Public Prompt Library

#TASK Tear down a competitor's product feature-by-feature and identify where they are strong, where they are weak, and where there is a gap we can win. #REQUEST Produce a structured competitive analysis, not a feature checklist. I want to know what to build, not just what they have. #ACTION Structure the output as: 1. **Competitor snapshot** — 2-3 sentences on who they are, their positioning, and their apparent target customer. 2. **Feature matrix** — list their core features. For each: what it does, how well it works (Strong/Adequate/Weak), and one specific observation (not 'good UX' but 'onboarding completed in 4 clicks with no email verification'). 3. **What they do better than us** — be honest. Name the specific advantage. 4. **Where they are vulnerable** — the gaps, rough edges, or underserved segments. 5. **Opportunities** — 3 concrete moves we could make that they are not covering. Each tied to a specific weakness above. #CONTEXT Our product: {{one-line description of what we build and who it's for}} Competitor: {{competitor name and URL}} What I know already: {{any prior research, customer feedback, or assumptions — or 'nothing yet'}} #EXAMPLE Good observation: 'Pricing page shows only annual plans on mobile — monthly is hidden behind a toggle. Likely losing price-sensitive mobile traffic.' Bad observation: 'Their pricing seems competitive.' Competitor details to analyze: {{paste competitor's feature list, pricing page content, or any notes you've gathered}}

# TASK Synthesize the provided sources into a structured literature review that a researcher or decision-maker can use to understand the current state of a topic. Topic: {{TOPIC}} Sources to synthesize: {{SOURCES}} # REQUEST Do not summarize each source one by one. Instead, identify the key themes, debates, and consensus points that emerge across sources. A good literature review tells a story about what the field collectively knows and where the gaps are. # ACTION ## Part 1: Thematic Synthesis Organize findings into 3-5 themes. For each theme: - Name the theme (specific, not generic — "Adoption barriers in enterprise vs. SMB" not "Challenges") - Which sources support this theme? (cite by [S1], [S2] etc.) - Where do sources agree? - Where do they disagree or contradict? (This is the most valuable part — surface tensions explicitly.) - What is the strength of evidence? (well-established, emerging, single-study, anecdotal) ## Part 2: Gap Analysis - What questions are sources NOT addressing that seem important? - Where is the evidence weakest? - What methodological limitations appear across the body of work? ## Part 3: Consensus Map One paragraph summarizing what the field collectively agrees on (if anything). Be honest — if there is no consensus, say so and explain what the main camps are. ## Part 4: Source Quality Notes For each source, one line on credibility: peer-reviewed? industry report? blog post? What's the potential bias? # CONTEXT - Number each source [S1], [S2], etc. as provided in the input - If sources conflict, do not resolve it for the reader — present both sides with the evidence each offers - Flag any claim that relies on a single source # EXAMPLE Input style: "[S1] Smith et al. (2024) found that 73% of enterprise teams adopted... [S2] However, a Gartner report (2025) showed..." Output theme example: **Theme: Adoption rates vary sharply by company size** - Enterprise adoption rates are consistently reported at 60-80% [S1, S3], while SMB rates lag at 20-30% [S2]. - Contradiction: [S1] cites cost as the primary barrier, while [S4] argues integration complexity matters more. - Evidence strength: Moderate. Multiple sources but reliance on survey data.

#ROLE You are an interview coach who has prepared executives, job candidates, and podcast guests for high-stakes conversations. #INSTRUCTIONS Build a complete interview preparation brief for the user. The brief must cover what they will likely be asked, what they should say, and what they should avoid saying. #STEPS ## Step 1: Anticipated Questions Generate 10-15 questions the interviewer is likely to ask, organized into three tiers: - **Tier 1 (Certain)**: Warm-up and background questions. Nearly guaranteed. - **Tier 2 (Likely)**: Role-specific, topic-specific, or behavioral questions. - **Tier 3 (Curveballs)**: Challenging, unexpected, or pressure questions designed to test composure. ## Step 2: Talking Points For each Tier 1 and Tier 2 question, provide: - A recommended answer structure (not a script — a framework like 'Problem → Action → Result' or 'Context → Choice → Outcome') - 2-3 key points to land - A specific example or story to use (from the user's background) - Target length (how long the answer should run) ## Step 3: Red-Flag Responses List 5 things to avoid saying: - Phrases that sound evasive or rehearsed - Topics that could derail the conversation - Over-sharing or under-sharing patterns - How to pivot if you start going down a wrong path ## Step 4: Questions to Ask Provide 5 questions the user should ask the interviewer, ranked by how much signal they provide about whether this is the right fit. ## Step 5: Logistics Checklist - What to prepare 24 hours before (research, materials, tech check) - First 60 seconds strategy (how to open strong) - Closing strategy (how to end on a memorable note) #END GOAL The user walks into the interview knowing what to expect, what to say, and how to handle surprises. #NARROWING - Keep answer frameworks flexible, not memorized scripts. The goal is preparedness, not robotic delivery. - Tailor everything to the specific interview type and context below. #CONTEXT - Interview type: {{interview_type}} (job interview, media appearance, podcast, panel, investor pitch) - Role or topic: {{role_or_topic}} - Company or show: {{company_or_show}} - User's background: {{user_background}} - Format: {{format}} (in-person, video, phone) and duration: {{duration}}

#SITUATION A stakeholder needs to understand what a dataset is telling them, but they do not have time to read raw numbers or build charts. They need the story the data tells, written in plain language. #PURPOSE Transform the provided data into a structured findings report that a non-technical decision-maker can act on in under five minutes. #EXPECTED OUTPUT Produce a report with these sections: ## Executive Summary (3-4 sentences) The single most important finding and why it matters. No jargon. ## Key Findings (5-7 bullet points) Each finding states the observation, the supporting number, and the implication. Example format: 'Revenue from product X dropped 23% month-over-month — investigate whether the price increase on June 1 is the cause.' ## Anomalies and Outliers List anything unusual: unexpected spikes, missing data, values that break a pattern. Flag whether each is worth investigating or likely a data quality issue. ## Trends Identify direction and velocity. Is the metric going up, down, or flat? How fast? Compare to the prior period if data allows. ## Recommendations (3-5 items) Specific, concrete next steps tied to the findings. Each recommendation references the finding it addresses. #CONTEXT - Data type: {{data_type}} (CSV / JSON / spreadsheet / pasted table) - Business context: {{business_context}} - Time period covered: {{time_period}} - Prior period for comparison: {{prior_period}} #STYLE - Plain English. Write for someone who skipped the meeting but needs to make the call. - Every claim must reference a number from the data. No unsupported assertions. - If the data is too sparse to support a finding, say so explicitly rather than guessing. #DATA {{raw_data}}

#ROLE: UX researcher who conducts discovery interviews. #TASK: Generate a user interview question guide for researching {{topic}}. #INTERVIEW STRUCTURE (45 minutes): ## 1. WARM-UP (5 min) - Background questions to build rapport - General context about their relationship to {{topic}} ## 2. CURRENT BEHAVIOR (10 min) - Walk me through how you currently {{activity}}... - What tools do you use? - What does a typical day look like regarding {{topic}}? ## 3. PAIN POINTS (15 min) - What's the hardest part about {{activity}}? - Can you tell me about a time when {{scenario}} went wrong? - What do you do AFTER {{activity}}? ## 4. WORKAROUNDS (10 min) - Have you tried to solve {{problem}} yourself? - What would your ideal solution look like? ## 5. WRAP-UP (5 min) - Is there anything I should have asked but didn't? - Who else should I talk to? #GUIDELINES: - Use open-ended questions (no yes/no) - Ask about PAST behavior, not future intentions - Follow-up probes for each main question

# ROLE You are a fact-checking auditor who specializes in finding hallucinations, unsupported claims, and grounding failures in LLM outputs. You treat every sentence as a claim that must be traced to a source. You do not rubber-stamp. You do not speculate. # CONTEXT LLMs hallucinate. They invent citations, fabricate statistics, misattribute quotes, and state assumptions as fact. In 2026 this problem compounds: agents chain multiple LLM calls, RAG systems retrieve imperfect context, and a single ungrounded claim can propagate through an entire workflow. A response that sounds confident is not a response that is correct. Grounding means every factual claim in the output can be traced to the provided source material. If the source does not support the claim, it fails — regardless of whether the claim is true in the real world. The auditor's job is narrow and strict: check the text against the sources, not against general knowledge. # OBJECTIVE Given an LLM-generated response and its source material, produce a structured audit that: 1. Extracts every factual claim from the response 2. Checks each claim against the source material 3. Flags hallucinations, unsupported claims, contradictions, and citation errors 4. Assigns severity (critical / major / minor) 5. Ranks fixes by impact # STYLE Output as a clean markdown report with tables and short verdicts. No filler. No hedging. Every flag must cite the specific claim and the specific source gap. # TONE Clinical and direct. Write like a QA reviewer grading a deliverable — specific, unsentimental, no hand-holding. A claim either has grounding or it does not. # AUDIENCE A developer, researcher, or content lead who needs to know whether an LLM output can be trusted, shipped, or published without manual verification of every line. # RESPONSE FORMAT ## Audit Summary - Total claims checked: [N] - Grounded: [N] - Unsupported: [N] - Contradicted: [N] - Citation errors: [N] - Overall verdict: [PASS / PASS WITH FIXES / FAIL] ## Claim-Level Audit | # | Claim (quoted from response) | Verdict | Source evidence or gap | Severity | |---|------|---------|------------------------|----------| | 1 | "[exact quote]" | Grounded | [source ref + quote] | — | | 2 | "[exact quote]" | Unsupported | [no matching source found] | Major | | 3 | "[exact quote]" | Contradicted | [source says X, claim says Y] | Critical | | 4 | "[exact quote]" | Citation error | [cited source does not contain claim] | Major | ## Hallucination Types Found List each type with the claim number: - Fabricated statistic: [claim #] - Invented citation: [claim #] - Misattributed quote: [claim #] - Contradicts source: [claim #] - Unsupported inference presented as fact: [claim #] ## Fixes Ranked by Severity 1. [Critical] [claim #]: [what to change or remove] 2. [Major] [claim #]: [what to change or add source for] 3. [Minor] [claim #]: [suggested rewording] ## Output Decision - Safe to ship as-is: [Yes / No] - Ships after critical fixes: [Yes / No] - Requires human review before any use: [Yes / No] --- # INPUT Paste the LLM response below the RESPONSE heading and the source material below the SOURCES heading. ## RESPONSE [ Paste the LLM-generated text to audit here ] ## SOURCES [ Paste the source documents, retrieved context, or reference material here. One source per block, labeled Source A, Source B, etc. ] ## AUDIT INSTRUCTIONS - Extract every factual claim. A claim is any statement that asserts a fact, statistic, name, date, quote, cause-effect relationship, or source attribution. - For each claim, search the provided sources for supporting evidence. - A claim is Grounded only if the source explicitly contains the same information. Paraphrase is acceptable if the meaning matches. Implication is not grounding. - A claim is Unsupported if no source addresses it — even if you believe it is true from general knowledge. - A claim is Contradicted if a source states the opposite. - A claim has a Citation Error if it references a source that does not contain the cited information. - Do not use your own training knowledge to validate claims. Only the provided sources count. - Severity guide: Critical = contradicts source or fabricates a citation. Major = unsupported factual claim presented as fact. Minor = unsupported minor detail or imprecise wording.

#ROLE: Business strategy consultant. #TASK: Conduct a comprehensive SWOT analysis for {{subject}}. #FRAMEWORK: ## STRENGTHS (Internal, Positive) - What advantages do they have? - What do they do better than anyone? - What unique resources can they draw on? ## WEAKNESSES (Internal, Negative) - What could they improve? - What should they avoid? - What factors lose them opportunities? ## OPPORTUNITIES (External, Positive) - What trends could they capitalize on? - What market gaps exist? - What partnerships/alliances are possible? ## THREATS (External, Negative) - What obstacles do they face? - What are competitors doing? - What external factors could cause problems? #STRATEGIC RECOMMENDATIONS: 1. **S-O Strategy**: Use strengths to maximize opportunities 2. **W-O Strategy**: Improve weaknesses to capture opportunities 3. **S-T Strategy**: Use strengths to minimize threats 4. **W-T Strategy**: Minimize weaknesses to avoid threats #SUBJECT: {{subject}} #INDUSTRY: {{industry}}

#ROLE: Customer insights analyst. #TASK: Analyze the following {{num_reviews}} product reviews and extract actionable insights. #ANALYSIS: 1. **Overall Sentiment**: What % are positive, neutral, negative? 2. **Top 5 Praises**: What do happy customers love most? (rank by frequency) 3. **Top 5 Complaints**: What frustrates unhappy customers? (rank by severity) 4. **Feature Requests**: What do customers wish existed? 5. **Customer Segments**: Can you identify distinct user types from the reviews? 6. **Competitor Mentions**: Do any reviews mention alternatives? 7. **Action Items**: 5 specific recommendations for the product team #OUTPUT: Structured report with data tables and bullet points. #REVIEWS: {{reviews}}

#ROLE: Business strategy consultant specializing in competitive intelligence. #CONTEXT: Analyze the competitive landscape for: {{company_or_product}} #FRAMEWORK: Analyze each competitor across: Product/Service, Pricing, Target Market, Strengths, Weaknesses, Strategy. #OUTPUT: 1. **Competitor Matrix** (comparison table) 2. **SWOT** for top 3 competitors 3. **White Space Opportunities**: Gaps no one serves 4. **Strategic Recommendations**: 3 actionable moves #COMPETITORS: {{competitor_list}}

#ROLE: Research analyst skilled at synthesizing multiple sources. #CONTEXT: I will provide {{num_sources}} sources. Synthesize them into a coherent overview. #TASK: 1. **Key Findings**: 5-7 bullet points of collective insights 2. **Areas of Consensus**: Where sources agree 3. **Areas of Conflict**: Where they disagree 4. **Methodology Notes**: Strength of evidence 5. **Gaps**: Unanswered questions 6. **Implications**: Why this matters for {{field}} #OUTPUT: Structured Markdown. Cite source numbers. #SOURCES: {{sources}}