted text, effectively substituting external information for the insight the user engaged with. Additionally, the answer bundles several distinct claims into one compound response, weakening atomicity and making consistent retrieval harder after long review intervals.


Can We Afford Large-scale Solar PV?

Q. [Brian Potter's Large-Scale Solar PV Analysis] What share of U.S. electricity can solar theoretically PV meet at today’s costs and with continued cost drops?
A. At current U.S. costs, solar PV can economically supply about **30–40%** of electricity demand. With continued cost declines (following historical learning curves), it could **feasibly support up to 80%**, but beyond that, sharply rising infrastructure demands make higher penetration increasingly costly.

The prompt fails fidelity to the highlighted concept. The user's highlight focuses on a concrete, self-contained insight about intermittency: supplying high fractions of demand requires massive 'overbuilding' (13.7 kW of panels for a home whose demand never exceeds 10 kW) plus substantial storage (40 kWh), and that requirements scale steeply—going from 80% to 90% supply nearly doubles panel capacity. Instead, the prompt tests a different claim from elsewhere in the article (the economically feasible share of U.S. electricity solar can meet at current vs. future costs), introducing external information the user did not anchor on. It is also compound and vaguely framed ('theoretically,' 'at today's costs,' 'with continued cost drops'), testing multiple conditions at once, which undermines stability for isolated review months later. A pluckable prompt would target the core insight directly, e.g., asking why supplying 80% of a home's electricity from solar requires far more than its peak demand, or what happens to infrastructure requirements when moving from 80% to 90% supply.


Can We Afford Large-scale Solar PV?

Q. [Brian Potter's Large-Scale Solar PV Analysis] By approximately what factor does required solar capacity change when increasing supply coverage from 80% to 90%?
A. It increases by nearly a factor of two (roughly doubling).

The prompt targets the exact quantitative anchor the user highlighted ('going from 80% to 90% requires nearly doubling solar panel capacity'), which serves as the concrete embodiment of the core insight: infrastructure requirements grow steeply and nonlinearly as solar coverage increases due to intermittency. It is atomic (tests one well-defined relationship), precise (specific percentages and capacity metric), and stable—it remains fully self-explanatory in isolation months later, since the question itself supplies all necessary context. It faithfully captures the complete unit of knowledge the user engaged with rather than a trivial fragment or external addition.


Can We Afford Large-scale Solar PV?

One common objection to the large-scale use of solar PV is that, even with batteries, it effectively requires an entire parallel energy system to meet electricity demand when there’s little or no sun and no battery charge. Even if the solar plus battery system can meet demand 99.9% of the time, supplying that last 0.1% of demand might theoretically require a large amount of expensive infrastructure, making effective costs much higher.

The highlighted passage articulates a central critique often raised about relying heavily on solar photovoltaic (PV) systems combined with batteries for electricity. The objection is that solar power’s inherent intermittency—its inability to generate electricity at night or during prolonged cloudy periods—means that to guarantee continuous supply (i.e., meeting 100% of electricity demand), you must maintain a whole separate, parallel energy system in reserve. This backup system is necessary to cover rare but critical moments when solar plus battery storage falls short, even if these moments are exceedingly infrequent (e.g., just 0.1% of the time).

The implication is that while solar and batteries may handle the vast majority (like 99.9%) of energy needs, the infrastructure needed to cover the remaining tiny fraction could be very large and expensive—potentially doubling energy system costs or more. This additional backup capacity might involve gas turbines or other generation technologies kept on standby but rarely used, inflating the effective cost and complexity of a fully solar-powered grid.

In context, the author is introducing this objection as a widespread concern but later explores how falling costs of solar PV and battery storage, as well as innovative operational strategies (like using gas turbines to charge batteries), can substantially reduce the burden of this backup system. Still, the highlighted passage captures the fundamental challenge: ensuring reliability in a fully solar-based system may demand costly, rarely used parallel infrastructure, which complicates and raises the expense of solar’s large-scale adoption.

Q. What fraction of electricity demand can solar PV meet according to expert consensus, and what fraction requires a parallel energy system?
A. According to expert consensus, solar PV can meet 99.9% of electricity demand, and 0.1% requires a parallel energy system.

This prompt fails on fidelity and stability grounds. First, it fabricates context absent from the source: the highlighted passage never mentions 'expert consensus'—it presents the 99.9%/0.1% split as a hypothetical ('even if the solar plus battery system can meet demand 99.9% of the time') used to illustrate an objection, not as an established factual benchmark. Converting a conditional illustration into a purported consensus figure creates a misleading, unstable claim. Second, it targets the wrong detail: the user's highlight centers on the core insight—the objection that guaranteeing reliability requires an entire parallel energy system whose rarely-used backup capacity could make effective costs much higher—not on memorizing the illustrative percentages themselves. A pluckable prompt would test the substance of the objection (why tail-demand coverage inflates costs), rather than treating decorative example numbers as the durable takeaway.


Can We Afford Large-scale Solar PV?

Q. Why might large-scale solar PV (even with batteries) risk high effective costs?
A. Because it may still require a full parallel energy system to meet demand during rare periods without sun or battery charge, adding expensive infrastructure.

The prompt directly targets the core insight of the highlighted passage: the objection that solar PV plus batteries may require an entire parallel backup energy system to cover rare no-sun/no-charge periods, driving up effective costs. It is atomic (tests one coherent causal idea), faithful to the highlight without introducing external details, and stable—terms like 'parallel energy system,' 'rare periods without sun or battery charge,' and 'expensive infrastructure' are precise and self-explanatory even when reviewed in isolation months later. While omitting the 99.9%/0.1% figures, those are supporting specifics rather than the essential insight, so their absence does not undermine retrievability or meaning.


Can We Afford Large-scale Solar PV?

Q. What is the impact of maintaining parallel backup infrastructure on the effective cost of an energy system?
A. It increases effective cost, even if the infrastructure is rarely used.

The prompt fails on both meaningfulness and stability. It strips away the specific context the user highlighted—the objection that intermittent solar PV plus batteries requires an entire parallel energy system to cover rare shortfall periods—and generalizes it into a near-tautology ('backup infrastructure increases cost'). The answer is trivially obvious and would be answerable without any exposure to the source material, so it tests nothing durable or insightful. Additionally, the vague framing ('an energy system') loses the precise anchor (solar PV intermittency, the 99.9%/0.1% framing) that made the highlighted idea coherent, making the prompt ambiguous when reviewed in isolation months later.


Can We Afford Large-scale Solar PV?

Q. What drives up the effective cost of solar PV systems, even when generation and storage are cheap?
A. The need to maintain a parallel energy system for rare periods when solar and batteries can't meet demand (i.e. lowpoints on the Duck Curve).

The prompt correctly targets the core insight of the highlight—that a rarely-used parallel backup system for periods when solar plus batteries fall short drives up effective costs—but it undermines its own stability by appending '(i.e. lowpoints on the Duck Curve)'. This parenthetical introduces external information not present in the source and is factually misleading: the Duck Curve's low points correspond to midday periods of abundant solar generation (a net-load trough), not the scarce-sun/no-battery-charge periods the highlight describes. Reviewed in isolation months later, a user would either absorb a false association or encounter a contradiction between the stored answer and their knowledge, violating the fidelity and precision requirements for a durable memory prompt.


Can We Afford Large-scale Solar PV?

capacity factor (the ratio of actual solar PV power supplied to maximum theoretical capacity

The author introduces the concept of "capacity factor" as a key metric to evaluate solar photovoltaic (PV) performance in meeting electricity demand. Specifically, the capacity factor is defined as the ratio of the actual amount of solar power generated over a period to the maximum theoretical power that could be generated if the solar panels operated at full capacity continuously.

In context, this metric is crucial because solar panels seldom operate at their maximum output due to factors such as time of day (no generation at night), weather conditions (cloud cover reducing output), and seasonal variations (solar insolation changes). By examining the capacity factor on an hourly and daily basis in California, the author highlights the variability in solar PV output—sometimes producing near full capacity (especially in summer), sometimes far less (notably in winter or cloudy conditions).

Understanding the capacity factor helps quantify how much infrastructure—solar panels and complementary storage or backup systems—is needed to meet electricity demand reliably. Since solar PV does not produce power uniformly or predictably at full rated capacity, system planners must "overbuild" capacity and add storage to cover times when output is low. Thus, capacity factor serves as a foundational parameter linking theoretical panel capacity to real-world energy supply and informs how feasible and costly it is to rely on solar PV to satisfy large portions of electricity loads.

Q. What does _capacity factor_ mean for solar PV?
A. It's the ratio of actual output to maximum possible output.

The prompt directly targets the exact concept the user highlighted: the definition of capacity factor. It is atomic (tests one well-defined idea), faithful to the source (the answer precisely mirrors the highlighted text—ratio of actual output to maximum theoretical capacity), and highly stable since 'capacity factor' is a durable, standard metric in energy systems whose definition will not change over time. The specific framing 'for solar PV' provides built-in context so the prompt remains self-explanatory even when reviewed in isolation months later. Definitional recall like this is ideal for spaced repetition.


Can We Afford Large-scale Solar PV?

Q. What does the capacity factor represent in the context of solar PV performance?
A. The ratio of actual solar PV power supplied to maximum theoretical capacity

The prompt directly targets the exact definitional insight the user highlighted—the definition of capacity factor as the ratio of actual solar PV output to maximum theoretical capacity. It is atomic (tests one well-defined concept), faithful to the highlighted text, and uses precise language ('capacity factor', 'solar PV') that remains self-explanatory when reviewed in isolation months later. While the surrounding article adds richer context about variability and overbuilding, the user's highlight anchors specifically to this definition, making it a durable, meaningful unit of knowledge worth retaining.


Can We Afford Large-scale Solar PV?

During most of 2024, electricity demand didn’t exceed 30,000 megawatts, but during the summer months it regularly exceeded 40,000, and for one brief window it approached 50,000 megawatts.

The highlighted passage points out a key characteristic of electricity demand variability over the course of 2024 in California. The author notes that while the typical demand for most of the year remained below 30,000 megawatts, during the summer there were regular periods when demand spiked above 40,000 megawatts, and even briefly approached 50,000 megawatts.

In context, this observation serves to emphasize the challenge of meeting peak electricity demand with solar PV systems alone. The significant seasonal variation—especially high demand in summer—means that any energy infrastructure designed to meet 100% of demand must be capable of supplying power at these peak levels, not just average levels. This leads to a large amount of infrastructure that remains underutilized much of the time but is essential for meeting peak loads.

Thus, the passage underscores an important implicit claim: large-scale energy systems, whether solar, battery-backed, or alternative generation like gas turbines, must address not only average demand but also peak demand fluctuations that can be substantial and episodic. This necessity complicates the economics and logistics of relying solely on solar PV, as the infrastructure must be overbuilt to handle these peaks, which directly relates to the article’s broader discussion about the feasibility and cost-effectiveness of large-scale solar PV deployment.

Q. How do peak summer and typical electricity demand periods compare in California during 2024?
A. Peak demand exceeds typical demand.

The prompt fails on both meaningfulness and specificity. Its answer—'peak demand exceeds typical demand'—is a trivially obvious fact true of virtually every electricity system, so it can be answered correctly without any retention of the source material, making it worthless for spaced repetition. It also discards everything the user actually highlighted: the concrete figures (typical demand under 30,000 MW vs. summer peaks regularly above 40,000 MW and briefly approaching 50,000 MW) and the core insight they anchor—that infrastructure must be sized for episodic peaks roughly 1.5–2x typical load, forcing costly overbuilding that complicates solar PV economics. A pluckable version would target that specific quantitative gap or its implication, not a generic comparison.


Can We Afford Large-scale Solar PV?

Q. What is the main seasonal variation in California's electricity demand during 2024?
A. Summer demand exceeds 40,000 MW and nears 50,000 MW, compared to under 30,000 MW in other seasons.

The prompt is faithful to the highlighted text but targets the wrong level of detail. According to the interpretation, what made this passage meaningful is its implication: peak demand (~50,000 MW) vastly exceeding typical demand (<30,000 MW) forces any solar-based system to be heavily overbuilt yet underutilized most of the time, undermining the economics of large-scale solar PV. The prompt instead asks for bare recall of three specific megawatt figures from a single state-year—surface-level data points that are fragile to memorize, carry little durable value in isolation, and omit the causal 'so what' the user actually cared about. A pluckable version would tie the peak-versus-average demand gap to the overbuilding and cost implications, making the essential insight—not the decorative numbers—the focus of recall.


Can We Afford Large-scale Solar PV?

Q. What is the main seasonal variation in California's electricity demand during 2024?
A. Demand exceeds 40,000 megawatts in summer and approaches 50,000 megawatts, contrasting with typical levels under 30,000 megawatts during other times.

The prompt is atomic, faithful, and directly tied to what the user highlighted: the single coherent fact that California's 2024 electricity demand stayed under 30,000 MW for most of the year but regularly exceeded 40,000 MW in summer and briefly approached 50,000 MW. This contrast is concrete and self-explanatory in isolation, satisfying the stability criterion, and it captures the empirical anchor behind the article's broader peak-demand argument, satisfying meaningfulness. While the prompt could be strengthened by explicitly connecting the figures to their implication (infrastructure must be sized for peaks, not averages), it cleanly and durably preserves the complete highlighted insight rather than a decontextualized fragment.


Can We Afford Large-scale Solar PV?

Q. What were California’s peak electricity demand levels in 2024?
A. Above 40,000 MW, briefly reaching 50,000 MW.

The prompt fails on both criteria. First, it targets the wrong level of detail: the user's highlight and interpretation center on the durable conceptual insight—that electricity demand varies seasonally, so infrastructure must be sized for rare summer peaks (~50,000 MW) rather than typical loads (~30,000 MW), causing underutilization and complicating the economics of solar PV. Instead, the prompt tests arbitrary, time-bound figures ('above 40,000 MW, briefly reaching 50,000 MW'), which is rote recall of decorative specifics rather than the principle the user cared about. Second, it lacks stability and coherence in isolation: the answer strips away the baseline (~30,000 MW) that gives the peak numbers their meaning, and exact 2024 megawatt values are precisely the kind of context-dependent trivia that becomes vague, forgettable, and low-value on review intervals of months or years. A pluckable version would ask why energy systems must be designed around peak rather than average demand, using the peak-to-typical contrast as supporting context.


Can We Afford Large-scale Solar PV?

Q. What are the peak electricity demand levels in California during 2024?
A. California's peak electricity demand in 2024 was above 40,000 megawatts with brief instances reaching 50,000 megawatts.

The prompt fails on fidelity and meaningfulness. The user's highlight, as interpreted, anchors a structural insight: California's demand varies dramatically between a typical baseline (~under 30,000 MW) and summer peaks (regularly above 40,000 MW, briefly approaching 50,000 MW), which forces any solar-based system to be overbuilt for rare peaks and thus underutilized much of the time. The memory prompt strips away this comparative context and tests only an isolated numeric fragment ('peak levels were above 40,000 MW'). Without the baseline figure, the number is decontextualized and loses the very point the user found interesting—the gap between average and peak demand and its economic implications. Additionally, the answer introduces slight drift ('reaching' vs. 'approached' 50,000 MW), and demanding precise recall of year-specific megawatt figures months later is unstable and low-value compared to remembering the underlying principle. A pluckable version would target the causal insight (e.g., why peak demand complicates the economics of solar-only systems) or at minimum preserve the baseline-vs-peak contrast.


Can We Afford Large-scale Solar PV?

Q. How does California’s summer 2024 electricity demand (in MWh) compare to other seasons?
A. Summer demand exceeds 40,000 MW and nears 50,000 MW, compared to under 30,000 MW in other seasons.

The prompt fails on both meaning and stability grounds. First, it reduces the highlighted insight to a bare numerical fragment (30k/40k/50k MW) stripped of the significance the user actually engaged with: that substantial seasonal peak demand forces any 100%-reliable infrastructure to be overbuilt relative to average load, which is central to the article's argument about solar PV economics. Testing raw figures leaves the insight decontextualized and less durable than the underlying principle. Second, it contains a precision error that undermines stability: the question labels the quantity 'in MWh' (energy) while the answer and source use MW (power), creating confusion when reviewed in isolation months later. Finally, the answer's phrase 'under 30,000 MW in other seasons' slightly overgeneralizes the source claim ('during most of 2024, demand didn't exceed 30,000 MW'), introducing fidelity drift.


Can We Afford Large-scale Solar PV?

Q. In California summer 2024, how many MWH was peak electricity demand compared to the seasonal average?
A. ≈10,000 MW higher (average ≈40,000 MW vs. peak ≈50,000 MW)

This prompt is not pluckable for several reasons. First, it fails fidelity to the highlighted text: the source states that demand 'didn't exceed 30,000 MW' most of the year, 'regularly exceeded 40,000 MW' in summer, and 'approached 50,000 MW' briefly—it never states a 'seasonal average of ~40,000 MW.' The prompt invents an 'average' figure and reframes the comparison, so the answer cannot be reliably reconstructed from what the user actually read. Second, there is a unit inconsistency: the question asks 'how many MWH' while the answer is given in MW (megawatts measure instantaneous demand; megawatt-hours measure energy), creating confusion on long review intervals. Third, it misses the core insight the user engaged with—per the interpretation, the interesting point is the causal/economic implication that infrastructure must be sized for rare peaks (~50,000 MW) while sitting underutilized when demand is below ~30,000 MW, complicating solar-only economics. A pluckable prompt would target that durable conceptual takeaway (e.g., the ~20,000 MW spread between baseline and peak and its implications for overbuilding), rather than a distorted numeric comparison with ambiguous framing.


Summary: The article examines the claim that semiconductor and solar PV manufacturing depends entirely on high-purity quartz from Spruce Pine, North Carolina. While Spruce Pine does supply 70-90% of the world's high-purity quartz used for crucibles in silicon ingot manufacturing, alternatives exist but are more expensive or less efficient. The author concludes that Spruce Pine represents a significant bottleneck but not an irreplaceable component of semiconductor manufacturing.

Does All Semiconductor Manufacturing Depend on Spruce Pine Quartz?

Quartz crucibles are indeed necessary for most semiconductor manufacturing, and Spruce Pine is where most of this quartz comes from. Spruce Pine quartz isn’t quite an irreplaceable linchpin in semiconductor manufacturing.

The highlighted passage emphasizes a nuanced position regarding the role of Spruce Pine quartz in semiconductor manufacturing. On one hand, it asserts that quartz crucibles—containers made from quartz used to hold molten silicon during the production of silicon ingots—are essential for most semiconductor manufacturing processes. Furthermore, it acknowledges that most of this high-purity quartz used for crucibles comes specifically from Spruce Pine, North Carolina.

However, the passage carefully qualifies this by stating that Spruce Pine quartz is not an entirely irreplaceable or singular "linchpin" in the industry. This means that while Spruce Pine is currently the main source of this crucial material, it does not solely and absolutely hold semiconductor manufacturing hostage. There are alternatives, though they may be less developed, more expensive, or less effective at the moment.

In context, the author is clarifying a common narrative circulating online that claims semiconductor manufacturing—and by extension the global tech economy—is utterly dependent on Spruce Pine quartz. The author counters that while Spruce Pine quartz is highly significant and a major current supplier, it does not represent a single point of absolute failure. The industry is aware of this bottleneck and is actively pursuing alternative sources and materials.

Thus, the core idea is that Spruce Pine quartz is critically important but not uniquely indispensable—its dominance is due to a favorable combination of purity, availability, and price rather than an absence of substitutes. This distinction helps temper alarmist claims and highlights ongoing efforts to build more resilient supply chains for semiconductor manufacturing.

Q. What role does the quartz mine in Spruce Pine, NC play in silicon wafer production?
A. It produces a highly pure quartz that offers an optimal balance of cost, purity, and availability for manufacturing silicon wafers.

The prompt misses the core insight the user highlighted. The passage's central point is the nuanced claim that while quartz crucibles are essential and Spruce Pine supplies most of the high-purity quartz, it is 'not quite an irreplaceable linchpin'—alternatives exist, so its dominance reflects economics rather than absolute necessity. The memory prompt instead tests only a secondary explanatory detail (the cost/purity/availability balance behind Spruce Pine's dominance) and omits the 'not irreplaceable' qualification entirely, which was the heart of what the user engaged with. Additionally, the answer doesn't cleanly match the question: it asks about the mine's 'role' in wafer production (providing quartz for crucibles that hold molten silicon) but answers with the reasons for its market dominance, creating ambiguity that undermines stability on long review intervals.


Q. How is Spruce Pine, NC involved in the silicon wafer production?
A. The quartz mine produces a highly pure form of quartz. It is a good balance between cost, purity, and availability

The prompt targets the core insight anchored by the highlight: Spruce Pine's significance stems from its high-purity quartz and its favorable balance of cost, purity, and availability—which implicitly conveys the 'important but not uniquely indispensable' nuance the user engaged with. It is atomic (tests one well-defined concept), uses concrete language ('quartz mine,' 'highly pure quartz') that remains self-explanatory months later without the original article, and stays faithful to the highlighted idea rather than testing trivialities or external details. While it could be strengthened by explicitly noting that Spruce Pine is 'not an irreplaceable linchpin' or mentioning the quartz crucible application, these omissions do not undermine the durability or clarity of the recalled knowledge.


Q. Where does most of the quartz used in semiconductor manufacturing come from?
A. Spruce Pine

This prompt fails the fidelity criterion because it tests only a surface detail while missing the core insight the user highlighted. The highlight's interesting content is the nuanced qualification: Spruce Pine quartz is the dominant source for crucibles, but it is NOT an irreplaceable linchpin—its dominance reflects favorable purity, availability, and price rather than an absence of substitutes. The generated prompt ('Where does most quartz come from?') reduces this self-contained, counterintuitive claim to a trivial geographic fact, leaving the essential half of the insight (the non-irreplaceability) untested. A pluckable version would target the full concept, e.g., asking why Spruce Pine quartz is significant yet not a single point of failure for semiconductor manufacturing.


Q. Are quartz crucibles necessary for most semiconductor manufacturing?
A. Yes, quartz crucibles are necessary for most semiconductor manufacturing.

This prompt is unpluckable because it targets the wrong detail. The user's highlight—and the interpretation—centers on the nuanced claim that while quartz crucibles are necessary and Spruce Pine is the dominant source of high-purity quartz, Spruce Pine is NOT an irreplaceable linchpin: alternatives exist, and its dominance reflects purity, availability, and price rather than absolute uniqueness. The generated prompt instead reduces the insight to a trivially true yes/no fact ('are quartz crucibles necessary?'), testing a surface-level fragment while discarding the very distinction the user found interesting. It also fails atomicity of meaning—it captures no causal or explanatory content (why alternatives exist, why Spruce Pine dominates)—so it would provide little durable value across spaced-repetition intervals.


Q. What is the name of the town where most quartz for semiconductor manufacturing comes from?
A. Spruce Pine

While the prompt is stable—it is atomic, precise, and cleanly answerable in isolation—it fails the meaningfulness criterion because it targets a surface detail rather than the core insight. The user's highlight and interpretation center on a nuanced, qualified claim: quartz crucibles are essential, most high-purity quartz does come from Spruce Pine, BUT it is 'not quite an irreplaceable linchpin' because alternatives exist. The article's entire thesis (reflected in its title) is answering that qualified question, yet the prompt only tests the supporting factoid of the town's name, stripping away the very distinction ('important but not uniquely indispensable') that made the passage worth highlighting. Per the guidance against testing trivial fragments that leave the insight decontextualized, a stronger prompt would ask why Spruce Pine quartz is significant yet not a single point of failure for semiconductor manufacturing.


Spruce Pine isn’t the only source of natural high-purity quartz. China produces around 5,000 tons annually, and is hoping to scale up its operations to 20,000 tons or more. Norway and Russia both produce a small amount, and historically Brazil was a major supplier.

The highlighted passage places Spruce Pine quartz in a broader global context by clarifying that it is not the sole source of natural high-purity quartz for semiconductor manufacturing. While Spruce Pine is often emphasized due to its dominant market share (70–90%), other regions like China, Norway, Russia, and historically Brazil also contribute to the supply. China currently produces a smaller volume (about 5,000 tons annually) but aims to significantly increase output to 20,000 tons or more. Norway and Russia have smaller production levels, and Brazil was once a major supplier. This information suggests that while Spruce Pine is critical today, there are alternative sources in operation or development globally, which could diversify supply and mitigate risks associated with overreliance on a single region. It underscores that the reliance on Spruce Pine quartz is significant but not absolute, and that the global supply chain includes multiple players with potential to expand production.

Q. [Alternative sources high-purity quartz] Name a few countries that currently have active quartz mines, and which ones are potential sources under investigation:
A. Norway and Russia have active quartz mines; Canada, South Carolina (USA), Sri Lanka, and Australia are potential sources under investigation.

This prompt is not pluckable for several reasons. First, it violates atomicity by being a compound question that tests two distinct things at once: countries with active mines AND potential sources under investigation. Second, it has poor fidelity to the highlighted concept—the highlight centers on China's current production (~5,000 tons annually, scaling toward 20,000+) and Brazil's historical role, yet the prompt omits China entirely, which is the most significant alternative source mentioned. Third, the answer introduces external information not grounded in the highlight or interpretation (Canada, South Carolina, Sri Lanka, Australia as 'potential sources under investigation'), which risks instability since the user's engagement was anchored to the specific passage about existing producers. A pluckable prompt would have isolated one clean fact from the highlight, such as asking about China's current output and expansion target, or which countries besides Spruce Pine currently produce high-purity quartz.


Q. [Alternative sources high-purity quartz] What are other countries that have quartz deposits?
A. Norway and Russia have active mines, Canada, South Carolina, Sri Lanka and Australia are being investigated as potential sources

The prompt fails on fidelity and stability. The highlighted passage specifically names China (~5,000 tons annually, aiming to scale to 20,000+), Norway, Russia, and historically Brazil as alternative high-purity quartz sources. The prompt's answer omits China and Brazil—the most substantive details in the highlight—and instead lists Canada, South Carolina, Sri Lanka, and Australia as 'potential sources,' information absent from both the highlight and its interpretation. Additionally, the question 'What are other countries that have quartz deposits?' is vague and compound: it conflates currently active producers with speculative future sources, making consistent retrieval difficult months later. A pluckable version would target the specific, concrete facts the user actually engaged with, such as China's production volume and expansion plans.


Q. Which countries besides China produce small amounts of high-purity quartz?
A. Norway and Russia

This prompt targets a surface-level trivia fragment rather than the core insight the user engaged with. The highlight's essential point—captured clearly in the interpretation—is that Spruce Pine, despite its 70–90% market dominance, is not the sole source of natural high-purity quartz, with alternatives existing in China (scaling toward 20,000+ tons), Norway, Russia, and historically Brazil. The prompt instead tests recall of a narrow list ('Norway and Russia') of minor producers, which is exactly the kind of decontextualized detail likely to fade on long review intervals. The question framing is also unstable: excluding 'China' from the query is arbitrary and confusing when reviewed in isolation (China is itself one of the alternative sources), and the phrase 'produce small amounts' invites ambiguity since Brazil was historically a major supplier and China's output is growing. A pluckable version would anchor to the durable concept, e.g., 'Is Spruce Pine the only source of natural high-purity quartz used in semiconductor manufacturing?' rather than testing an isolated roster of minor producers.


Q. Which country is aiming to increase its production of high-purity quartz to 20,000 tons or more?
A. China

This prompt is pluckable. It is atomic, testing a single well-defined fact (which country aims to scale high-purity quartz output to 20,000+ tons), and it is directly faithful to the highlighted text, which explicitly names China and its expansion target. The embedded figure ('20,000 tons or more') acts as built-in context, making the prompt self-explanatory and stable for isolated review months later—no access to the original article is needed to understand or answer it. While narrower than the full 'Spruce Pine isn't the only source' insight, it isolates a concrete, durable detail (China's ambition to become a much larger supplier) that supports exactly what the user engaged with: the existence and growth potential of alternative quartz sources outside Spruce Pine.