Borrowing it
Nothing to install: this file belongs to product-on-purpose/pm-skills. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/product-on-purpose/pm-skills/main/AGENTS.mdgit clone --depth 1 https://github.com/product-on-purpose/pm-skillsWrote 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/instructions/product-on-purpose/pm-skills/agents-md)<a href="https://agentmods.dev/instructions/product-on-purpose/pm-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/product-on-purpose/pm-skills/agents-md/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/instructions/product-on-purpose/pm-skills/agents-md"><img src="https://agentmods.dev/badge/instructions/product-on-purpose/pm-skills/agents-md.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 | $0.08400 | $0.08400 |
| Opus 5 | $0.04200 | $0.04200 |
| Sonnet 5 | $0.01680 | $0.01680 |
| Haiku 4.5 | $0.00840 | $0.00840 |
Grade A, and why
pm-skills AGENTS.md 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 10d 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 — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM-Skills
Open source Product Management skills for AI agents
This repository contains professional PM skills organized by the Triple Diamond framework plus foundation capabilities. Each skill helps AI agents produce high-quality PM artifacts.
Skills
Foundation Classification
build-risk-review
Path: skills/foundation-build-risk-review/SKILL.md
Runs a fast pre-build risk review on a product idea, feature request, or scope change, naming the single assumption most likely to make it fail and returning a clear verdict (build small, validate first, pivot first, or don't build yet) with a no-code validation step. Use before committing build effort, when triaging whether to honor a feature request, or when deciding whether to expand scope, ahead of writing a PRD. For a launched product's pivot-or-persevere decision, use iterate-pivot-decision instead.
lean-canvas
Path: skills/foundation-lean-canvas/SKILL.md
Produces a one-page lean canvas across nine interlocking blocks (problem, customer, UVP, solution, channels, revenue, cost, metrics, unfair advantage) with optional inline HTML and SVG visual rendering. Use when framing a new product thesis, stress-testing an existing strategy, comparing strategic options side-by-side, or aligning a team on business-model assumptions. Works as a strategic hub that cross-links to deeper PM skills without duplicating them.
meeting-agenda
Path: skills/foundation-meeting-agenda/SKILL.md
Produces an attendee-facing agenda that sets what will be discussed, who owns each topic, and how time will be spent. Supports ten meeting type variants (standup, planning, review, decision-making, brainstorm, 1-on-1, stakeholder-review, project-kickoff, working-session, exec-briefing). Emits a shareable summary suitable for Slack or email plus a full agenda with time-boxed topics, type tags, owners, attendee prep, and logistics.
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.
- 10d ago First seen · 475 lines · 8,400 tokens per session scan A ef27274cf67b
pm-skills AGENTS.md is an instructions file published in the GitHub repository product-on-purpose/pm-skills (657 stars, last pushed today), licensed Apache-2.0. It adds 8,400 tokens to every session, about $0.0420 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 2026-08-30.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.