validating-product-market-fit

validating-product-market-fit is a skill for Claude Code from qte77/claude-code-plugins. It costs 42 tokens per session (806 once invoked), scanned A, original, Apache-2.0.

A product-market-fit review step for a go-to-market process. Product-market fit means evidence that a product solves an important problem for a reachable group of buyers.

In plain words
What is it for?
Use it to score problem severity, solution fit, market timing, and other factors after completing market analysis.
Why use it?
It turns earlier market research into a scored assessment, evidence table, and list of risks instead of leaving the decision to guesswork.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions Claude Code.

Part of the market-research plugin — 8 skills shipped together

Good fit Use it to score problem severity, solution fit, market timing, and other factors after completing market analysis.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/qte77/claude-code-plugins/validating-product-market-fit
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add qte77/claude-code-plugins --skill validating-product-market-fit
Clone the repo
git clone --depth 1 https://github.com/qte77/claude-code-plugins

Made for: Claude Code.

Or install market-research, the plugin that ships this one along with the rest of its 8 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for validating-product-market-fit

README.md
[![agentmods](https://agentmods.dev/badge/skills/qte77/claude-code-plugins/validating-product-market-fit.svg)](https://agentmods.dev/skills/qte77/claude-code-plugins/validating-product-market-fit)
Your own site
<a href="https://agentmods.dev/skills/qte77/claude-code-plugins/validating-product-market-fit"><img src="https://agentmods.dev/badge/skills/qte77/claude-code-plugins/validating-product-market-fit.svg" alt="Measured on agentmods" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 806 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00042 $0.00806
Opus 5 $0.00021 $0.00403
Sonnet 5 $0.00008 $0.00161
Haiku 4.5 $0.00004 $0.00081

Measured 6d ago against content hash d073cd372ddf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

validating-product-market-fit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/market-research/skills/validating-product-market-fit/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Validating Product-Market Fit (Phase 2)

Target: $ARGUMENTS

Phase 2 of the GTM pipeline. Depends on Phase 1B. Scores PMF across multiple dimensions using evidence from prior phases.

Mode Awareness

Read config/mode.md before starting:

  • concise — Overall PMF score + top 3 evidence points + top 2 risks
  • detailed — Full per-dimension scoring, evidence matrix, risk register with mitigations
  • conservative — Weight negative evidence heavily; set high evidence bar
  • ambitious — Weight leading indicators and analogous market signals; accept proxy evidence

Inputs

  • results/phase-1b/market-analysis.md — Market sizing and buyer personas
  • results/phase-0/capability-profile.md — Technical capabilities
  • results/phase-1a/competitor-map.md — Competitive context
  • config/validation_criteria.md — Phase 2 quality gates
  • config/mode.md — Style and approach settings

PMF Scoring Dimensions

Score each dimension 1-10, then compute weighted average:

Dimension Weight Description
Problem severity 25% How painful is the problem for buyers?
Solution fit 25% How well does the product solve it?
Market timing 20% Is the market ready?
Competitive moat 15% Can differentiation be sustained?
Distribution path 15% Is there a clear route to customers?

Workflow

  1. Read all Phase 0, 1A, 1B outputs
  2. Score each dimension with evidence justification
  3. Compute weighted PMF score (0-10)
  4. Identify PMF risks — What would invalidate each dimension?
  5. Propose mitigations for top risks
  6. Validate against criteria — Check config/validation_criteria.md Phase 2 gates

Output

Write to results/phase-2/:

pmf-assessment.md

# Product-Market Fit Assessment

## PMF Score: [X.X] / 10

## Dimension Scores

| Dimension | Score | Evidence |
|-----------|-------|----------|
| Problem severity | [X]/10 | [evidence] |
| Solution fit | [X]/10 | [evidence] |
| Market timing | [X]/10 | [evidence] |
| Competitive moat | [X]/10 | [evidence] |
| Distribution path | [X]/10 | [evidence] |

## Evidence For PMF
- [evidence point] — Source: [phase output or URL]

## Evidence Against PMF
- [counter-evidence] — Source: [phase output or URL]

## PMF Risk Register

| Risk | Likelihood | Impact | Mitigation |
|------|-----------|--------|------------|
| [risk] | H/M/L | H/M/L | [approach] |

## Recommendation
[Proceed to GTM / Iterate on product / Pivot hypothesis]

Read the full file on GitHub · 97 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 97 lines · 42 tokens per session scan A d073cd372ddf

Subscribe to this mod's changes

validating-product-market-fit is a skill published in the GitHub repository qte77/claude-code-plugins (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 42 tokens to every session and 806 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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