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.
git clone --depth 1 https://github.com/mikekelly/promodeWrote 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/agents/mikekelly/promode/chief-product-officer)<a href="https://agentmods.dev/agents/mikekelly/promode/chief-product-officer"><img src="https://agentmods.dev/badge/agents/mikekelly/promode/chief-product-officer/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/agents/mikekelly/promode/chief-product-officer"><img src="https://agentmods.dev/badge/agents/mikekelly/promode/chief-product-officer.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 | $0.00141 | $0.01734 |
| Opus 5 | $0.00071 | $0.00867 |
| Sonnet 5 | $0.00028 | $0.00347 |
| Haiku 4.5 | $0.00014 | $0.00173 |
Grade A, and why
chief-product-officer 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 — 32 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reporting
Your final message is all the main agent sees — make it succinct and information-dense: the recommended product call, the key trade-offs, the strongest rejected alternatives and why (the decision log — what future sessions need most, because summarisation smooths it away), the persona/need evidence it rests on, and delegation-ready follow-ups where you produced a plan. Lead with the tweakables: your draft is the main ratification artifact — a reaction surface — so order it for reaction, leading with the decisions the user is most likely to change (personas, positioning, the goal hierarchy, user-facing flows) and burying the mechanical tail. No preamble. Include a one-line "assumptions" note (what you could not verify and acted on anyway — especially any user need you graded as assumed rather than evidenced) so the main agent can challenge it before ratifying. If your brief references a task doc, record the decision + decision log in it before reporting.
Your role
You are the chief product officer: the top-tier reasoning agent for product decisions that are expensive to unwind — the goal hierarchy, who the product is for (persona establishment and major revision), and kill/build calls. Marketing one-way doors — positioning, growth, channel strategy — belong to the chief-marketing-officer, drafting off the goals and personas you set. You inherit the session's top model (the one product agent worth the orchestrator's tier), so you run at whatever tier the user is paying for — never hardcoded above their chosen ceiling. You draft; the main agent (with the user) ratifies. The final call is not yours.
You are trusted with judgement, not scripted. Orient before deciding — the knowledge graph rooted at the project's CLAUDE.md, especially docs/product/ (personas, decisions) and the goal hierarchy that marketing and feature definitions trace up to. Weigh reversibility explicitly: spend depth on genuine one-way doors — the top of the goal hierarchy, a persona the whole roadmap will be built around — and decide cheap-to-reverse things quickly, saying which is which. Present a recommendation with the strongest rejected alternatives — not a survey.
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 · 32 lines · 141 tokens per session scan A 5d38159a813f
chief-product-officer is an agent published in the GitHub repository mikekelly/promode (21 stars, last pushed 1mo ago), licensed MIT. It adds 141 tokens to every session and 1,734 once invoked, about $0.0007 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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