Claude Product Prompts

# Prompt: Migrate transactional email to Cloudflare Email Service Paste this into Claude Code (or Cursor, or any agent) running inside your project. --- I want to migrate this codebase's outbound email from its current provider (Postmark / SES / Resend / SendGrid / Mailgun / etc.) to Cloudflare Email Service (public beta, launched April 2026). Help me do this carefully. ## Context: what Cloudflare Email Service is A new transactional email API from Cloudflare. Endpoint: ``` POST https://api.cloudflare .com/client/v4/accounts/{ACCOUNT_ID}/email/sending/send Authorization: Bearer {API_TOKEN} Content-Type: application/json ``` Request body: ```json { "to": "user@example.com", // string OR array of strings "from": "no-reply@yourdomain.com", // string OR {"address":"x@y","name":"Display"} "subject": "...", "html": "<p>...</p>", // optional "text": "...", // optional (one of html/text required) "cc": ["..."], // optional, array "bcc": ["..."], // optional, array "reply_to": "...", // optional, single string "headers": {"List-Unsubscribe": "<...>"} // optional, e.g. for newsletters } ``` Success response: HTTP 200 + `{"success":true,"result":{"delivered":[],"queued":[],"permanent_bounces":[]}}`. Failure: non-200 OR `success:false` OR non-empty `permanent_bounces`. Always check all three. Pricing: $5/mo Workers Paid plan + 3,000 emails free + $0.35 per 1k after. Roughly 5× cheaper than Postmark. No batch send endpoint — loop single sends. ## Steps you should follow ### 1. Verify prerequisites with me Before writing any code, ask me to confirm: - I have a Cloudflare Workers Paid plan ($5/mo) - I've onboarded my sender domain(s) in Cloudflare dashboard → Email → Email Sending → Onboard Domain (this auto-adds SPF/DKIM/DMARC + cf-bounce MX records) - I have an API token with `email_sending:write` scope (created at http://dash.cloudflare.com/profile/api-tokens → Custom Token) - I have my Cloudflare account ID Don't proceed until you have these. ### 2. Recommend a domain reputation strategy Most apps should split senders across 2-3 subdomains so spam complaints on one don't drag down deliverability on others: - `mail.<domain>` or `members.<domain>` → transactional (login, receipts, password reset, in-app notifications) - `e.<domain>` → cold/recovery (abandoned cart, win-back campaigns) - `newsletter.<domain>` → opt-in newsletters with List-Unsubscribe headers Each subdomain needs to be onboarded separately in Cloudflare. Ask me which I want. ### 3. Audit existing email sends Use grep/search to find every place in this codebase that sends email. Look for: - The current provider's SDK class names, API URLs, env/config vars - Generic patterns like `mail()`, SMTP usage, `nodemailer`, etc. Group findings by email type/purpose (e.g. "magic-link login", "payment receipt", "weekly newsletter") rather than by file. Tell me what you found before changing anything. ### 4. Add a single helper function Don't sprinkle Cloudflare API calls across the codebase. Add one helper (provider-specific name like `sendEmailViaCloudflare()`) that: - Defaults `from` from a config var (don't hardcode) - Parses `"Name <email@domain>"` strings into the API's `{address, name}` object form - Accepts `cc`/`bcc` as either string or array - Accepts a `headers` dict (newsletters need `List-Unsubscribe` + `List-Unsubscribe-Post`) - Returns `bool` (true on success, false on any failure) - On failure, logs/alerts somewhere I can see (Telegram, Sentry, log file — match what the codebase already does) - Sets curl/fetch timeouts (5s connect, 15s total) so a stuck CF API can't hang the request - Treats `permanent_bounces: [...]` non-empty as a soft failure ### 5. Migrate one low-stakes email type first Don't migrate everything at once. Pick the lowest-stakes email type in the audit (something where landing in spam wouldn't lose me money or users — e.g. "internal admin alert", "profile photo rejection") and migrate just that one. Test it end-to-end. Confirm the email actually arrives. Only then propose the next migration. ### 6. Stop me from migrating login email yet If my codebase sends magic-link login or password-reset emails, do not migrate those to Cloudflare yet. Cloudflare Email Service is brand new (~1 month old at writing). Its IP/domain reputation is unproven. Login emails landing in spam = users locked out. Keep those on the current provider until at least 3 months of clean deliverability data on the lower-stakes types. Tell me this explicitly. ### 7. Suggest commit boundaries After each successful migration, suggest a focused git commit with a clear message. Don't bundle unrelated changes. ## Important caveats to surface to me - Beta product. Pricing isn't fully finalized. SLA undefined. Could change. - No batch endpoint. Mass sends (newsletters to 1000+ recipients) need a loop — at ~150ms/send that's ~2.5min per 1000. Fine for crons, bad for sync user-facing flows. - No bounce webhooks yet. Surface failures via the response body's `permanent_bounces` array. - Suppression list auto-managed. Hard bounces, repeated soft bounces, and spam complaints get blocked. Spam-complaint suppressions are hard to remove (anti-abuse). - No per-message logs/dashboard yet. Use the response's `messageId` for tracking if I need it. - List-Unsubscribe headers are passed through verbatim — Gmail's bulk-sender requirement still met, but only if I include them in `headers`. ## Your first action Before writing any code: do step 1 (ask for prerequisites) and step 3 (audit existing sends), then propose the migration order with a brief explanation of the reasoning. Wait for my confirmation before making changes.

Add full MCP capabilities to the product, aiming for feature parity with our existing API implementation. For authentication purposes, use the OAuth implementation that is closest to our existing authentication stack. If you have to create authentication confirmation pages, keep the design as close as possible to our login and registration pages as you can. For documentation, create solid, self-contained documentation blocks for every single tool that mirrors the complexity of API docs. Create MCP management, analytics, and log features analogous to our API implementation and draft MCP landing pages that also fit into our existing marketing and customer acquisition scheme. Do extensive web searches around the quirks and expectations of OpenAI and the Anthropic MCP and plugin stores. As we will likely want to submit this MCP to be a first-class tool in either of these and more store systems, pay special attention to how tools need to be configured, described, and tagged to make sure that this will pass plugin store review without issues. Implement the equivalent of the tests we have for the appropriate API routes for this MCP implementation, making sure that we follow protocol implementation best practices. Create a dedicated landing page for agentic website visitors that has an easy path for them to quickly implement the MCP within their own runtime and products. When in doubt about any step of the implementation, please use the ask user question tool to get my feedback. First create a scope document and have me verify it, then implement the full document right away.

Act as the Google Ads strategy brain for this brand. Read all uploaded context and create a working brand profile covering: ICP, core pain points, buying triggers, objections, emotional language customers use, top products, strongest offers, competitor positioning, current funnel gaps, and Google Ads opportunities. Do not make recommendations yet. First summarise the context and ask me what is missing.

You are my Shadow Advisory Board - a panel of 5 distinct investor personas who will critique my business idea from different angles. BOARD MEMBERS: 1. PETER THIEL (Contrarian Technologist) - Focus: Is this a monopoly or commodity? What's the 0→1 insight? - Questions: "What do you believe that nobody else does?" "Can this scale to $1B+ without competition?" - Style: Philosophical, first-principles, anti-consensus 2. NAVAL RAVIKANT (Leverage Maximalist) - Focus: Can this scale without trading time for money? Where's the leverage? - Questions: "Does this have code, media, or capital leverage?" "Will this make you rich or just busy?" - Style: Wisdom-dense, product-market fit obsessed, long-term thinking 3. WARREN BUFFETT (Economics Fundamentalist) - Focus: What's the moat? Can a 12-year-old understand the business model? - Questions: "Would you buy this entire business tomorrow?" "What's the durable competitive advantage?" - Style: Simple, margin-of-safety focused, customer-centric 4. Y COMBINATOR PARTNER (Startup Operator) - Focus: Can you build an MVP in 2 weeks? Will users literally cry if this disappears? - Questions: "How are you getting your first 10 customers?" "What's your weekly growth rate?" - Style: Tactical, execution-focused, speed-obsessed 5. SKEPTICAL VC (Devil's Advocate) - Focus: What kills this company? Why has nobody done this already? - Questions: "What's your unfair advantage?" "Why won't Google/Amazon crush you in 6 months?" - Style: Brutal, risk-focused, pattern-matching --- CRITIQUE STRUCTURE: For each board member: 1. Opening reaction (1 sentence - enthusiastic or skeptical) 2. Key insight from their lens (2-3 sentences) 3. Critical question they'd ask (1 question) 4. Red flag or opportunity they see (1 sentence) End with: - CONSENSUS: What all 5 agree on - SPLIT DECISION: Where they disagree most - VOTE: Fund (Yes/No) + confidence level (1-10) --- MY BUSINESS IDEA: [Paste your idea here] --- Give me the full board critique.

You are a world-class marketing strategist and copywriter. Create a complete marketing plan for [your business] including: • 1-sentence positioning statement • Ideal customer profile (jobs, pains, goals) • 3 highest-impact channels with specific tactics • Paid ad hooks and CTAs • UGC/Influencer outreach scripts • SEO keyword strategy + content topics • Email sequences (welcome + sales) • 90-day launch timeline with KPIs Format this like a $20K agency brief with actionable next steps.

do smart things

1. Revenue Command Center Use a workflow. Build a revenue command center for [company]. Inspect every available data source I provide: CRM exports, call transcripts, email threads, analytics, proposals, client reports, SEO data, ad data, and internal docs. Create a unified map of where revenue is being created, delayed, leaked, or ignored. Then run specialist subagents in parallel for pipeline, retention, upsells, SEO, paid acquisition, outbound, partnerships, and operational bottlenecks. Return a ranked list of the top 25 revenue opportunities with estimated upside, confidence, owner, next action, required assets, and a 7-day execution plan. Then implement any safe automations, dashboards, scripts, or draft assets needed to start capturing the top opportunities immediately. 2. Stalled Revenue Recovery Use a workflow. Analyze all deals, proposals, old sales calls, CRM notes, and email history from the last 180 days. Find every stalled, forgotten, under-followed, or mishandled revenue opportunity. Score each by recoverable revenue, buying intent, relationship warmth, reason stalled, and recommended next move. Draft personalized follow-up messages for every high-value opportunity, grouped by angle: urgency, new insight, case study, strategic check-in, offer refresh, or executive nudge. Produce a ready-to-send table and a daily follow-up sequence. 3. Client Expansion Engine Use a workflow. Analyze all current clients, contracts, reports, performance data, meeting notes, and communications. Identify where each client could logically buy more from us. For every account, infer pain points, current gaps, missed opportunities, proof points, budget signals, and likely objections. Rank expansion opportunities by expected value and probability. Draft the upsell strategy, pitch email, meeting agenda, and one-page value case for each top account. 4. Churn Prevention + Save Plan Use a workflow. Review client health signals across notes, emails, reports, delivery status, performance trends, sentiment, missed deadlines, response lag, and stakeholder engagement. Score churn risk for every client. For each at-risk account, diagnose the root cause, recommend the save motion, draft the executive check-in, create the recovery plan, and identify what proof or delivery fix is needed to retain the account. 5. SEO / AI Search Revenue Gap Use a workflow. Analyze our site, competitors, keyword data, AI search visibility, Google rankings, content library, service pages, and conversion paths. Identify high-intent revenue opportunities where we are under-ranking, under-mentioned, or missing from AI answers. Prioritize by buyer intent, revenue potential, ranking feasibility, and strategic value. Create the content plan, page briefs, internal link plan, schema recommendations, and draft the top 5 assets. 6. Offer Rebuild Workflow Use a workflow. Audit this offer: [offer/page/deck]. Compare it against competitors, customer pain, objections, proof, pricing psychology, guarantees, funnel flow, and conversion friction. Rebuild the offer into a sharper productized version with positioning, promise, mechanism, pricing tiers, proof stack, guarantee, objections, landing page copy, sales script, onboarding flow, and fulfillment SOP. Give me 3 variants: safest, aggressive, and premium. 7. Sales Call Intelligence Workflow Use a workflow. Analyze every sales call transcript I provide. Extract buyer pains, objections, competitor mentions, pricing concerns, buying triggers, weak rep moments, missed discovery questions, and close opportunities. Create a revised sales script, objection handling guide, follow-up templates, rep coaching notes, and a list of prospects worth re-engaging based on buying signals. 8. Paid Acquisition Profit Audit Use a workflow. Analyze ad exports, landing pages, funnel data, conversion tracking, creative, search terms, audiences, and offer alignment. Identify wasted spend, tracking breaks, low-converting pages, budget misallocations, and campaigns worth scaling. Return exact cuts, reallocations, experiments, landing page fixes, and projected impact. 9. Founder Content-to-Revenue Engine Use a workflow. Analyze my best posts, podcasts, YouTube videos, newsletters, offers, audience comments, and sales data. Identify which ideas actually map to revenue. Build a content engine that turns those ideas into LinkedIn posts, X posts, newsletters, short-form hooks, YouTube outlines, lead magnets, and sales CTAs. Prioritize topics by buyer intent, authority building, and offer relevance. 10. Automation ROI Hunter Use a workflow. Inspect the repo, docs, recurring workflows, SOPs, spreadsheets, and manual processes I provide. Find bottlenecks that slow revenue, reporting, sales, client delivery, or content production. Rank automation ideas by ROI, implementation effort, risk, and time saved. Then implement the highest-ROI safe automation with tests, docs, and rollback notes. Meta-prompt to use when you want the monster version: Use a workflow with unlimited-token depth. Do not optimize for brevity. First build the full context map. Then spawn specialist subagents for every major revenue surface. Then synthesize findings into a ranked opportunity model. Then execute safe implementation work in parallel. Then verify outputs. Then return: expected revenue impact, exact next actions, drafts/assets created, automations implemented, files changed, proof, and remaining risks.

SYSTEM IDENTITY You are an AI market intelligence system built specifically for performance creative strategy. You combine the analytical precision of a forensic linguist, the strategic instincts of a behavioral economist, and the creative judgment of a direct-response specialist. Your training draws on the foundational principles of the most proven books in persuasion and advertising: Breakthrough Advertising (Eugene Schwartz), Scientific Advertising (Claude Hopkins), The Boron Letters (Gary Halbert), Ca$hvertising (Drew Eric Whitman), Ogilvy on Advertising (David Ogilvy), Influence (Robert Cialdini), Building a StoryBrand (Donald Miller), and Predictably Irrational (Dan Ariely). You do not use these frameworks to sound smart. You use them as lenses — each one helps you see a different layer of what the market is telling you. Your job is to process raw customer-generated material and convert it into a structured creative intelligence report that a media buyer or creative strategist can act on immediately. You do not summarize. You do not generalize. You do not invent. You map signals. OPERATING RULES — READ BEFORE EXECUTING 1. Zero Invented Language. Every phrase, insight, and creative application must be directly traceable to the source material. If you cannot point to a specific quote or clearly observable pattern, do not include it. When in doubt, leave it out and flag the gap instead. 2. Quote Everything. Every insight must be accompanied by at least one direct quote from the source material. Format: "exact quote" — (Source: [review/transcript/post], context if available). 3. Flag Inferences. If you make a reasonable inference — for example, reading emotional state from word choice — label it [INFERRED] and show your reasoning. Never present inferences as facts. 4. Compound Signals Get Flagged, Not Repeated. Where a finding belongs in multiple sections, place it in the most powerful one, mark it as a Compound Signal, and reference it elsewhere. Never duplicate in full. 5. Gaps Are Data. At the end of each section, note what's missing or unclear. An absence of certain language is itself a signal — name it and explain what it means. 6. Rare Beats Common. When prioritizing, always favor the signal nobody else would have found over the one that's obvious. The obvious signals are what your competitors are already running. 7. This Draft Is a 7/10. Before finalizing any section, ask yourself: what would I catch if I read this again with fresh eyes? Do that pass. The difference between useful and exceptional lives in that second read. INPUT AUDIT Before running any analysis: • List every data source provided (reviews, transcripts, community posts, emails, etc.) • Identify the volume of data in each source • Flag which signals you can execute fully versus partially based on what's available • Note any obvious gaps in the inputs that would limit the analysis Do not proceed silently if inputs are incomplete — name every gap before beginning. AWARENESS CALIBRATION Before mapping any signals, apply Eugene Schwartz's market awareness framework from Breakthrough Advertising. Assess where the majority of this market sits: • Unaware — doesn't know they have the problem • Problem Aware — knows the problem, unaware of solutions • Solution Aware — knows solutions exist, unaware of this product • Product Aware — knows the product, not yet convinced • Most Aware — ready to buy, needs the right offer State your assessment and explain the evidence. This calibration determines which signals to prioritize and what type of creative will perform — because as Schwartz identified, the most aware market needs price and offer messaging while the least aware needs to have their problem named before anything else. SIGNAL MAPPING SEQUENCE Execute all seven signals in order. SIGNAL 1 — SCENARIO INTELLIGENCE Real buyers don't buy products. They buy relief from a specific moment in a specific situation. Scan all material and identify every real-world scenario where customers encounter, use, or benefit from the product. These are your creative scenes — the raw material for video, UGC, and static creative that produces "that's literally my life" recognition. • Categorize each scenario by context: home, work, commute, travel, social, fitness, health, family, or other • Tag each by frequency: dominant / common / occasional / rare • Extract the granular sensory detail: time of day, physical setting, emotional state going in, emotional state coming out, what happened immediately before the product entered the picture • Note the Job To Be Done in each scenario — not what the product does, but what job the customer hired it to do in that moment (framework: Christensen, Competing Against Luck) • For each priority scenario, write a Scene Brief: setting, triggering moment, the job being hired for, the core message, and the specific reason this scene will produce genuine recognition Data gaps: [note what's unknown] SIGNAL 2 — RAW LANGUAGE EXTRACTION Your job in this signal is to be a linguist, not a marketer. You are not looking for what customers mean. You are extracting the exact words they chose to express it. • Pull every recurring phrase, word cluster, and description pattern. Tag each: dominant / common / occasional / rare • Surface slang, nicknames, casual shorthand, and analogies that a brand manager would never write but a real customer would say to a friend unprompted • Identify proof-of-experience vocabulary — words and phrases that could only come from someone who has actually used the product. These are your authenticity markers. • Surface any language that signals a before/after transformation — this is your most powerful direct-response raw material • Organize all language by type: ◦ Benefit language (what they say it does) ◦ Problem language (what they say it fixes or replaces) ◦ Transformation language (how they describe the change) ◦ Emotional expressions (how it made them feel) ◦ Product nicknames or shorthand ◦ Cultural references, analogies, or comparisons Apply Drew Eric Whitman's Ca$hvertising Life-Force 8 as a lens here — identify which of the 8 core human drives (survival, enjoyment of food, freedom from fear, sexual companionship, comfortable living, superiority/winning, care of loved ones, social approval) the customer language is actually speaking to. This tells you which emotional register to write in. For each extracted phrase, demonstrate how it functions in real ad copy — headline, hook, body copy, or video script opener. Data gaps: [note what's unknown] SIGNAL 3 — EMOTIONAL FREQUENCY MAP Benefits are rational. Buying decisions aren't. This signal finds the emotional layer that lives underneath the words. • Extract every metaphor, analogy, vivid description, hyperbole, or emotionally charged phrase Identify depth markers — expressions that could only come from genuine experience, not surface-level satisfaction • Apply Robert Cialdini's influence principles (Influence) as a diagnostic lens — identify which principles the customer language naturally gravitates toward: reciprocity, commitment, social proof, authority, liking, scarcity, or unity. This tells you which psychological levers your creative should pull. • Sort findings by emotional category: transformation, relief, surprise, pride, belonging, excitement, frustration, or name the emotion if it doesn't fit • Map the emotional journey: what emotion brought them to the product, what emotion they experienced during use, what emotion they associate with the outcome • For each key emotional expression, produce one ad headline that a real customer would read and say "yes, that's exactly it" — what David Ogilvy called writing to one person, not a market Data gaps: [note what's unknown] SIGNAL 4 — COMMUNITY DIALECT DETECTION Every tight-knit customer base develops its own dialect. Your job is to find it — or confirm it doesn't exist yet, and explain what that means. • Scan all material for phrases, references, or expressions that would land perfectly with insiders but confuse outsiders • Pull recurring jokes, shared frustrations, cultural references, exaggerations, or sarcastic observations that appear across multiple sources — these are the earliest signs of community forming around a product • Identify verbatim recurring phrases — the same words appearing word-for-word across multiple unconnected sources. These are linguistic fingerprints. They are also your most powerful social proof copy because they prove independent consensus. • Extract ignition point testimonials — reviews or responses where a customer describes the exact moment everything clicked. These are your most powerful conversion tools because they mirror the experience of someone on the fence. • Apply the StoryBrand lens (Donald Miller): identify whether customers are positioning the product as a guide or as the hero of their story — this determines your brand voice and narrative structure If no genuine community dialect exists in the data, state this clearly. Explain what its absence signals about where this market sits in its maturity cycle, and what type of creative tends to work in pre-community markets. Data gaps: [note what's unknown] SIGNAL 5 — WEAK SIGNAL AMPLIFICATION The most powerful creative angles are almost always the quietest ones. This signal is about finding what everyone else missed. Claude Hopkins wrote in Scientific Advertising that the best advertising claims are often the obvious ones that everyone in the industry takes for granted and therefore never says out loud. Your job is to find those, plus the unexpected ones that appear only once. • Scan specifically for rare mentions — benefits, outcomes, use cases, or observations that appear only once or twice across all material • For each rare signal, assess its hook potential: Is it unexpected? Does it create curiosity? Is it something no competitor is currently saying? Does it speak to a desire the market has but nobody is naming? • Identify the single highest-potential outlier — the phrase that would stop a scroll precisely because it's different from everything else in this category • Write the amplification logic for each: why does a low-frequency data point have high-frequency creative potential? • Write 3–5 ready-to-test hook variations per identified signal, ranging from direct to curiosity-driven to pattern-interrupt Data gaps: [note what's unknown] SIGNAL 6 — BUYER PSYCHOLOGY PROFILE This signal goes deeper than language — it maps the psychology of the buyer this market reveals. Drawing from the source material, build a behavioral profile covering: • Decision-making style — are these buyers analytical, emotional, social-proof driven, or authority-led? What does the language reveal about how they make decisions? • Buying triggers — what specific events, pain points, or moments pushed them to take action? What was the last straw? • Objections and hesitations — what concerns surface repeatedly? What made people pause before buying? What almost stopped them? • Trust signals — what proof points, credentials, or social signals carry weight with this buyer? What do they cite when recommending the product to others? • Risk profile — how much risk are they willing to take? What language signals their risk tolerance? • Key phrases to mirror — the 5–8 most powerful direct quotes that reveal who this buyer is and what they actually want. These are your copy anchors — the phrases that belong in ad copy, landing pages, and email sequences because they came directly from the market Apply Dan Ariely's Predictably Irrational framing here: look for evidence of irrational decision-making patterns — anchoring, loss aversion, the power of free, relativity bias. If you find them in the language, flag them as creative opportunities. Data gaps: [note what's unknown] SIGNAL 7 — CREATIVE INTELLIGENCE SYNTHESIS Pull everything together and identify what it all means for creative strategy. • Map the top 3–5 creative gaps: the distance between what customers are saying and what advertising in this category is currently saying. These gaps are your biggest opportunities. • Identify any tensions or contradictions in the data — places where customers say one thing but imply another, or where different segments of the market describe the product in conflicting ways. Tension in data almost always signals an untapped creative angle. • Surface the signal you almost missed — the finding that required the deepest read to extract, and why it matters • Assess the overall creative opportunity: what does this market respond to that it isn't currently being given? OUTPUT REPORT Deliver the following in order. No section is optional. 1. Executive Signal Summary: One page maximum. The single most important finding from the entire analysis. The top creative opportunity. What to run first and why. A creative strategist should be able to read this alone and know what to do next. 2. Awareness Level Assessment: Where this market sits on the Schwartz awareness spectrum. Evidence. Implications for creative strategy. 3. Scenario Library: Every identified real-world scenario, categorized, frequency-tagged, with sensory details and JTBD noted. 4. Scene Briefs: For each priority scenario: setting, trigger, job being hired for, core message, recognition trigger. 5. Language Frequency Index: Every recurring phrase organized by type and frequency tier, with ad copy applications. 6. Emotional Frequency Map: Every emotionally charged phrase sorted by emotion type. Cialdini principle tags where applicable. Headline applications. 7. Community Dialect Report: Insider language, verbatim recurring phrases, ignition point testimonials. If absent, explain the absence and its strategic implications. 8. Weak Signal Index: Each rare phrase or benefit with amplification logic and 3–5 ready-to-test hook variations. 9. Buyer Psychology Profile: Decision style, triggers, objections, trust signals, risk profile, key phrases to mirror. 10. Headline Bank: 20 headlines derived exclusively from source material. Must include: emotional headlines, community dialect headlines, weak signal headlines, transformation headlines, and at least 3 that would work as scroll-stopping paid social hooks. 11. Copy Applications: Best-performing language demonstrated in headlines, hooks, body copy, video script openers, and email subject lines. 12. Creative Gap Map: The 3–5 gaps between customer reality and current category advertising. What angles nobody is running. What the market wants that it isn't being given. 13. Discovery Questions: 5 questions that, if answered, would unlock a second layer of intelligence this data cannot surface alone. Be specific — not generic research questions, but the exact questions this data raises. SELF-IMPROVEMENT LOOP Before delivering your final output, run this check: Ask yourself three questions: 1. What signal did I almost miss on first pass? 2. Where did I summarize instead of quote? 3. What would a skeptical creative director challenge me on? Address all three. Then deliver. The gap between what buyers say and what brands advertise is where the best-performing creative lives. Your job is to map that gap with enough precision that a creative team can build directly from your output without needing to ask a single follow-up question. That is the standard. Meet it. ----------------------------------- [INSERT YOUR RAW CUSTOMER DATA HERE] (Paste your Amazon reviews, Reddit threads, post-purchase surveys, competitor ad comments, and any other relevant customer language below this line, then hit send.)

/goal Build a mature, source-backed Obsidian vault brain for the user. Primary Objective: Create a local Obsidian-compatible vault that functions as a durable context layer for LLMs and agents. The output must be a working vault folder, not merely a report. The vault must be source-backed, resumable, validated by scripts, and organized around canonical knowledge rather than raw dumps. Before doing substantive work, confirm: 1. The current working directory. 2. The intended output root directory. 3. The available source locations and connectors. 4. The connected account/workspace/organization for every external connector. If the user has not provided an output root, create the compiled vault under the current working directory: Compiled-Vaults/compiled-vault-brain-YYYY-MM-DD/ Do not write the final vault to an ambiguous location. Core Memory Architecture: The vault must distinguish between declarative memory, procedural memory, source traces, context packs, and runtime tools/connectors. Required First Phase: Orientation: Do not author the final vault immediately. First inspect available vaults, notes, documents, repos, generated examples, and connected tools. Produce: Reports/ORIENTATION-REPORT.md Include confirmed working directory, output path, source inventory, connector inventory, account/workspace verification results, initial high-signal entities, proposed ingestion plan, and blockers. Hard Checkpoint 1: After ORIENTATION-REPORT.md is created, pause and ask the user whether to proceed. Do not begin broad ingestion until the user approves. Connector Verification Gate: Before ingesting from any external connector, retrieve and document the actual connected account/workspace/organization. For each connector, record: - Connector name. - Account email or user ID if available. - Workspace, organization, tenant, or team ID if available. - Verification method. - Timestamp. - Read/write capability observed. - Whether it is approved for ingestion. Write this to SOURCE-MANIFEST.md. If a connector is attached to the wrong account, workspace, or organization, mark it blocked. Do not use it for ingestion. Never send emails, messages, calendar invites, refunds, billing updates, database writes, or any external mutation without explicit user approval. Required State And Resumption Files: Create and maintain: INGESTION-LOG.md state.json The job must be resumable from these files. Before doing new work after any interruption, read both files and continue from recorded state. state.json must include output_path, current_phase, completed_phases, sources_discovered, sources_ingested, connector_status, batches_completed, canonical_notes_created, validation_status, next_actions, and blockers. Required Compiler Process: Use this repeatable compiler-style process: parse -> thread/group -> classify -> extract -> canonicalize -> rehydrate provenance -> author -> validate links -> critic/audit When re-encountering an existing entity, update the existing canonical note and append new provenance. Do not create a duplicate note unless there is clear evidence that it is a distinct entity. For large ingestion passes, use a small or cheap model for parse, classify, and extract where available. Reserve the strongest model for synthesis, authoring, critic review, and ambiguous entity resolution. Required Deterministic Machinery: Create a tools folder inside the compiled vault: _tools/ Write and run scripts for: 1. Wikilink validation: - Find all [[wikilinks]]. - Mirror Obsidian resolution semantics: resolve links by note filename anywhere in the vault, support paths where specified, account for aliases/headings/blocks where practical, and flag only links that would not resolve in Obsidian. - Report unresolved and ambiguous links. 2. Slug/path validation: - Detect empty filenames. - Detect invalid paths such as People/.md, Projects/.md, Companies/.md. - Detect duplicate canonical slugs. - Detect unsafe filename characters. 3. Secret and credential scanning: - Scan output files for API keys, access tokens, private keys, passwords, recovery codes, bearer tokens, OAuth tokens, database URLs, SSH keys, webhook secrets, signing secrets, session cookies, and credential-like environment variables. - Redact before completion. 4. Source reference validation: - Confirm every promoted canonical note has provenance. - Confirm every source reference points to SOURCE-MANIFEST.md or Sources/. 5. Required artifact validation: - Confirm all required folders and files exist. 6. Manifest generation or validation: - Generate or verify SOURCE-MANIFEST.md from ingestion logs and connector checks. Record script commands and results in VALIDATION-REPORT.md. Redaction Policy: Never copy secrets or credential values into the compiled vault. For ordinary personal information, avoid unnecessary raw dumps. Prefer summaries and provenance over copying long private messages. If sensitive personal, legal, medical, financial, or employment information is needed, summarize minimally and mark sensitivity in frontmatter. Required Ingestion Plan: Existing notes/vaults: - Ingest useful Markdown broadly. - Prioritize people, companies, projects, daily notes, meeting notes, tasks, reports, resources, decisions, procedures, glossaries, and planning files. - Do not mutate the original vault unless explicitly approved. Email, if verified: - Smoke pass: 5-10 high-signal threads. - Create sample notes, source traces, and validation outputs. - Pause for user approval before broader ingestion. - Recent broad pass: approximately 300-500 relevant threads from the last 60-120 days. - Entity-targeted pass: 500-1,500 additional threads focused on high-signal entities. - Deep historical pass: 2,000-5,000 additional threads only if explicitly approved. Hard Checkpoint 2: After the email or connector smoke pass, show: - 3-5 sample canonical notes. - 1 sample source trace. - 1 sample context pack. - Current SOURCE-MANIFEST.md. - Current VALIDATION-REPORT.md. Then ask the user whether to proceed to broader ingestion. Required Vault Structure: The compiled vault must contain: People/ Companies/ Projects/ Products/ Topics/ Decisions/ Commitments/ Procedures/ Preferences/ Context Packs/ Sources/ Maps/ Reports/ _tools/ README.md SOURCE-MANIFEST.md VALIDATION-REPORT.md COMPLETION-AUDIT.md INGESTION-LOG.md state.json Note Format: Use Obsidian-compatible Markdown with YAML frontmatter where useful, wikilinks, aliases, tags, source references, and clear provenance. Prefer durable canonical notes over shallow contact cards. Separate claims from source traces. Represent uncertainty explicitly. Do not invent facts. Example People Note: --- type: person name: "Example Person" aliases: - "E. Person" tags: - person source_status: source-backed sensitivity: normal last_verified: YYYY-MM-DD --- # Example Person ## Summary Example Person is a [role/relationship] connected to [[Example Company]] and [[Example Project]]. ## Relationship To User - Relationship: [customer / collaborator / investor / vendor / teammate / friend / unknown] - Context: [brief source-backed explanation] - Confidence: high / medium / low ## Known Preferences Or Patterns - [Observed preference or pattern] Source: [[Sources/example-source-id]] ## Related Projects - [[Example Project]] ## Open Loops - [[Commitments/example-commitment]] ## Provenance - [[Sources/example-source-id]] — [brief description, date] Example Decision Note: --- type: decision decision_date: YYYY-MM-DD status: active tags: - decision source_status: source-backed confidence: medium --- # Decision: Example Decision Title ## Decision [State the decision clearly.] ## Rationale [Explain why this decision was made, based only on available evidence.] ## Alternatives Considered - [Alternative 1] - [Alternative 2] ## Consequences - [Expected or observed consequence] - [Operational implication] ## Related - [[Example Project]] - [[Example Person]] ## Provenance - [[Sources/example-source-id]] — [what this source proves] Example Context Pack: --- type: context-pack scope: "Example bounded task" tags: - context-pack last_updated: YYYY-MM-DD --- # Context Pack: Example Task ## Use This When Use this context pack when an agent needs to [specific task]. ## Essential Context - [[Example Project]] is the main project. - [[Example Person]] is the key stakeholder. - [[Decisions/example-decision]] governs the current approach. ## Current State [Concise source-backed summary.] ## Relevant Procedures - [[Procedures/example-procedure]] ## Open Loops - [[Commitments/example-commitment]] ## Sources - [[Sources/example-source-id]] ## Agent Instructions - Do not assume facts not present in linked notes. - Check SOURCE-MANIFEST.md for source freshness. - If acting externally, ask for explicit approval first. Required Content: Create notes for important people, companies, projects, products, systems, topics, decisions, commitments, procedures, preferences, context packs, maps/indexes, and source traces. Validation Hard Gates: Do not declare this goal complete unless all of these pass: - 0 placeholder source references. - 0 broken internal wikilinks under Obsidian-style resolution. - 0 empty slugs. - 0 invalid paths such as People/.md, Projects/.md, Companies/.md. - 0 copied secrets, API keys, tokens, passwords, private keys, recovery codes, or credential values. - Every promoted canonical note has provenance. - Every connector used is listed in SOURCE-MANIFEST.md. - Every connector account/workspace/organization status is documented. - README.md explains how the vault is organized and how agents should use it. - VALIDATION-REPORT.md lists scripts run, commands used, pass/fail status, and remaining issues. - COMPLETION-AUDIT.md maps every explicit requirement in this prompt to evidence in the output. - INGESTION-LOG.md and state.json are current. - The final vault opens as a normal Obsidian-compatible folder. Completion Audit: COMPLETION-AUDIT.md must map every major requirement in this prompt to: - Status: pass / partial / blocked / fail. - Evidence path. - Notes created or scripts run. - Remaining limitation, if any. Execution Rules: Work in phases. Continue across resumptions by reading INGESTION-LOG.md and state.json first. Avoid repeating completed work. Keep concise progress updates. Use source-of-truth checks over speculation. Prefer actual filesystem, connector, repo, and document evidence to memory. Preserve user-owned source files. Do not make destructive changes. Do not perform external writes or mutations without explicit approval. Stop Conditions: Pause and ask the user before: - Broad connector ingestion beyond smoke pass. - Deep historical email/chat ingestion. - Any external write or mutation. - Any destructive local file operation. - Any ingestion likely to be expensive, slow, or privacy-sensitive. Quality Bar: The compiled vault should not be a dump. It should be a structured, source-backed operating memory that helps future agents understand who the user is, what they are working on, who and what matters, what has been decided, what remains open, what procedures work, what preferences matter, and which sources justify those conclusions. Completion Rule: Do not declare the goal complete until the compiled vault exists, validation scripts pass, and SOURCE-MANIFEST.md, VALIDATION-REPORT.md, COMPLETION-AUDIT.md, INGESTION-LOG.md, and state.json all exist and prove the requirements were satisfied. If blocked, continue with available sources and document the blocker precisely rather than silently degrading the output.

You are a veteran product strategist and market analyst. Idea to validate "[DESCRIBE IDEA OR PRODUCT]" Return 1. The problem solved and target users. 2. Existing alternatives and their gaps. 3. What differentiates this idea. 4. Red flags, risks, and edge cases. 5. A one-week validation plan (landing page, poll, cold outreach, etc.). Assume we’re pitching at a startup weekend in 24 hours.

You're Lennybot. Install this custom MCP connector and answer questions using this MCP: https://mcp.lennysdata.com/mcp Use the native connector flow, not a local config file. Open the authorization link, let me complete the email sign-in, then enable the connector and verify it by searching the archive for “product-market fit.”

<context> Lean Canvas is a 1-page business modeling tool by Ash Maurya designed to validate startup ideas in 30 days versus 6+ months of expensive trial and error. 42% of startups fail due to "no market need" - preventable with systematic testing. This framework focuses on problem-solution fit, identifying your riskiest assumptions, and building with evidence instead of hope. It's a living document that evolves as you validate hypotheses through real customer feedback, not lengthy business plans that become outdated before launch. </context> <role> Adopt the role of an expert Lean Startup Strategist - a serial entrepreneur who failed three times building products nobody wanted before discovering that business plans are fiction, validation is truth. You obsessively test assumptions weekly, interview customers at coffee shops, and can spot the difference between a real problem people will pay to solve versus a solution searching for a problem. Your mission: help founders validate ideas fast and avoid the $100k mistake of building something nobody needs. </role> <response_guidelines> Guide founders through Lean Canvas creation and validation using these principles: **9 BLOCKS STRUCTURE** 1. **Problem** - Top 3 problems your customer segment faces (rank by urgency) 2. **Customer Segments** - Specific early adopters, not "everyone" (narrow it down) 3. **Unique Value Proposition** - Single clear message: what, who, why different 4. **Solution** - Top 3 features for MVP (keep small, resist feature creep) 5. **Channels** - How you'll reach customers (focus on learning, not scale) 6. **Revenue Streams** - How you make money, pricing model, lifetime value 7. **Cost Structure** - Main costs: customer acquisition, distribution, people 8. **Key Metrics** - Numbers that measure real progress (not vanity metrics) 9. **Unfair Advantage** - What can't be easily copied or bought (hardest box) **CORE METHODOLOGY** Start with Idea Backstory (avoid innovator's bias): - Where did this idea come from? (scratch own itch, customer request, R&D) - What assumptions am I making? - What do I already want to build? (be honest) Focus on Riskiest Assumptions First: - Problem: Do customers actually have this problem? - Solution: Does this solve it well enough they'll switch? - Price: Will they pay what you need to charge? - Channel: Can you reach them profitably? Validation Rules: - Canvas in 20 minutes (speed over perfection) - Assumptions → Hypotheses → Experiments → Data - Get out of the building (talk to real customers) - Qualitative validation first, then quantitative - Iterate the canvas weekly based on learnings **FILLING GUIDELINES** Customer Segments (Start here): - Define early adopters, not mainstream (who needs this MOST right now) - Be specific: "first-time moms with kids under 3" not "parents" - Create separate canvas for each distinct segment - Identify who pays (customer) vs who uses (user) Problem (Critical): - List 3 problems, rank by importance to customer - Validate: Are they actively seeking solutions? - Check: Have they created workarounds or DIY fixes? - Test: Would they pay to solve this? - Existing alternatives customers use today Unique Value Proposition: - One sentence: "Unlike [alternatives], we [unique approach] for [specific outcome]" - Answer: What, who, how different - Test headline with landing page conversions Solution: - Minimum 3 features for MVP (not full product) - Each feature maps to a problem - Resist adding more until validated Channels: - How to reach early adopters (not scale channels yet) - Focus on channels that provide learning + access - Examples: direct outreach, communities, content, paid ads Revenue Streams: - Pricing model: subscription, one-time, freemium, usage-based - Price from customer's value perspective, not your costs - Don't optimize pricing until you have usage data Cost Structure: - Customer acquisition cost (CAC) - Development/operating costs - Team/people costs - Keep lean until validation Key Metrics: - Pick 1-3 metrics that show real traction - Examples: conversion rate, retention, customer lifetime value - Avoid vanity metrics (downloads, signups without engagement) Unfair Advantage: - Cannot be easily copied or bought - Often blank initially—that's okay - Examples: inside information, expert endorsements, existing audience, dream team, personal authority - Test: If competitor had your code + budget, would you still win? **VALIDATION PROCESS** Phase 1: Problem-Solution Fit (Weeks 1-2) - Interview 10-15 early adopters - Validate problem exists and is painful - Test if solution concept resonates - Pivot or persevere decision Phase 2: Product-Market Fit (Weeks 3-4) - Build smallest testable MVP - Get real users (not friends/family) - Measure key metrics - Iterate based on behavior, not opinions Phase 3: Business Model Fit (Ongoing) - Validate pricing and revenue model - Test channel effectiveness - Prove unit economics work - Scale what's validated **EXPERIMENT DESIGN** Every assumption needs a test: - Hypothesis: "I believe [assumption]" - Test: "To verify this, I will [experiment]" - Success: "And measure [metric]" - Timeframe: "In [days]" Common experiments: - Problem interviews (validate pain) - Landing page (test value prop + price) - Concierge MVP (manual delivery) - Wizard of Oz (fake automation) - Pre-orders (validate willingness to pay) **ITERATION RULES** Update canvas weekly based on: - Customer interview insights - Experiment results - Metric changes - Market feedback Pivot or Persevere Framework: - Validated hypothesis → Persevere, move to next risk - Invalidated hypothesis → Pivot, change canvas block - Unclear results → Redesign experiment, test again Take a deep breath and work on this problem step-by-step. </response_guidelines> <task_criteria> Create and validate a complete Lean Canvas that tests your riskiest assumptions before building. PROCESS: 1. Start with idea backstory (identify your biases) 2. Fill 9 blocks in 20 minutes (assumptions mode) 3. Rank assumptions by risk (what kills the business if wrong) 4. Design experiments for top 3 risks 5. Get out of building, run tests, collect data 6. Update canvas with validated learnings 7. Pivot or persevere weekly FOCUS ON: Early adopters not everyone, real problems not assumed, experiments not opinions, evidence over hope, speed over perfection, iteration weekly AVOID: Building before validation, "everyone" as customer segment, solutions before problems, vanity metrics,假 unfair advantages, falling in love with Plan A, optimizing unvalidated assumptions </task_criteria> <information_about_me> ● BUSINESS IDEA: [INSERT YOUR IDEA - WHAT YOU WANT TO BUILD] ● IDEA BACKSTORY: [INSERT WHY/HOW THIS IDEA CAME TO YOU] ● TARGET CUSTOMER HYPOTHESIS: [INSERT WHO YOU THINK NEEDS THIS] ● PROBLEM HYPOTHESIS: [INSERT WHAT PROBLEM YOU THINK THEY HAVE] ● CURRENT STAGE: [INSERT: IDEA/MVP BUILT/EARLY USERS/SCALING] </information_about_me> <response_format> <lean_canvas> **[CUSTOMER SEGMENTS]** Early Adopters: [Specific segment with characteristics] Who Pays: [Customer vs User if different] **[PROBLEM]** 1. [Top priority problem - most urgent/painful] 2. [Second problem] 3. [Third problem] Existing Alternatives: [How they solve this today] **[UNIQUE VALUE PROPOSITION]** [One sentence: Unlike X, we Y for Z] **[SOLUTION]** 1. [Feature addressing Problem 1] 2. [Feature addressing Problem 2] 3. [Feature addressing Problem 3] **[CHANNELS]** Path to Early Adopters: [Specific channels for learning + reach] **[REVENUE STREAMS]** Model: [Subscription/one-time/freemium/usage] Price: [Amount and reasoning] LTV: [Customer lifetime value if known] **[COST STRUCTURE]** CAC: [Customer acquisition cost] Operations: [Development/hosting/tools] People: [Team costs] **[KEY METRICS]** Primary: [Most important metric] Secondary: [Supporting metrics] **[UNFAIR ADVANTAGE]** [What can't be easily copied - or "TBD through execution"] </lean_canvas> <risk_assessment> **Riskiest Assumptions (Ranked):** 1. [Assumption] - Risk: High/Medium/Low 2. [Assumption] - Risk: High/Medium/Low 3. [Assumption] - Risk: High/Medium/Low **Why These Matter:** [Explain what breaks if these are wrong] </risk_assessment> <validation_plan> **Week 1-2: Problem-Solution Fit** Hypothesis: [What you're testing] Experiment: [How you'll test it] Success Metric: [What proves it right] Who: [10-15 early adopters to interview] **Week 3-4: Product-Market Fit** MVP: [Smallest testable version] Test: [How users will interact] Measure: [Key metric to track] Goal: [Number that shows traction] **Next Pivot/Persevere Decision:** [When and based on what data] </validation_plan> <next_actions> **This Week:** [Top 3 actions to move forward] **First Experiment:** [Specific test you can run in next 7 days] **Success Criteria:** [What validates you're on right track] </next_actions> </response_format>