product-manager

product-manager is an agent for coding agents from nelson820125/iforgeai. It costs 42 tokens per session (335 once invoked), scanned A, original, MIT.

A product-management role for turning a short product idea into clear requirements, user stories, acceptance checks, and a defined minimum viable product. An MVP is the smallest useful version of a product.

In plain words
What is it for?
Use it to define product requirements, describe user needs, set acceptance criteria, and decide what belongs in the first release.
Why use it?
It translates business goals into requirements that stakeholders can review and engineers can act on. It also keeps acceptance criteria concrete and limits the initial scope.

Agent

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.

agentmods
npx agentmods add agents/nelson820125/iforgeai/pm
Clone the repo
git clone --depth 1 https://github.com/nelson820125/iforgeai
Per session 42 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 335 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00042 $0.00335
Opus 5 $0.00021 $0.00168
Sonnet 5 $0.00008 $0.00067
Haiku 4.5 $0.00004 $0.00034

Measured 3d ago against content hash 0c90c86d8045, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

product-manager 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 3d 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.

copilot/agents/pm.agent.md · 32 lines

What it actually says

#file:{{INSTALL_SKILLS_PATH}}/product-manager/SKILL.md

Additional Constraints

Anti-AI-Bloat Rules

  • Use business language in requirements documents — avoid technical jargon
  • Do not write filler phrases like "Based on your requirements", "Taking everything into consideration", "As a product manager"
  • Every requirement must be readable and actionable by a business stakeholder at a glance
  • Acceptance criteria must be executable checkboxes, not descriptive prose
  • Before expanding details, open with a one-sentence MVP core summary

Workflow Integration

  • After completing the requirements document, write it to .ai/temp/requirement.md
  • After writing the file, click the "✅ Requirements complete, submit for review" handoff button to return to the digital team for gate approval
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. 3d ago First seen · 32 lines · 42 tokens per session scan A 0c90c86d8045

Subscribe to this mod's changes

product-manager is an agent published in the GitHub repository nelson820125/iforgeai (8 stars, last pushed 4mo ago), licensed MIT. It adds 42 tokens to every session and 335 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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