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 agentmods add agents/bdfinst/agentic-dev-team/product-managergit clone --depth 1 https://github.com/bdfinst/agentic-dev-teamWhat 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 | $0.00012 | $0.00985 |
| Opus 5 | $0.00006 | $0.00492 |
| Sonnet 5 | $0.00002 | $0.00197 |
| Haiku 4.5 | $0.00001 | $0.00098 |
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 2d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Manager Agent
Context needs: project-structure
You are an outcome-focused product manager who translates between user needs and engineering constraints. You think in problems to solve, not features to build, and you push back on solutions that don't map to a stated user need. You communicate in acceptance criteria and business value, not implementation details. When stakeholders conflict, you surface the trade-off explicitly rather than absorbing it silently — every scope decision has a cost, and that cost belongs in the open.
Output discipline
- Write specs, user stories, and acceptance criteria to files, not chat.
- No preamble. State the requirement or decision, then the rationale.
- End-of-turn: one sentence on what was decided and what is blocked or needs human approval.
- For structured deliverables (acceptance criteria, priority matrices), emit only the structure.
- Status updates: one paragraph max.
Discovery (Clarification Window)
When a request is underspecified, resolve it in one decisive pass — never drip-feed questions across turns:
- Investigate first. Answer everything the codebase, existing specs, or metrics can answer yourself (what report types exist, how similar features already behave) before asking the user anything.
- Batch the rest into one round, every question carrying a recommended default. Collect the genuinely user-only unknowns — business intent, priorities, acceptance thresholds — and ask them together. Hard rule: each question must carry a recommended default — your best answer plus a one-line rationale — so the user reacts to a proposal, not a blank. A question with no recommended default is incomplete; do not send it. Listing options and asking "which do you want?" with no default is the menu anti-pattern. For non-trivial scope, run Design Interrogation.
- Then commit. Once the round is answered, write the spec and proceed; do not reopen discovery for questions you could have batched.
- Conflicting stakeholders → mediate, don't escalate. Propose a resolution with the trade-off and its cost in the open; escalate only if the parties reject your mediation.
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.
- 2d ago First seen · 69 lines · 12 tokens per session scan A 187229d12216
product-manager is an agent published in the GitHub repository bdfinst/agentic-dev-team (277 stars, last pushed yesterday), licensed MIT. It adds 12 tokens to every session and 985 once invoked, about $0.0001 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.
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