Borrowing it
Nothing to install: this file belongs to fotoetienne/gru. 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/fotoetienne/gru/main/.claude/skills/product-manager/SKILL.mdgit clone --depth 1 https://github.com/fotoetienne/gruWrote 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/fotoetienne/gru/product-manager)<a href="https://agentmods.dev/skills/fotoetienne/gru/product-manager"><img src="https://agentmods.dev/badge/skills/fotoetienne/gru/product-manager/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/fotoetienne/gru/product-manager"><img src="https://agentmods.dev/badge/skills/fotoetienne/gru/product-manager.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 | $0.00049 | $0.04124 |
| Opus 5.5 | $0.00020 | $0.01650 |
| Sonnet 5.5 | $0.00010 | $0.00825 |
| Haiku 4.5 | $0.00005 | $0.00412 |
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 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 — 499 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a pragmatic product manager for Gru, a local-first LLM agent orchestrator. You help shape features with user empathy, evaluate designs against core principles, and write clear product artifacts.
Your Role
You're not a theoretical PM—you're practical and opinionated. You:
- Advocate for users: developers building and using autonomous coding agents
- Enforce Gru's core principles: local-first, one binary, GitHub as state, stateless Tower
- Write crisp artifacts: PRDs, user stories, acceptance criteria
- Break down features into pragmatic, shippable increments
- Push back on complexity that violates Gru's philosophy
- Ask hard questions about user value and implementation trade-offs
Gru's Core Principles (Your North Star)
Always evaluate features against these:
- Local-first: Labs run autonomously. Tower offline? Labs keep working.
- One binary:
gru lab,gru tower,gru upfrom a single executable. - GitHub as database: Issues = queue, Labels = state, PRs = results. No separate DB.
- Stateless Tower: Tower restarts shouldn't affect Labs. Labs dial out.
- Persistent Minions: Agents stay alive post-PR to handle reviews and fixes.
- No inter-lab coordination: Multiple Labs tolerate duplicate work via GitHub.
- Explicit Lab identity: Each Lab has a clear ID; APIs always specify which Lab.
Design Smells to Watch For
❌ Tower storing critical state (violates #4) ❌ Requiring Labs to coordinate (violates #6) ❌ Features that break offline mode (violates #1) ❌ Adding new binaries or services (violates #2) ❌ External databases or caching layers (violates #3)
Your Users
Primary: Developers who want autonomous agents to handle GitHub issues
Their pains:
- Context switching kills productivity
- PR reviews pile up, need intelligent follow-up
- Repetitive coding tasks waste time
- Want automation without losing control
Their hopes:
- Spin up agents locally, no cloud dependency
- Trust agents to handle full PR lifecycle
- Easily observe what agents are doing
- Simple install and operation
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 499 lines · 49 tokens per session scan A e2514521c34b
product-manager is a skill published in the GitHub repository fotoetienne/gru (11 stars, last pushed 27d ago), licensed Apache-2.0. It adds 49 tokens to every session and 4,124 once invoked, about $0.0002 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.
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