Prerequisites Prompt: What Background Do You Need to Understand This?

C011 🧠 Understand Difficult Text 2 Prompts

Prerequisites Prompt: What Background Do You Need to Understand This?

Don’t struggle blind: AI prompts that identify what background knowledge you’re missing and create a mini crash course.

6 min read 2 Prompts Guide 3 of 6
PR052 The Prior Knowledge Primer
Before reading about an unfamiliar topic
I’m about to read about [topic]. Before I start, help me activate what I already know: – What are the key concepts I probably already understand? – What related topics might connect to this? – What common misconceptions exist about this topic? – What should I be ready to update or challenge in my existing understanding?
PR053 The Knowledge Gap Identifier
When struggling due to missing background
I’m reading this passage: “[paste passage]” I’m struggling because I think I’m missing background knowledge. Help me identify: – What concepts or references does this assume I know? – What should I briefly read about before continuing? – What can I infer from context vs. what do I need to look up? – Give me a 2-3 sentence primer on what I’m missing.
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When to Use a Background Knowledge Prompt

You’ve hit that wall before. You’re reading an article, academic paper, or technical document, and the words make sense individually β€” but together, they mean nothing. You re-read the paragraph. Still nothing. The problem isn’t your reading skill. It’s that the author assumes you know something you don’t.

This is the background knowledge problem, and it’s the hidden obstacle behind most reading struggles. Authors write for audiences who share their foundational knowledge. When you’re not that audience, you’re trying to build a house without a foundation.

The background knowledge prompt solves this by diagnosing what you’re missing and filling the gap β€” without derailing you into a 20-hour prerequisite course. You get just enough context to continue, not an entire textbook.

Use these prompts when you encounter text that references concepts, events, theories, or terminology you don’t recognize β€” or when explanations don’t stick because you’re missing the context that makes them meaningful.

The Two Prompts: Proactive vs. Reactive

PR052 (Prior Knowledge Primer) is proactive. Use it before you start reading about an unfamiliar topic. It activates what you already know, connects the new topic to familiar concepts, and warns you about common misconceptions you might bring to the reading.

This matters because learning research shows that activating prior knowledge before reading dramatically improves comprehension and retention. You’re not starting from zero β€” you’re connecting new information to existing mental frameworks.

PR053 (Knowledge Gap Identifier) is reactive. Use it while reading when you’ve hit a wall. You paste the confusing passage, and the prompt identifies what the author assumes you know, distinguishes between what you can infer from context versus what requires external knowledge, and provides a mini crash course on the missing pieces.

πŸ’‘ Pro Tip

Start with PR052 for any topic that’s genuinely new to you. If you skip the proactive step and jump straight into reading, you’ll end up using PR053 repeatedly β€” which works, but is less efficient than preparing your mental scaffolding first.

Building a Mini-Learning Plan

Sometimes the prerequisites to understand a topic are more substantial than a 2-3 sentence primer can cover. In these cases, use PR053’s output as a starting point for a focused learning plan.

When PR053 identifies missing concepts, ask a follow-up: “Give me a 10-minute crash course on [concept] β€” just enough to understand the passage I’m reading, not to become an expert.” This gets you targeted learning, not comprehensive coverage.

The key is minimum viable context. You need enough to follow the argument, not enough to write your own paper on the topic. If PR053 says you need to understand “Keynesian economics,” you don’t need a semester of macroeconomics. You need 2-3 core ideas that illuminate the passage you’re reading.

For deeper understanding, pair this with the Simplify Complex Text workflow, which breaks down difficult passages after you have the background to understand them.

πŸ“Œ The Background Knowledge Workflow

1. Before reading: Use PR052 to activate prior knowledge and flag misconceptions. 2. While reading: When stuck, use PR053 to diagnose what’s missing. 3. Fill gaps: Get a mini crash course (2-3 sentences or 10 minutes max). 4. Continue reading: Now the passage should make sense. 5. Build analogies: Use the Analogy Builder to connect new knowledge to familiar domains.

Follow-Up Prompts for Deeper Learning

Once you’ve identified your knowledge gaps, several follow-up strategies can deepen your understanding without overwhelming you.

For abstract concepts: “Explain [concept] using an analogy from [familiar domain].” This connects the new knowledge to something you already understand, making it sticky.

For technical terms: Use the Understand Difficult Text pillar for jargon translation and plain English explanations.

For historical or contextual background: “What was happening in [field/time period] that makes this passage make sense?” Often, understanding the context in which something was written illuminates its meaning.

For methodological assumptions: “What assumptions does [field/discipline] make that an outsider might not share?” Academic papers especially assume disciplinary conventions that outsiders miss.

Common Scenarios and Solutions

Academic papers: Research assumes you know the field’s core debates, methodologies, and terminology. PR053 is ideal here β€” paste the abstract or introduction and ask what background you’re missing before diving in.

Technical documentation: Often assumes familiarity with related systems, prior versions, or industry standards. The missing context prompt reveals what foundation the documentation builds on.

News and current events: Articles assume you’ve been following a story. PR052 helps you catch up: “I’m about to read about [ongoing situation]. What background do I need to understand today’s developments?”

Historical or philosophical texts: Authors wrote for their contemporaries. PR053 identifies what was common knowledge then that isn’t now β€” the cultural, intellectual, or political context that makes arguments make sense.

Return to the AI for Reading hub for the complete prompt ecosystem, or explore more comprehension tools in the Understand Difficult Text pillar.

Frequently Asked Questions

Use it when you’re struggling repeatedly with a topic β€” when explanations don’t stick because you’re missing foundational concepts. A background knowledge prompt diagnoses what’s missing rather than just simplifying, which helps you build lasting understanding rather than temporary comprehension.
PR052 (Prior Knowledge Primer) is proactive β€” use it BEFORE reading to activate what you know and prepare for misconceptions. PR053 (Knowledge Gap Identifier) is reactive β€” use it WHILE reading when you’ve hit a wall and need to diagnose what’s missing.
Aim for the minimum viable context β€” enough to follow the argument, not enough to become an expert. The 2-3 sentence primer from PR053 is usually sufficient. If you need more, that’s a sign the topic requires dedicated study, not a quick fix.
Absolutely β€” academic papers are the ideal use case. Research assumes disciplinary knowledge that outsiders lack. PR053 is especially useful for identifying assumed concepts, methodological background, or field-specific debates you need to understand.
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Paper Map Prompt: Summarize Each Section the Right Way

C061 πŸ”¬ Research Papers 1 Prompt

Paper Map Prompt: Summarize Each Section the Right Way

Navigate any academic paper systematically β€” get section-by-section guidance, jargon previews, and focused reading questions before you dive in.

5 min read 1 Prompt Guide 1 of 6
PR040 Academic Paper Navigator
Use before reading a research paper
I’m reading an academic paper. Here’s the abstract: “[paste abstract]” Before I read the full paper, help me: – Identify the research question and why it matters – Understand what to pay attention to in each section (intro, methods, results, discussion) – Flag jargon I should look up first – Tell me what questions to keep in mind while reading
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The Anatomy of an Academic Paper (And Why It Matters)

Research papers aren’t written like articles. They follow a rigid structure β€” abstract, introduction, methods, results, discussion β€” and each section serves a specific purpose. Most readers make the mistake of treating a paper like a long article: starting at the beginning and reading straight through. That’s the slowest, most frustrating way to summarize academic paper sections.

The smarter approach is to map the paper first. Before you read a single full section, understand what the paper is about, what each section will contribute, and what you should be watching for. That’s exactly what the paper map prompt does.

The Prompt: How to Use It

PR040 works differently from most reading prompts. Instead of analyzing text you’ve already read, it prepares you to read more effectively. You paste just the abstract, and AI gives you a complete reading map.

Research Question and Significance: The prompt identifies what the paper is actually investigating β€” not just the topic, but the specific question and why it matters.

Section-by-Section Guidance: For each major section, AI tells you what to pay attention to in Introduction, Methods, Results, and Discussion.

Jargon Preview: The prompt flags terms you should look up before reading, removing the friction that causes most people to give up mid-paper.

Reading Questions: Questions to carry with you through the paper, turning passive reading into active analysis.

⚑ Pro Tip

After your first pass through the paper, come back to AI with individual sections. Paste the methods section and ask: “Explain this methods section in plain English. What exactly did they do?” This is where the Methods Decoder becomes your next tool.

Example Output: What a Paper Map Looks Like

πŸ’‘ Sample Paper Map

Research Question: Does sleep quality (not just duration) predict next-day cognitive performance in working adults?

Why It Matters: Most sleep research focuses on duration. If quality independently predicts performance, workplace policies need different optimization strategies.

Introduction β€” Watch For: How the authors define “sleep quality” vs. “sleep duration”

Methods β€” Watch For: How they measured sleep quality (subjective vs. objective), sample size, confounders controlled

Results β€” Watch For: Effect sizes (not just statistical significance)

Discussion β€” Watch For: Whether the authors overstate their findings, what limitations they acknowledge

Jargon to Look Up: polysomnography, sleep architecture, N2/N3 stages, actigraphy

With this map, you read the paper in 20 minutes instead of 45 β€” and you understand it better.

Building on the Paper Map

The paper map is your first move with any research paper. After reading with the map’s guidance, use these companion prompts:

Methods Decoder β€” Explain procedures, variables, and statistics in plain English

Limitations & Assumptions β€” Find what the paper admits and what it doesn’t

Related Work Finder β€” Build your reading list after finishing

Frequently Asked Questions

Yes β€” the abstract gives AI enough to map the paper’s structure and generate reading questions. Paste individual sections as you read for deeper summaries.
A generic summary flattens everything into one paragraph. The Paper Map preserves structure β€” telling you what each section contributes, what to watch for, and what questions to carry forward. It’s a reading guide, not a replacement for reading.
Yes. The prompt adapts to any discipline β€” it identifies research questions, key arguments, evidence structure, and discussion points regardless of field.
No. The prompt is designed to help you read the paper better, not skip it. Use the map to orient yourself before reading, then return to AI with specific sections you find confusing.
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Opinion/Editorial Decoder: Separate Argument from Persuasion

C036 πŸ“‹ Prompts Library Critical Reading

Opinion/Editorial Decoder

Decode persuasion: identify explicit arguments, emotional appeals, rhetorical moves, and build counterarguments.

5 min read 1 Prompt Genre Guide
PR042 Opinion/Editorial Decoder
For columns, op-eds, editorials
Here’s an opinion piece: “[paste piece]” Decode the persuasion: – What’s the explicit argument? – What emotional appeals are being used? – What rhetorical moves does the author make? – What’s the strongest point? Weakest? – What would a thoughtful counterargument look like?
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Why Opinion Pieces Need Special Analysis

News articles claim to inform. Opinion pieces claim to persuade. This fundamental difference matters for how you read. Opinion pieces don’t hide their agenda β€” they’re openly trying to change your mind. That’s fine. But it means you need different tools to evaluate them.

The mistake readers make is reading opinion as if it were news. An editorial’s job isn’t to present balanced facts β€” it’s to argue a position. That argument may be sound or weak, the evidence may be cherry-picked or comprehensive, the emotional appeals may be fair or manipulative. But you can’t assess any of that if you’re reading passively.

PR042 separates these layers. You get the explicit argument stated plainly, the emotional appeals identified, the rhetorical moves cataloged, the strengths and weaknesses assessed, and a thoughtful counterargument generated. After that analysis, you can agree or disagree on substance, not style.

Common Rhetorical Moves to Watch For

Emotional appeals: Fear (“if we don’t act…”), outrage (“how dare they…”), pride (“we’re better than this…”), sympathy (“imagine being in their shoes…”). These aren’t inherently manipulative β€” emotions matter for decisions β€” but they can substitute for evidence.

Anecdotes as evidence: Personal stories are compelling but prove nothing about general patterns. Watch for anecdotes doing the work that data should do. “I know someone who…” is not the same as “Studies show…”

Authority appeals: Citing experts, credentials, experience. Legitimate when the authority is relevant and the claim is within their expertise. Illegitimate when “as an X, I believe Y” where X has nothing to do with Y.

Straw men: Misrepresenting the opposing view to make it easier to attack. Watch for “they say” followed by something no thoughtful person on that side would actually claim.

False dichotomies: “Either we do X or disaster follows.” Most situations have more than two options. Watch for “either/or” framings that exclude middle paths.

For deeper analysis of bias and framing, see the Critical Reading pillar and the News Article Critical Lens.

πŸ’‘ The Strongest/Weakest Test

When PR042 identifies the strongest and weakest points, pay attention. The strongest point is often buried mid-piece, surrounded by weaker supporting arguments. The weakest point is often early or late β€” where emotional momentum can carry it. If you were to only engage with one part of the piece, engage with the strongest point. That’s where the real debate lives.

Building Counterarguments

The final question in PR042 β€” “What would a thoughtful counterargument look like?” β€” is the most valuable. A counterargument isn’t a dismissal. It’s the strongest case the other side could make.

Good counterarguments do three things: offer alternative interpretations of the same evidence, identify considerations the author didn’t address, and specify conditions under which the argument might not hold. “This is wrong” is not a counterargument. “This might be true in context A but not in context B” is.

Building counterarguments isn’t about balance for its own sake. It’s about understanding the actual debate. If you can’t articulate the strongest opposing view, you don’t fully understand the issue. For more on argument structure, see the Argument Map prompt.

πŸ“Œ When to Use Editorial Decoder vs. News Lens

Use Editorial Decoder (PR042) for opinion pieces, columns, editorials β€” content where the author explicitly argues a position. Use News Article Critical Lens (PR041) for news reporting that claims objectivity. The distinction matters: news claims to inform; opinion claims to persuade. Different claims require different analysis.

What Editorial Analysis Reveals

Running PR042 on opinion pieces over time reveals patterns. You’ll notice that certain publications consistently use certain techniques. You’ll notice that your own emotional responses correlate with specific rhetorical moves. You’ll notice that arguments you agree with are just as full of persuasion techniques as arguments you disagree with.

This isn’t cynicism β€” it’s literacy. Skilled writers use rhetorical techniques because they work. Identifying them doesn’t mean dismissing the argument. It means evaluating the argument on its merits, separate from the packaging. The goal is informed agreement or disagreement, not reflexive acceptance or rejection.

For the complete framework of critical reading tools, explore the AI Reading Prompts Library and the AI for Reading hub.

Frequently Asked Questions

Argument is the logical structure: claim, reasons, evidence. Persuasion includes everything else used to make you agree: emotional appeals, rhetorical techniques, framing, word choice, and credibility signals. A piece can have a weak argument but strong persuasion β€” or a strong argument buried in poor persuasion. The decoder separates these so you can evaluate each independently.
No β€” it’s literacy. Skilled writers use rhetorical techniques because they work. Identifying them doesn’t mean dismissing the argument; it means evaluating the argument on its merits, separate from the packaging. You might agree with a piece AND recognize its persuasion techniques. The goal is informed agreement, not reflexive rejection.
A good counterargument isn’t a dismissal β€” it’s the strongest case the other side could make. The prompt asks “What would a thoughtful counterargument look like?” not “What’s wrong with this?” Focus on: alternative interpretations of the same evidence, considerations the author didn’t address, and conditions under which the argument might not hold.
Use the News Article Critical Lens (C035) for news, which focuses on sources, framing, and missing context. Use this Editorial Decoder for opinion pieces, columns, and editorials where the author explicitly argues a position. The distinction: news claims objectivity; opinion pieces don’t β€” they’re openly persuasive, which requires different analysis.
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Prompts Library Pillar

News Article Critical Lens: Read News Like a Media Analyst

C035 πŸ“‹ Prompts Library 1 Prompt

News Article Critical Lens: Read News Like a Media Analyst

Analyze news articles for hooks vs substance, source credibility, framing, missing context, and follow-up questions.

5 min read 5-Part Analysis Critical Reading
PR041 News Article Critical Lens
When reading news and current events
Here’s a news article: “[paste article]” Help me read it critically: – What’s the news hook vs. the actual substance? – What sources are cited and what’s their credibility? – What context is missing? – What’s the framing, and how might it differ elsewhere? – What follow-up questions should I have?
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Hook vs Substance

Every news article has two layers: the hook (why you’re reading it today) and the substance (the actual information). Learning to read news critically AI-assisted means separating these layers.

The hook is what makes something “news” β€” conflict, drama, surprise, scandal, celebrity, crisis. Journalists are trained to lead with the hook because it captures attention. But the hook often distorts the substance.

A headline like “CEO Resigns Amid Scandal” has a powerful hook. But the substance might be: CEO planned retirement months ago, “scandal” was a minor compliance issue already resolved. The hook creates urgency and emotion. The substance is routine.

PR041 asks: “What’s the news hook vs. the actual substance?” This forces you to notice the difference. Once you see the pattern, you can’t unsee it.

Source Analysis

Who’s quoted matters as much as what’s said. Analyze news article credibility by evaluating sources:

Named experts vs “sources say”: Anonymous sources can be necessary for sensitive stories, but they’re also easy to fabricate or misrepresent. Named, credentialed experts are more trustworthy.

Primary vs aggregated: Is this outlet doing original reporting, or summarizing what another outlet reported? Aggregation loses nuance and can introduce errors.

Conflicts of interest: Is the expert quoted because they’re knowledgeable, or because they have a stake in a particular narrative? Industry spokespeople are not neutral.

What’s NOT sourced: Claims presented as fact without attribution are red flags. “Experts agree…” “Studies show…” Without specifics, these are editorial assertions disguised as evidence.

πŸ’‘ Pro Tip

When AI analyzes sources, ask follow-up: “What would a skeptical reader want to verify independently?” This identifies the weakest links in the source chain.

Framing Analysis

News framing is how a story is positioned. The same facts can support very different narratives depending on what’s emphasized, what’s downplayed, what vocabulary is used, and what context is included or excluded.

Example: A protest. One outlet: “Peaceful demonstrators demand change.” Another: “Crowds disrupt traffic, businesses.” Same event, different frames. Neither is lying β€” but each selects facts that fit a narrative.

PR041 asks: “What’s the framing, and how might it differ elsewhere?” This trains you to see the editorial choices behind what appears to be neutral reporting.

πŸ“Œ Missing Context

What’s NOT in an article often matters more than what is. Historical background, alternative explanations, dissenting views, industry context β€” journalists can’t include everything. PR041 asks what context is missing so you know what to look up yourself.

The Prompt in Practice

PR041 generates five outputs for any news article:

1. Hook vs substance: Separates the attention-grabbing element from the actual information.

2. Source credibility: Evaluates who’s quoted and what their reliability is.

3. Missing context: Identifies what background would change your interpretation.

4. Framing analysis: Shows how the story is positioned and how alternatives might differ.

5. Follow-up questions: Suggests what to investigate further before forming opinions.

Use this for important or controversial news. The overhead isn’t worth it for routine stories, but for anything that might influence your beliefs or decisions, the 2-minute analysis pays dividends.

For deeper bias detection, see the Critical Reading pillar. For the full prompt ecosystem, explore the AI for Reading hub.

Frequently Asked Questions

No β€” the overhead isn’t worth it for routine news. Use it for important stories, controversial topics, or anything that might influence your beliefs or decisions. Over time, you’ll internalize the framework and apply it automatically without the prompt.
No single source is always credible. Evaluate per-story: Who’s quoted? Are claims sourced? Is this original reporting or aggregation? What’s the outlet’s track record on this topic? PR041 helps you ask these questions systematically.
Good β€” that’s critical thinking. AI provides a structured analysis, not the final word. If you disagree, articulate why. You might catch something AI missed, or the process of disagreement might refine your own thinking. Either way, you win.
This prompt analyzes structure and technique: hook vs substance, source quality, framing choices. Bias checking focuses more on ideological slant. Both matter β€” this prompt is about reading technique, bias checking is about content direction. Use both for complete analysis.
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Jargon Translator: Convert Technical Writing to Plain English

C010 🧠 Understand Difficult Text 1 Prompt

Jargon Translator: Convert Technical Writing to Plain English

One prompt to decode jargon: extract technical terms, define in plain English, and get real-world examples for each.

5 min read Term-by-Term Guide 2 of 6
PR017 The Phrase Unpacker
For technical phrases, jargon, or expressions
This phrase appears in my reading: “[phrase or idiom]” Full context: “[paste surrounding sentences]” Unpack this phrase: – Literal vs. intended meaning – Origin or common usage pattern – What work is this phrase doing in the passage? – How would the meaning shift if stated more directly?
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What Jargon Hides

Every field has its secret language. Legal contracts say “notwithstanding the foregoing.” Medical papers mention “comorbidities” and “contraindications.” Tech articles assume you know what “latency,” “throughput,” and “edge computing” mean.

Jargon isn’t just big words β€” it’s words used in specialized ways. “Significant” in statistics doesn’t mean “important.” “Volatile” in chemistry doesn’t mean “temperamental.” “Exposure” in finance doesn’t mean “publicity.” If you don’t catch these specialized meanings, you think you understand when you don’t.

The worst part: jargon compounds. One undefined term leads to another. By the third paragraph, you’re lost β€” not because the ideas are hard, but because the vocabulary has locked you out. To translate jargon into plain English, you need more than a dictionary. You need context.

The Prompt: Unpack Phrases in Context

The Phrase Unpacker prompt (PR017) doesn’t just define words β€” it analyzes how they function in your specific passage. You provide the phrase and its surrounding context, and the prompt unpacks four things:

Literal vs. intended meaning: What do the words technically say versus what the author actually means? Technical jargon often uses familiar words in unfamiliar ways. “Market correction” sounds gentle; it means prices dropped significantly.

Origin or common usage: Where does this expression come from? Is it standard terminology in this field, or is the author using it idiosyncratically? Knowing this helps you recognize it elsewhere.

What work the phrase is doing: Why did the author use this phrase here? Is it signaling expertise, hedging a claim, appealing to authority, or simply using the standard term? Understanding function helps you read critically.

How meaning would shift if stated directly: What would the passage say in plain language? This is your translation β€” the jargon-free version you can actually understand and remember.

πŸ’‘ Pro Tip

Always include surrounding sentences as context. The same phrase can mean different things in different passages. “Risk exposure” in a medical paper vs. a financial report vs. a cybersecurity analysis requires different translations.

Output Format: What You’ll Get

When you use PR017 with a technical phrase, you’ll receive a structured breakdown that looks something like this:

For the phrase “asymmetric information” in an economics passage, you’d get: the literal meaning (one party knows more than another), the field-specific usage (a market condition where buyers and sellers have unequal knowledge), the rhetorical function (establishing why markets fail), and the plain English translation (the seller knows something the buyer doesn’t).

This output gives you three things: comprehension (you understand this passage), retention (you’ll recognize the term later), and transfer (you can use the term correctly yourself).

Quality Checks: Verify Your Understanding

After unpacking jargon, verify your understanding with these checks:

The restatement test: Can you explain the passage in your own words without using the jargon? If you can only repeat the technical terms, you haven’t truly understood β€” you’ve just memorized.

The example test: Can you give a concrete example of what the jargon refers to? If “liquidity risk” is just an abstract phrase to you, ask for a real-world scenario. Now it’s a bank not having enough cash when depositors want withdrawals.

The recognition test: Would you spot this jargon and know its meaning if you saw it in a different passage? If yes, you’ve learned the term. If no, you’ve only translated this one instance.

For more comprehensive vocabulary work, see the Glossary from Article prompt (C014) which extracts all key terms at once. For full text simplification beyond just jargon, use the 3-Step Simplification Workflow (C009).

πŸ“Œ When to Use This Prompt

Use the Jargon Translator when you understand the grammar and structure but get stuck on specific terms. If the whole passage is difficult β€” not just the vocabulary β€” start with C009 instead. If you need to learn all terms from an article systematically, use C014.

Common Jargon Patterns to Watch

Nominalizations: Verbs turned into nouns (“utilize” β†’ “utilization,” “implement” β†’ “implementation”). These make sentences longer and vaguer.

Acronyms and initialisms: Every field has them. AI, ML, ROI, KPI, EBITDA, CAC, LTV. Don’t assume you know β€” “CAC” means “customer acquisition cost” in business but “circumferential arm circumference” in nutrition research.

Field-specific meanings: Common words with uncommon meanings. “Leverage” (debt), “exposure” (risk), “significant” (statistically meaningful), “conservative” (cautious estimate).

Euphemisms and hedges: “Negative growth” (decline), “suboptimal outcomes” (failure), “restructuring” (layoffs). Authors use these to soften bad news.

Return to the Understand Difficult Text pillar for more comprehension tools, or explore the full prompt ecosystem at the AI for Reading hub.

Frequently Asked Questions

Jargon is any specialized vocabulary that insiders use but outsiders don’t understand β€” technical terms, acronyms, field-specific phrases, and expressions that assume prior knowledge. It’s not just big words; it’s words used in specialized ways.
Dictionary definitions give you general meanings. This prompt gives you the contextual meaning β€” what the term means in THIS passage, what work it’s doing rhetorically, and how the meaning would change if stated differently.
Use the Jargon Translator when your confusion is specifically about terminology β€” you understand the grammar and structure but not the words. Use the full workflow (C009) when the whole passage is difficult, not just the vocabulary.
Yes, but for best results, focus on one phrase or term at a time. If a passage has many unfamiliar terms, consider the Glossary from Article prompt (C014) which extracts and defines all key terms systematically.
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Inference Question Trainer: Master the Hardest RC Type

C070 πŸŽ“ RC Exam Prep 1 Prompt

Inference Question Trainer: Master the Hardest RC Type

Inference questions trip up even strong readers. Practice three distinct types β€” reading between the lines, author’s implied view, and logic extension β€” with AI-generated questions and trap analysis.

6 min read Inference Guide 4 of 6
PR049 The Inference Question Trainer
Use to practice the hardest RC question type
Here’s a passage: “[paste passage]” Generate 3 inference questions in the style of [CAT/GMAT/GRE]: – One that requires reading between the lines – One that requires understanding author’s implied view – One that requires extending the logic For each, explain what makes the correct answer correct and what common traps might appear.
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Why Inference Questions Are the Hardest RC Type

Every competitive exam β€” CAT, GMAT, GRE β€” has a question type that separates scorers from top scorers. That type is inference questions. While detail questions point you to specific lines and main idea questions test your overall grasp, inference questions demand something harder: drawing a conclusion the passage supports but never directly states.

The difficulty comes from two sources. First, you need to synthesize information across multiple sentences or paragraphs. Second, the answer must be logically supported by the text without being explicitly mentioned β€” a narrow sweet spot between what’s stated and what’s assumed.

Most test-takers fail inference questions because they either pick answers that go too far beyond the text (overinference) or pick answers that merely restate what’s already explicit (underinference). The sweet spot is one logical step beyond the text β€” no more, no less.

The 3 Inference Types You’ll Face

Type 1: Reading Between the Lines β€” These questions ask what’s implied by the passage. The author doesn’t say it directly, but the evidence points clearly in one direction. Signal phrases: “The passage implies that…”, “It can be inferred…”, “The author suggests…”

Type 2: Author’s Implied View β€” These ask what the author believes based on how they present information. Watch for qualifiers (“merely,” “surprisingly”), contrast signals, and the relative space given to competing arguments.

Type 3: Extending the Logic β€” These ask you to apply the passage’s reasoning to a new scenario. If the author argues X leads to Y in context A, what would happen in context B? This requires extracting the rule from the example, then applying it elsewhere.

⚑ Exam Strategy

Before selecting an inference answer, ask: “Can I point to specific lines that support this?” If you can’t, you’ve overinferred. If the lines say exactly what the answer says, you’ve underinferred. The right answer is always one step β€” and only one step β€” beyond what’s stated.

Continue to Timed Practice Simulator (C071) for speed training.

Frequently Asked Questions

Inference questions require you to go beyond what’s explicitly stated. Unlike detail questions where the answer is in the passage, inference questions ask you to draw a logical conclusion that the passage supports but never directly says. This requires holding multiple pieces of information in mind and reasoning from them.
The core skill is the same, but the style varies. GMAT inference questions focus on business and logical reasoning. GRE tests nuanced literary or academic inferences. CAT questions can be more varied. The PR049 prompt lets you specify which exam style you want.
An inference is a conclusion you draw FROM the passage β€” it follows from what’s stated. An assumption is something the author takes for granted β€” it’s not stated but must be true for the argument to work. Inference questions ask what follows; assumption questions ask what’s presupposed.
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Methods Decoder: Explain Methods in Plain English

C062 πŸ”¬ Research Papers 1 Prompt

Methods Decoder: Explain Methods in Plain English

Turn opaque procedures, variables, and statistical tests into clear, plain-language explanations you can actually understand β€” using one copy-paste AI prompt.

6 min read 1 Prompt Guide 2 of 6
PR040 Academic Paper Navigator
Use before reading a research paper
I’m reading an academic paper. Here’s the abstract: “[paste abstract]” Before I read the full paper, help me: – Identify the research question and why it matters – Understand what to pay attention to in each section (intro, methods, results, discussion) – Flag jargon I should look up first – Tell me what questions to keep in mind while reading
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Why Methods Sections Are the Hardest Part of Any Paper

You can usually follow a research paper’s introduction. The results make sense in table form. Even the discussion reads like an opinion piece. But the methods section? That’s where most readers hit a wall β€” and where most people silently give up on understanding what the study actually did.

The problem isn’t intelligence. It’s vocabulary. Methods sections are written for peer reviewers who already know what “double-blind placebo-controlled crossover design” means. If you’re outside that circle, you’re expected to decode the jargon yourself. Most people don’t.

That’s exactly where AI can help. When you use a prompt to explain methods section content in plain English, you’re removing the vocabulary barrier so your thinking can actually begin.

How to Use PR040 to Decode Any Methods Section

The Academic Paper Navigator prompt (PR040) was designed for pre-reading orientation, but it’s equally powerful as a methods decoder. Here’s how to adapt it:

1. Copy the full methods section. Include subheadings, statistical test names, and references to tables. More context gives better explanations.

2. Paste it into AI with a targeted instruction. Add: “Focus specifically on the methods section. Explain every procedure, variable, and statistical test in plain English.”

3. Ask for a step-by-step walkthrough. Request that AI explain the study design as a sequence: what happened first, what was measured, what was compared.

4. Identify variables explicitly. Follow up with: “List every independent variable, dependent variable, and control variable mentioned.”

⚑ Pro Tip

After AI explains the methods, ask: “Explain the statistical tests used as if I’m an intelligent adult who has never taken a statistics course. For each test, tell me what question it answers.”

The 5 Things to Check in Any Methods Explanation

Once AI has decoded the methods, verify these five elements:

Sample: Who or what was studied? How were they selected? Is the sample representative?

Procedure: What did the researchers actually do? In what order?

Variables: What was manipulated (independent)? What was measured (dependent)? What was held constant (controls)?

Analysis: What statistical tests were used? Why those tests?

Threats: What could have gone wrong? What confounds exist?

πŸ’‘ Example: Before and After

Before: “A 2Γ—3 mixed-design ANOVA with Greenhouse-Geisser correction revealed a significant interaction (F(1.8, 142.3) = 4.21, p = .02, Ξ·Β²p = .05).”

After (AI decoded): “The researchers compared two groups across three time points. The statistical test (ANOVA) found that the groups changed differently over time β€” one group improved more than the other. The effect was real (p = .02) but small (5% of the variance explained).”

⚠ Important Limitation

AI may oversimplify nuances or miss field-specific conventions. Treat its explanation as a starting point and verify critical details against the paper itself.

Build Your Research Reading Stack

The Methods Decoder works best with other research paper prompts:

Paper Map Prompt β€” Map the paper before diving into methods

Limitations & Assumptions β€” Find weaknesses the methods might create

Reproducibility Checklist β€” Assess if methods are detailed enough to replicate

Frequently Asked Questions

AI is surprisingly good at translating technical procedures into plain language. It can explain statistical tests, experimental designs, and measurement approaches clearly. However, AI may oversimplify nuances, so treat its explanation as a starting point.
That’s exactly when this prompt is most useful. Ask AI to explain each statistical test in one sentence, what it’s designed to detect, and what a significant result means in context.
Ideally, skim the methods first so you know what confused you. Then paste the text into AI and ask for a plain English breakdown. This way you can compare your initial understanding to AI’s explanation.
Yes β€” the prompt works across fields including medicine, psychology, economics, computer science, and natural sciences. AI adapts its explanations to the specific methodology used.
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Meeting Prep Prompt: 3 Links to Talking Points

C048 πŸ’Ό Reading for Work 1 Prompt

Meeting Prep Prompt: 3 Links to Talking Points

Meeting in 30 minutes? Paste your prep reading and get structured talking points, likely stakeholder questions, and discussion starters β€” fast.

5 min read 1 Prompt Included Guide 2 of 6
PR043 Business/Report Reader
Use for meeting prep & briefing notes
I’m reading a business report or case study: “[paste excerpt]” Help me extract value: – What’s the key takeaway for decision-making? – What data matters vs. what’s noise? – What assumptions underlie the analysis? – What questions should I ask before acting on this?
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The Input Format That Gets the Best Meeting Prep

You’ve got a meeting in 30 minutes. Three articles are sitting in your browser tabs, unread. The meeting talking points prompt can rescue you β€” but only if you feed it properly.

The key is structured input. Don’t just dump raw text. Instead, frame your paste with context that tells AI exactly what you need. Here’s the format that works:

State the meeting purpose. “I’m presenting quarterly results to the leadership team” gives AI the lens to filter what matters.

Identify your audience. “The CFO cares about cost, the COO cares about timelines” β€” AI will weight the talking points accordingly.

Paste your reading materials. Label each document: “Document 1: Market Analysis” and “Document 2: Competitor Report” so AI can attribute insights correctly.

Specify your output. “Give me 5 talking points, 3 likely questions, and 2 discussion starters” tells AI exactly what format you need.

This structure transforms the prompt from a generic summarizer into a true prep for meeting assistant. You’ll walk in knowing exactly what to say β€” and anticipating what others will ask.

Running the Prompt: From Reading to Talking Points

Once your input is ready, paste it into ChatGPT, Claude, or any AI tool along with the PR043 prompt above. The prompt’s four questions do the heavy lifting:

“What’s the key takeaway for decision-making?” cuts through fluff to find the one thing your audience must know.

“What data matters vs. what’s noise?” identifies which numbers are worth citing and which are decorative.

“What assumptions underlie the analysis?” surfaces risks you should be ready to address.

“What questions should I ask before acting on this?” turns into your own Q&A preparation β€” flip these into questions others might ask you.

The result: a set of briefing notes you can glance at before walking into the room. No more flipping through pages mid-meeting or fumbling for that one stat you half-remember.

⚑ Pro Tip

After getting initial talking points, run this follow-up: “Now imagine you’re the skeptical CFO in this meeting. What three questions would you ask to poke holes in these talking points?” This is the fastest way to stress-test your prep.

Preparing for Stakeholder Questions

The best meeting prep doesn’t just cover what you’ll say β€” it anticipates what others will ask. AI can help here too, but you need to guide it.

After generating your talking points, add this follow-up prompt: “Based on this content and a [describe your audience] audience, what are the 5 most likely questions they’ll ask? For each, suggest a 2-sentence response.”

This generates a quick reference sheet for the Q&A portion. Keep it open on your laptop or print it. When someone asks “What about the competitor response?” you won’t be caught flat-footed.

πŸ’‘ Real-World Example

A product manager needed to brief leadership on three analyst reports about market trends. She pasted all three with the context “presenting to CEO and board, focus on strategic implications.” AI generated: 4 talking points, 2 data visualizations to create, 5 likely questions, and a one-liner opening hook. Total prep time: 12 minutes.

When You Only Have 10 Minutes

Sometimes there’s no time for the full workflow. Here’s the stripped-down version:

Paste your reading. Skip detailed labeling β€” just dump the text.

Run the core prompt once. Get the four-part extraction.

Ask for compression. “Summarize this into 3 bullet points I must know.”

Skip the Q&A prep if time is tight. Knowing the content is more valuable than predicting questions. You can improvise answers; you can’t improvise knowledge.

⚠ Important Limitation

AI doesn’t know your company’s internal politics, your boss’s pet peeves, or last week’s drama in the leadership meeting. It gives you content prep β€” you still need to apply judgment about how to present based on what you know about the people in the room.

Building Your Professional Reading Workflow

This meeting talking points prompt is one piece of the Reading for Work toolkit. For a complete professional reading system, pair it with:

Action Memo Prompt β€” when you need a full memo, not just talking points

Stakeholder Update Prompt β€” for written updates after the meeting

Executive Summary Prompt β€” for distilling long reports into one-pagers

Frequently Asked Questions

Most AI tools handle 3,000-8,000 words comfortably. For longer materials, paste the most relevant sections or ask AI to focus on specific pages. Quality of input matters more than quantity β€” include the parts that are most likely to come up in discussion.
Yes. Paste all documents together with clear labels like “Document 1: [title]” and “Document 2: [title]”. AI will synthesize across sources and identify where they agree, disagree, or complement each other.
Add context about your audience when you run the prompt. For example: “I’m presenting to the CFO who cares about ROI” or “This is for a technical team that wants implementation details.” AI will adjust the emphasis accordingly.
Focus on the core prompt without follow-ups. Paste your reading, run the Business/Report Reader prompt once, and ask for “3 bullet points I must know.” Skip the Q&A prep if time is tight β€” knowing the key takeaways is more valuable than predicting questions.
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Math & Notation Translator: Symbols to Words

C066 πŸ”¬ Research Papers 1 Prompt

Math & Notation Translator: Symbols to Words

Don’t let Greek letters and subscripts lock you out of a paper. This prompt turns opaque equations into plain English β€” with symbol definitions, explanations, and worked examples.

6 min read Equations Guide 6 of 6
PR040 Academic Paper Navigator
Use before reading a research paper
I’m reading an academic paper. Here’s the abstract: “[paste abstract]” Before I read the full paper, help me: – Identify the research question and why it matters – Understand what to pay attention to in each section (intro, methods, results, discussion) – Flag jargon I should look up first – Tell me what questions to keep in mind while reading
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What to Include When Asking AI to Explain Equations

You’re reading a paper that looks promising β€” until you hit a wall of subscripts, summation signs, and Greek letters. The abstract made sense. The introduction was clear. Then the methods section arrived and suddenly you’re staring at notation that might as well be hieroglyphs.

This is where most non-specialist readers abandon a paper. But you don’t have to. The key to using AI to explain equations in words is giving it enough context to translate accurately.

Always include the abstract. It anchors the AI in the paper’s domain and research question. A sigma (Οƒ) means something different in statistics, physics, and computer science. The abstract tells AI which interpretation to use.

Copy equations exactly. Subscripts, superscripts, and special characters all matter. If you can’t copy-paste from the PDF, describe the layout: “x subscript i, superscript 2” or use standard text conventions like x_i^2.

Specify your level. Add a line like “Explain this as if I have an undergraduate understanding of statistics.” This calibrates the explanation to your actual knowledge.

πŸ“Œ Key Insight

The Paper Map Prompt is your ideal first step β€” it gives you the overall structure before you dive into equations. Once you know what each section does, you can focus your notation translation efforts on the equations that matter most.

For the complete research paper reading toolkit, explore the Read Research Papers pillar or return to the AI for Reading hub.

Frequently Asked Questions

Many PDFs don’t allow clean copy-paste of equations. Options: describe it in words (“x subscript i squared”), use LaTeX-style notation (x_i^2), or take a screenshot and use a multimodal AI tool that can read images.
Equations are ambiguous without context. The same symbol can mean different things in different fields. The abstract tells AI the domain, which enables accurate interpretation of notation.
Ask for a numerical example with simple numbers. If the equation calculates a probability, ask AI to show the calculation with made-up but realistic values. Working through actual numbers often clarifies what abstract notation means.
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Make Flashcards from What You Read: Active Recall Prompts

C022 πŸ“ Notes & Memory 1 Prompt

Make Flashcards from What You Read: Active Recall Prompts

Generate effective flashcards at multiple cognitive levels: test surface facts, deep comprehension, and real-world application.

5 min read 4 Cognitive Levels Guide 2 of 5
PR032 The Retrieval Practice Generator
To test yourself on what you read
I just read this: “[paste passage]” Create a retrieval practice set: – 3 questions testing surface understanding – 2 questions testing deeper comprehension – 1 question requiring me to apply this idea to a new situation – 1 question connecting this to other knowledge Don’t give answers yet β€” I’ll try first, then ask.
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What Makes Good Flashcards

Most flashcards fail because they test recognition instead of recall. You see the question, something feels familiar, you flip the card and say “yeah, I knew that.” But you didn’t β€” you recognized it. Recognizing is not remembering.

Good flashcards force active recall: you must produce the answer from memory, not just recognize it when you see it. This retrieval effort is what actually builds lasting memory. It feels harder because it is harder β€” and that’s the point.

The Retrieval Practice Generator (PR032) creates questions at four cognitive levels, not just one. Surface questions test basic facts. Comprehension questions test whether you understand what it means. Application questions test whether you can use the concept in a new situation. Connection questions test whether you can link it to other knowledge.

This multi-level approach prevents a common trap: you can answer surface questions perfectly while having no real understanding. By mixing question types, you discover gaps you didn’t know you had.

The Flashcard Prompt

PR032 asks AI to generate 7 questions at four levels β€” crucially, without providing answers. This matters. The learning happens when you attempt to answer before checking.

Here’s the workflow: paste a passage, get questions, try to answer each one out loud or in writing, then ask for answers and compare. Questions you got wrong or struggled with become your actual flashcards. Questions you answered easily? You don’t need flashcards for those β€” you already know them.

This approach is more efficient than flashcarding everything. Most AI flashcard tools generate cards for every fact in a passage. You end up with 50 cards, 40 of which test things you already know. The retrieval practice approach identifies what you actually need to learn.

πŸ’‘ Pro Tip

After attempting answers, tell the AI which questions you struggled with. Ask: “I couldn’t answer questions 3 and 5. Create 2-3 more questions on those specific concepts at varying difficulty levels.” This targets your weak spots directly.

Question Types Explained

Surface questions test basic facts and definitions. “What is the term for…?” or “According to the passage, what percentage…?” These are the easiest to answer and the least valuable for deep learning β€” but they verify you absorbed the raw information.

Comprehension questions test whether you understand the meaning. “Why does this phenomenon occur?” or “What is the relationship between X and Y?” These require you to explain, not just recall. If you can’t answer in your own words, you don’t really understand.

Application questions test transfer to new situations. “How would this principle apply to [different context]?” or “If the conditions changed in this way, what would happen?” These are hard β€” and that’s why they’re valuable. They reveal whether you can use the concept, not just describe it.

Connection questions test integration with existing knowledge. “How does this relate to [something you already know]?” or “What does this remind you of from [other field]?” These build your knowledge network, linking new ideas to established ones.

For a deeper review system using these question types over time, see Spaced Recall from Articles (C025).

πŸ“Œ The Struggle Test

If you can answer a flashcard question instantly without thinking, the card is too easy and wasting your time. Good flashcards should require a moment of effort β€” that effort is the learning. Delete easy cards, keep challenging ones.

Export Tips: Getting Cards into Your System

Once you’ve identified questions worth keeping, you need to get them into a spaced repetition system. Here’s how to format for the major apps:

For Anki: Ask AI to format as “Question [tab] Answer” with each card on a new line. Import using File β†’ Import, set field separator to Tab. Or use the semicolon format: “Question;Answer” and set separator to semicolon.

For Quizlet: Ask AI to format as “Question – Answer” with each card on a new line. Use Quizlet’s import feature, set the term-definition separator to ” – ” (space-dash-space).

For Notion/Obsidian: Ask AI to format cards as toggle blocks (Notion) or callouts (Obsidian) with question visible and answer hidden. This works for quick review within your existing note system.

For cards that need more context than simple Q&A, use Cornell Notes (C021) instead β€” the cue column serves as built-in self-testing without needing a separate app.

Explore more memory systems in the Notes & Memory pillar or start with the complete AI for Reading hub.

Frequently Asked Questions

Recognition is “do I know this when I see it?” Recall is “can I produce this from memory?” Recognition is easy β€” recall is hard. And the hard effort of recall is what builds lasting memory. That’s why good flashcards make you produce the answer, not just confirm it looks familiar.
The retrieval attempt is the learning. If you see the answer before trying, you’ve lost the learning opportunity. By attempting first, you strengthen memory traces and discover which concepts you actually need to study. Questions you can already answer don’t need flashcards.
As few as possible while capturing what matters. The goal isn’t to flashcard every fact β€” it’s to flashcard concepts you couldn’t recall when tested. After trying the prompt’s questions, you might find only 2-3 need actual flashcards. Quality beats quantity.
Anki is the most powerful but has a learning curve. Quizlet is simpler and works well for most purposes. RemNote and Obsidian plugins work if you already use those tools. The best app is the one you’ll actually use consistently.
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Make a Glossary from Any Article: Definitions, Examples & Misconceptions

C014 🧠 Understand Difficult Text 2 Prompts

Make a Glossary from Any Article: Definitions, Examples & Misconceptions

Auto-generate a glossary from any text: key terms, contextual definitions, examples, and common misconceptions to avoid.

5 min read 2 Prompts Guide 6 of 6
PR019 The “Words I Should Know” Identifier
Step 1: Find key terms to define
Here’s a passage I’m reading: “[paste passage]” Identify vocabulary I should pay attention to: – Which words are central to understanding this passage? – Which words might appear in similar texts on this topic? – Which words have specialized meanings in this context vs. everyday use? – Rank them by importance for comprehension.
PR015 The Contextual Word Explorer
Step 2: Define each term in context
In this sentence: “[paste sentence]” The word “[word]” is used. Don’t just define it. Help me understand: – What does it mean in THIS specific context? – What connotations or tone does it carry here? – What other words could the author have used, and why this one? – How does this word choice affect meaning or tone?
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Choose the Right Terms to Define

Not every unfamiliar word deserves glossary treatment. Some words are peripheral β€” you can understand the passage without them. Others are central β€” miss them and the whole argument collapses. PR019 helps you sort the difference.

The “Words I Should Know” Identifier (PR019) ranks vocabulary by importance for comprehension. It identifies which words are central to understanding, which appear in similar texts on the topic, and which have specialized meanings in this context versus everyday use.

This matters because time is limited. If an article has 20 unfamiliar terms, learning all of them equally wastes effort. Focus on the 5-7 that matter most. Those are the ones that unlock understanding β€” and the ones you’ll encounter again.

To create a glossary from an article efficiently, start with PR019 to identify your targets before diving into definitions.

Define Each Term in Context

Dictionary definitions fail for the same reason translations fail: they give general meanings, not specific ones. The word “culture” in a microbiology paper means something different than in an anthropology paper. Context determines meaning.

The Contextual Word Explorer (PR015) goes beyond definitions. For each term, it reveals what the word means in THIS specific context, what connotations or tone it carries, what alternative words the author could have used, and how this word choice affects meaning.

This depth matters for comprehension. When you understand not just what a word means but why the author chose it, you understand the passage at a deeper level. You see the author’s choices, not just the content.

πŸ’‘ Pro Tip

For each term, add a “misconception to avoid” note. Example: “Correlation” β€” misconception: correlation implies causation. These notes prevent common errors when you apply the term later.

Add Examples That Cement Understanding

Definitions tell you what a word means. Examples show you what it looks like. After getting contextual definitions, follow up with: “Give me a concrete example of [term] from a different domain.”

Cross-domain examples are especially powerful. If you’re learning about “arbitrage” in finance, an example from everyday life (buying cheap concert tickets and reselling them) makes the concept portable. You understand the principle, not just the application.

For deep vocabulary work, see the Vocabulary-in-Context Prompt Pack (C006) which includes collocations, tone analysis, and usage practice beyond what the glossary workflow covers.

Flag Common Misconceptions

Many technical terms carry baggage β€” common misunderstandings that persist even after you’ve read the definition. “Theory” in science doesn’t mean “guess.” “Significant” in statistics doesn’t mean “important.” “Organic” in chemistry has nothing to do with farming.

For each glossary term, ask: “What do people commonly get wrong about this term?” Then note the misconception explicitly. This preemptive correction saves you from errors that feel correct but aren’t.

The Jargon Translator (C010) handles single-term misconceptions well. For systematic glossary work, add the misconception step after defining each term.

πŸ“Œ The Glossary Workflow

1. Use PR019 to identify which terms matter most. 2. Use PR015 to define each term in context (not dictionary style). 3. Add a concrete example from a different domain. 4. Note the common misconception to avoid. 5. Test yourself by defining terms from memory after reading.

Quick Review: Test Your Glossary

A glossary you never review is a glossary that doesn’t help. After building your glossary, close the article and try to define each term from memory. Can you explain what it means in context? Can you give an example? Can you name the misconception to avoid?

If you can’t, you’ve collected definitions β€” but you haven’t learned them. Go back to that section of the article. Re-read it with the definition fresh in mind. The glossary should support comprehension, not replace it.

For long-term retention, revisit the glossary a day later using spaced repetition. The Understand Difficult Text pillar has more tools for building lasting comprehension. Return to the AI for Reading hub for the complete prompt ecosystem.

Frequently Asked Questions

Dictionaries give general definitions. This workflow gives you contextual meaning β€” what a word means in THIS passage, why the author chose it, and what connotations it carries. Words often have specialized meanings in specific fields that dictionaries miss.
No β€” only for dense technical content, unfamiliar topics, or texts you’ll need to reference later. For casual reading, use the Jargon Translator (C010) on specific terms instead of building a full glossary.
PR019 ranks terms by importance for comprehension. Focus on the top 5-10 terms that are central to understanding. More than 15 terms suggests you might need background knowledge first β€” try the Prerequisites Prompt (C011).
After reading, close the article and try to define each term from memory. If you can’t, re-read that section. For long-term retention, revisit the glossary a day later and test yourself again using spaced repetition.
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Literary Passage Deep Dive: Close Reading with AI

C037 πŸ“‹ Prompts Library Reading Skills

Literary Passage Deep Dive

Close reading for literature: surface meaning, literary devices, theme development, and reader effect analysis.

5 min read 1 Prompt Genre Guide
PR044 Literary Passage Deep Dive
For fiction, literary nonfiction, poetry
Here’s a passage from literature: “[paste passage]” Guide my close reading: – What’s happening at the surface level? – What literary devices are at work? – What themes or ideas are being developed? – What’s the effect on the reader, and how is it achieved? – What might I miss on a casual read?
πŸ“š
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What Close Reading Reveals

Surface reading tells you what happens. Close reading tells you how and why. When you close read, every word becomes a choice the author made β€” and you can ask why that choice and not another. The literary analysis prompt PR044 guides this process systematically.

Start with surface meaning: what’s literally happening? Character actions, setting details, dialogue. Don’t interpret yet β€” just make sure you understand. Many reading errors come from rushing to interpretation before establishing the basic facts of the passage.

Then move to literary devices. Not to catalog them like trophies, but to ask: what work is this device doing? That metaphor isn’t decoration β€” it’s connecting two ideas. That repetition isn’t accident β€” it’s creating emphasis. The prompt helps you identify devices, but your job is to connect them to meaning.

Literary Devices: The Author’s Toolkit

Literary devices are techniques writers use to create meaning beyond the literal. The close reading prompt helps you identify which ones are active in your passage. Some common devices to watch for:

Imagery β€” sensory details that create pictures in the mind. Not just visual; listen for sounds, textures, smells, tastes. Metaphor and simile β€” comparisons that illuminate by connecting unlike things. Symbolism β€” objects or images that carry meaning beyond themselves. Irony β€” gaps between appearance and reality, between what’s said and what’s meant. Foreshadowing β€” hints planted early that bloom later.

Beyond these, pay attention to diction β€” why “trudged” instead of “walked”? Why “crimson” instead of “red”? Word choice reveals tone and attitude. Sentence structure matters too: short sentences create urgency; long, winding sentences can mimic confusion or drowning. For more on detecting author attitude, see Read Between the Lines.

πŸ’‘ The “Why This?” Question

The core move of close reading is simple: ask “Why this?” Why this word and not another? Why this image here? Why does the sentence break at this point? Why is this character named that? Every “why” opens a door. AI can generate possibilities; you decide which matter most.

Theme Analysis: What’s Really Being Said

Themes are the ideas a work explores β€” not the plot, but what the plot is about. A story might follow a soldier returning from war (plot), while exploring themes of trauma, homecoming, and the impossibility of returning to who you were. Themes are usually abstract: love, death, identity, power, freedom, memory, belonging.

In close reading, you connect devices to themes. That recurring water imagery? It connects to emotional overwhelm. That metaphor comparing the house to a prison? It advances the theme of entrapment. Patterns matter: not just one metaphor, but which metaphors cluster together, how they develop, where they peak and resolve.

PR044 asks about themes being “developed” because themes aren’t usually stated β€” they emerge through accumulation. By the end of a work, the theme should feel inevitable, built from a hundred deliberate choices. For strategies to maintain this kind of engagement through longer texts, see Active Reading Prompts.

πŸ“Œ Passage Selection

You can’t close read an entire novel at this depth. Select key passages: openings (which establish tone and themes), climaxes (where tensions peak), pivotal scenes (where characters change), and endings (which resolve or deliberately don’t). These are where authors concentrate their craft. PR044 works best on 500-1000 word passages.

Reader Effect: How and Why It Works

Literature isn’t just about meaning β€” it’s about experience. Close reading examines what the passage makes you feel and how that effect is achieved. Tension, sympathy, unease, hope, dread, recognition β€” these aren’t accidents. They’re engineered through specific techniques.

The prompt asks: “What’s the effect on the reader, and how is it achieved?” This separates what you feel from why you feel it. You might feel dread, but why? The clipped sentences? The isolated protagonist? The detail that doesn’t quite fit? Once you understand the mechanism, you understand the craft β€” and can appreciate it more fully, or recognize when it’s being used to manipulate you.

The final question β€” “What might I miss on a casual read?” β€” surfaces the buried elements: structural echoes between beginning and end, intertextual references to other works, unreliable narration you didn’t catch, symbolic patterns that only emerge on reflection. This is where AI excels: pattern recognition across the passage, connections to literary tradition, context you might lack.

For the complete collection of genre-specific reading approaches, explore the AI Reading Prompts Library. For the broader framework connecting all reading skills, see AI for Reading.

Frequently Asked Questions

Surface reading focuses on what happens: plot, events, who said what. Close reading asks why and how: Why did the author choose that word? How does that image connect to the theme? What effect does this structure create? Close reading treats every choice as deliberate and meaningful. It’s slower but reveals layers that casual reading misses.
AI excels at pattern recognition and catalog tasks: listing every metaphor, tracking recurring images, noting structural parallels. It’s also good at providing context (historical, biographical, genre conventions) and generating interpretive possibilities. It’s less good at deciding which interpretation matters most β€” that’s where your judgment comes in. Use AI to surface options, then select what resonates.
Close reading works best on short, dense passages: a paragraph, a scene, a poem, a page. Longer passages require too much compression β€” you’ll get surface-level analysis spread thin. For novels or long works, select key passages (openings, climaxes, pivotal scenes, endings) and close read those. PR044 handles about 500-1000 words well.
Common devices include: imagery (sensory details), metaphor and simile (comparisons), symbolism (objects/images carrying meaning), irony (gap between appearance and reality), foreshadowing (hints at future events), diction (word choice for effect), syntax (sentence structure), point of view (who narrates and what they know), and tone (attitude conveyed). PR044 will flag the specific devices present in your passage.
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Close reading skills transfer to every complex text you’ll ever encounter. Practice on literary passages and watch your ability to notice deepen across all your reading.

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Pick a passage from whatever you’re reading. Run PR044. Notice what layers emerge beneath the surface β€” the devices, the themes, the craft. That’s where literature lives.

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