Borrowing it
Nothing to install: this file belongs to Avyayalaya/pm-skills-arsenal. 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/Avyayalaya/pm-skills-arsenal/main/AGENTS.mdgit clone --depth 1 https://github.com/Avyayalaya/pm-skills-arsenalWrote 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/avyayalaya/pm-skills-arsenal/agents-md)<a href="https://agentmods.dev/instructions/avyayalaya/pm-skills-arsenal/agents-md"><img src="https://agentmods.dev/badge/instructions/avyayalaya/pm-skills-arsenal/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/avyayalaya/pm-skills-arsenal/agents-md"><img src="https://agentmods.dev/badge/instructions/avyayalaya/pm-skills-arsenal/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 | $0.01579 | $0.01579 |
| Opus 5 | $0.00790 | $0.00790 |
| Sonnet 5 | $0.00316 | $0.00316 |
| Haiku 4.5 | $0.00158 | $0.00158 |
Grade A, and why
pm-skills-arsenal 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 12d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Machine-readable capability manifest for AI agents and orchestrators. Deploy this file to the root of any public repository to make its capabilities discoverable.
System
Name: PM Skills Arsenal
Author: Parth Sangani
Description: 12 PM skills encoding domain expertise as loadable context for AI agents. Each skill is 1,000-1,300 lines of methodology, frameworks, and failure modes — not prompt templates.
Benchmark (self-administered): 98/105 on a self-authored 7-dimension rubric, scored by the same author who wrote the skills. Methodology + 15 raw outputs at benchmark/ for independent re-scoring. Read this score with that lens.
Compliance: All 12 skills pass validate_skills.py discoverability audit (capability_summary + input_schema + output_schema + example_invocation + description all present). Latest audit: 2026-04-23.
Skills
| Skill | Domain | Frameworks | Lines | Version |
|---|---|---|---|---|
| competitive-market-analysis | Strategy | 7 Powers, Aggregation Theory, JTBD, Wardley Mapping, Christensen Disruption | 1,300 | 1.3.0 |
| discovery-research | Research | Evidence synthesis, interview analysis, hypothesis building | 1,100 | 1.3.0 |
| problem-framing | Analysis | Problem Definition Canvas, 5 Whys, JTBD, Opportunity Sizing, ICE/RICE | 1,100 | 1.3.0 |
| specification-writing | Definition | Outcome-first methodology, acceptance criteria taxonomy, scope boundary protocol | 1,100 | 1.3.0 |
| metric-design-experimentation | Measurement | NSM rubrics, Goodhart countermeasures, A/B design, retention cohorts | 1,300 | 1.3.0 |
| product-strategy | Strategy | Vision Cascade, Bet-Sizing, Option-Value Sequencing, Tension Surfacing | 1,100 | 2.0.0 |
| go-to-market-strategy | Strategy | Market Entry Thesis, Channel Unit Economics, Launch Gating, Dunford Positioning | 1,200 | 2.0.0 |
| pricing-packaging | Strategy | Model Selection, Van Westendorp, Good/Better/Best, Revenue Impact | 1,200 | 2.0.0 |
| executive-writing | Communication | Minto/SCR, Audience Calibration, Decision Architecture, Zero-Jargon Compression | 1,200 | 2.0.0 |
| narrative-building | Communication | Narrative Arc, April Dunford Positioning, Why Now, Audience Adaptation | 1,200 | 2.0.0 |
| multi-channel-publishing | Communication | Channel Taxonomy, Compression Methodology, Hook Adaptation, Evidence Density | 1,100 | 2.0.0 |
| stakeholder-alignment | Influence | Power-Interest-Position, Coalition Analysis, Decision Archaeology, Alignment Sequencing | 1,200 | 2.0.0 |
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.
- 12d ago First seen · 103 lines · 1,579 tokens per session scan A adbc73adda60
pm-skills-arsenal AGENTS.md is an instructions file published in the GitHub repository Avyayalaya/pm-skills-arsenal (6 stars, last pushed 3mo ago), licensed MIT. It adds 1,579 tokens to every session, about $0.0079 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.
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).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
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.
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).