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.
npx skills add adidacta/pmf-detective --skill plan-pmf-modegit clone --depth 1 https://github.com/adidacta/pmf-detectiveWrote 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.
[](https://agentmods.dev/skills/adidacta/pmf-detective/plan-pmf-mode)<a href="https://agentmods.dev/skills/adidacta/pmf-detective/plan-pmf-mode"><img src="https://agentmods.dev/badge/skills/adidacta/pmf-detective/plan-pmf-mode/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/adidacta/pmf-detective/plan-pmf-mode"><img src="https://agentmods.dev/badge/skills/adidacta/pmf-detective/plan-pmf-mode.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.02811 |
| Opus 5.5 | $0.00013 | $0.01124 |
| Sonnet 5.5 | $0.00007 | $0.00562 |
| Haiku 4.5 | $0.00003 | $0.00281 |
Grade A, and why
plan-pmf-mode 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PMF Plan Mode - Full Context Builder
You guide product builders through creating their complete PMF context layer in sequence: ICP → Value Proposition → MVP PRD → Validation Plan → Execute.
Important: The first 3 sections are assumptions. The validation plan decides how to test them, then routes to the right execution skill.
How This Skill Works
This skill orchestrates the full flow by following each builder's process in sequence. Each builder skill (icp-builder, value-prop-builder, etc.) defines its own phases and questions — follow their SKILL.md instructions directly. This skill provides the sequencing, transitions, and progress tracking between sections.
Your Role
- Walk users through all sections in order
- For each section, follow the corresponding builder skill's full flow
- One question at a time
- Save each section when complete
- Move to next section automatically
The Flow
┌───────────────────────────────────────────────────────────────┐
│ PMF CONTEXT BUILDER │
├───────────────────────────────────────────────────────────────┤
│ │
│ Let's build your PMF context layer. │
│ │
│ We'll work through 4 steps + execution: │
│ 1. ICP — Who your customer is (assumption) │
│ 2. Value Proposition — Why they should care (assumption) │
│ 3. MVP PRD — What to build & why (assumption) │
│ 4. Validation Plan — How you'll test these assumptions │
│ │ │
│ ├─→ Landing Page (if validating with signups) │
│ ├─→ Outreach + Mom Test (if validating with talks) │
│ └─→ Build with BMAD (if validating by building) │
│ │
│ Each section becomes a reference file Claude uses │
│ when building anything for your product. │
│ │
└───────────────────────────────────────────────────────────────┘
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.
- 2mo ago First seen · 276 lines · 33 tokens per session scan A e2db89f72fc9
plan-pmf-mode is a skill published in the GitHub repository adidacta/pmf-detective (18 stars, last pushed 28d ago), licensed MIT. It adds 33 tokens to every session and 2,811 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
plan-pmf-mode compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| plan-pmf-modeadidacta/pmf-detective | Skill | 18 | 28d ago | MIT | A | 33 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |