measure-pmf

Assess Product-Market Fit signals by segment using supplied Sean Ellis survey responses, retention/cohort evidence, reference-customer evidence, organic pull…

Skill by ThorStarlord

IndexedMIT

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Assess Product-Market Fit signals by segment using supplied Sean Ellis survey responses, retention/cohort evidence, reference-customer evidence, organic pull, qualitative feedback, and unit-economics evidence. Use for product_measurement responsibility and produce pmf_report. A measured PMF classification requires actual preserved evidence; without sufficient observations return not_measured or insufficient_evidence rather than inferring PMF from framework thresholds or growth anecdotes.

Use cases: marketing, research

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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codeload.github.com · found in install command

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~/.claude/skills/measure-pmf

What's inside

Skill name: measure-pmf
Description: Assess Product-Market Fit signals by segment using supplied Sean Ellis survey responses, retention/cohort evidence, reference-customer evidence, organic pull, qualitative feedback, and unit-economics evidence. Use for product_measurement responsibility and produce pmf_report. A measured PMF classification requires actual preserved evidence; without sufficient observations return not_measured or insufficient_evidence rather than inferring PMF from framework thresholds or growth anecdotes.
License: MIT
Instructions: 25 lines in SKILL.md · view on GitHub

Files (2)

SKILL.md
contract.md · references/

SKILL.md (first lines)

# Measure PMF

Satisfy a `product_measurement` responsibility by producing `pmf_report`.

## Inputs

Require product/segment context and an inventory of actual available evidence. Sean Ellis survey, retention, NPS, organic growth, reference-customer, and unit-economics evidence are optional inputs individually; absence must stay visible.

## Procedure

1. Read [references/contract.md](references/contract.md).
2. Scope the assessment to a named segment and time window.
3. Inventory evidence sources before applying any framework.
4. Compute Sean Ellis share only from supplied response counts; preserve sample size and eligibility caveats.
5. Describe retention/cohort, referral/organic, qualitative, and economics signals only from supplied evidence.
6. Distinguish contradictory signals instead of averaging them into false certainty.
7. Classify `measured` only when the minimum evidence required by the chosen assessment method exists; otherwise use `partial` or `not_measured`.
8. Recommend next evidence/action without claiming scale readiness or PMF as fact beyond the observations.
9. Return `pmf_report` and control.

## Boundary

`40% heuristic != universal PMF proof`, `growth != PMF`, `NPS != PMF`, and `PMF assessment != authority to scale spend or fundraising claims`.

From ThorStarlord/sensemaking-skills, MIT.

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Forks: 0
Open issues: 7
Last commit (this folder): Sep 10, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License: MIT
Repository: github.com/ThorStarlord/sensemaking-skills
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: GitHub github-graphql

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measure-pmf skill. Agent Mart. https://agentmart.dev/skills/thorstarlord-measure-pmf (last updated 2026-10-24)