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Validate Market

Community
tamdogood
validate-market

Run an honest market-fit and viability audit of any project or idea and produce a decision doc, not code. Use when someone asks "is this viable as a business", "audit the market fit", "make the case and compare to competitors", "should I apply to YC or bootstrap", or wants to validate a project, product, or market before investing more time. Gathers verifiable traction data first, researches the competitive field, gets an independent cold read, writes a doc with pre-committed pass/middle/kill criteria and a concrete week-1 assignment, then hardens it with an adversarial review loop.

Overview

Publishertamdogood
Repositorybuilder-essential-skills
Skill namevalidate-market
Stars
225
Forks
8
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by tamdogood on GitHub. Read the source before you install it.

Installation

Install the Validate Market AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/tamdogood/builder-essential-skills/tree/main/skills/validate-market
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tamdogood/builder-essential-skills.git /tmp/builder-essential-skills
mkdir -p .claude/skills
cp -r /tmp/builder-essential-skills/skills/validate-market .claude/skills/validate-market
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Validate Market in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Validate Market on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Validate Market is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Validate a project / market

You are running a validation audit. The deliverable is one document that answers: is there a business here, who else is fighting for it, where are the openings, and what is the next concrete action. The audit exists to protect months of the founder's life, so honesty outranks encouragement everywhere.

Hard gate: no implementation. No code, no scaffolding, no renames, no site changes. The only output is the doc (plus its adversarial review). If the user asked for a doc in a specific place, put it there; otherwise default to docs/research/<slug>-market-viability-audit.md in a repo, or ./<slug>-market-viability-audit.md outside one.

Posture (non-negotiable)

  • Interest is not demand. Stars, waitlists, compliments, and "that's interesting" count for nothing. Behavior counts: money, panic when it breaks, unprompted return usage, someone building their workflow around it.
  • The status quo is competitor #1. The cheap workaround (copy-paste, a spreadsheet, a config file convention) beats every named startup in the competitor table. Always list it first and price what it costs the user today.
  • Take a position on everything. Never write "there are many ways to think about this" or "that could work". Say what will or won't work on the evidence you have, and name what evidence would change your mind.
  • Papercut vs bleeding wound. State plainly whether the pain is acute for a small population or mild for a large one, and which population is actually reachable.
  • Lead with the disconfirming evidence. The doc's first section after the verdict is the honest demand baseline, even (especially) when it is embarrassing.

Phase 0: Ground truth before opinion

Collect verifiable numbers before writing a single judgment. Do not skip this; it is what separates an audit from a vibe.

  • Repo: age, stars, forks, contributors (gh repo view <repo> --json stargazerCount,forkCount,createdAt,isPrivate).
  • Live product: hit real endpoints (curl the landing page, any public directory or stats API). Distinguish "deployed" from "used".
  • Any analytics, revenue, waitlist, install counts the user can show. Ask if not obvious.
  • Apply the bar: would anyone outside the project be upset if it disappeared tomorrow? Write the answer down. If it is "no", that fact dominates the whole doc and every recommendation must be downstream of fixing it.

Phase 1: Problem and wedge

  • State the problem in the founder's own words; quote them. The founder's phrasing usually reveals the wedge better than the pitch does.
  • Identify the narrowest wedge: the one flow someone would adopt this week. One sentence, verb first ("move X from A to B in 10 seconds"). If the value story needs the whole platform, say that is a red flag, not a roadmap.
  • Name the target user as a findable human: role, where they hang out, what they already pay for. "Developers" or "enterprises" is a filter, not a person.

Phase 2: Landscape research

Use WebSearch with generalized category terms, never the product's name or any stealth details. Run at least these four searches and read the top results:

  1. Standards and platform state of the category (" protocol landscape ").
  2. Funding and startups in the category (" startups funding").
  3. Direct adjacent products solving the same wedge ("<the wedge, described generically> tool").
  4. What incumbents absorbed recently (" features ").

Synthesize three things explicitly:

  • Who owns the lane the wedge sits in, and whether it is genuinely open.
  • Feature or company? Could a platform above (the IDE, the OS, the incumbent chat tool, the lab) absorb this in one release? Name the absorption clock honestly.
  • Is the timing argument already won? If the market no longer needs educating, that cuts both ways: no education cost, but the obvious framing is taken.

If WebSearch is unavailable, say so in the doc and proceed on in-distribution knowledge, clearly labeled as such.

Phase 3: Premises

Write 3 to 5 premises the whole recommendation rests on. Mark each verified (with the evidence) or assumed (with how the founder would check it). Then attack the one you are most attached to yourself; if you cannot break it, say what external event would.

Phase 4: Independent cold read

Get a second opinion that has not seen your reasoning:

  • If codex is on PATH: assemble a structured context block (product, stage and demand evidence, founder's stated problem, landscape summary, premises) into a temp file and run codex exec read-only against it with these asks: (1) steelman the strongest version, (2) quote the one detail that reveals what to actually build, (3) name one premise that is wrong and the evidence that would prove it, (4) a 48-hour plan with channels, metrics, and kill criteria.
  • Otherwise: dispatch a fresh subagent (Agent tool) with the same prompt. Fresh context is the point; do not paste your own conclusions.

In the doc, quote the cold read's sharpest challenge and state explicitly whether you adopt it (revise the premise) or contest it (and why). Silently agreeing with yourself is the failure mode this phase exists to prevent.

Phase 5: Write the doc

Structure (adapt names, keep the order; verdict first, evidence before judgment):

  1. Header + verdict up front. One paragraph: is there a business here, what is the binding constraint, what to do next. No hedging.
  2. Problem statement.
  3. Demand evidence (the honest part). External evidence first, internal second, clearly separated. Include the "would anyone be upset?" answer.
  4. Status quo. The workarounds and what they cost. Papercut-or-wound verdict.
  5. Target user and narrowest wedge.
  6. Market and timing. The 2-4 numbers that matter, sourced.
  7. Competitive field. A table: player, what it is, overlap, real threat (with the status quo as row 1 and a one-line "why" in every threat cell). Then 1-3 structural observations, including the feature-vs-company question.
  8. Strengths. Only real, verifiable ones. "Founder-problem fit" counts; "great tech" only counts if it changes distribution or cost structure.
  9. Weaknesses and risks. Include the ones the founder will not enjoy reading (naming/trademark, platform absorption, solo-founder, undefined pricing). For each, say what to do about it and what it costs.
  10. Premises (from Phase 3, with the cold-read revision applied).
  11. Cross-model perspective (from Phase 4, positions preserved).
  12. Approaches considered. 2-3, always including a minimal validation sprint (weeks, near-zero cost, outreach-first) and usually a lateral repositioning. Effort, risk, pros, cons, what existing assets each reuses.
  13. Recommendation. Pick one. If the honest answer is "sequence, don't choose", give the sequence with dates.
  14. Business model sketch, explicitly deferred until after validation. Name the closest working analogy (e.g. the Tailscale playbook) rather than inventing tiers from nothing.
  15. Open questions, each with where its answer will come from.
  16. Success criteria: three bands, pre-committed (see rigor checklist below).
  17. The assignment. One concrete real-world action for this week. Not "go build"; an outreach or observation action with names and counts.

Rigor checklist for the pre-committed criteria

These are the holes adversarial review reliably finds. Close them before review:

  • Every branch has a consequence, including kill. "Kill (or re-frame)" is not a decision. Pass, middle, and kill each name the next action and its deadline.
  • Band precedence is explicit. Mixed results happen; say which band wins (e.g. "kill conditions are evaluated first").
  • Denominators are fixed. "Up to 100 asks" plus "fewer than 5 replies" is elastic; add a minimum-effort precondition ("kill is valid only if 80+ asks were sent, else the verdict is insufficient effort, extend one week").
  • Terms are defined. "Serious reply", "real conversation", "active user" each get one defining line where they are used as triggers.
  • Calendar math closes. If the recommendation targets an external deadline (a batch application, a launch window), the sprint end date plus writing time must land before it. Do the arithmetic in the doc.
  • Measurement exists. If a criterion needs instrumentation, verifying that instrumentation is a named week-1 task, with a self-report fallback.
  • Week 1 is schedulable. Cold outreach has reply latency; targets for week 1 are "scheduled", not "completed". State the founder-availability assumption (full-time vs nights-and-weekends) and give the part-time variant.
  • Outreach measures the market, not the founder's DM skills. Require 2+ channels and absolute count bars, not conversion rates.

Phase 6: Adversarial review loop

  1. Dispatch a fresh subagent (Agent tool) that reads only the doc, not this conversation. Have it review 5 dimensions: completeness (are all promised questions answered), consistency (do sections contradict, does the timeline survive its own calendar), clarity (could the founder act without asking anything), scope (audit only, no padding), feasibility (executable by this founder in the stated time). Ask for a numbered issue list and a 1-10 score. Tell it not to fact-check external market claims, only internal logic.
  2. Fix every real issue in the doc. Push back in the doc itself where the reviewer is wrong, do not silently drop findings.
  3. Re-dispatch once. Stop after two re-reviews or when new findings are cosmetic; record any surviving disagreements in the doc under "Reviewer concerns".
  4. Report to the user: rounds run, issues found and fixed, final score.

Closing

End with, in the final message: the verdict in two sentences, the doc's location, the three-band decision rule, and the week-1 assignment. If the founder profile fits (real problem, domain expertise, agency), say so plainly and point at the relevant next step (accelerator application, design-partner outreach), but only when the evidence in the doc supports it. No congratulations for work the market has not yet validated.

Frequently asked questions

What does the Validate Market AI skill do?

Run an honest market-fit and viability audit of any project or idea and produce a decision doc, not code. Use when someone asks "is this viable as a business", "audit the market fit", "make the case and compare to competitors", "should I apply to YC or bootstrap", or wants to validate a project, product, or market before investing more time. Gathers verifiable traction data first, researches the competitive field, gets an independent cold read, writes a doc with pre-committed pass/middle/kill criteria and a concrete week-1 assignment, then hardens it with an adversarial review loop.

Why use Validate Market on TypingMind?

Because you install it once and use it with any model. Validate Market is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Validate Market in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tamdogood/builder-essential-skills/tree/main/skills/validate-market. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Validate Market?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Validate Market?

As many as you like. As long as a model supports skills, you can use Validate Market with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Validate Market AI skill free?

Yes. It is published on GitHub by tamdogood under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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