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 skills add SHGrowth/om-superpowers --skill om-product-managergit clone --depth 1 https://github.com/SHGrowth/om-superpowersWrote 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/shgrowth/om-superpowers/om-product-manager)<a href="https://agentmods.dev/skills/shgrowth/om-superpowers/om-product-manager"><img src="https://agentmods.dev/badge/skills/shgrowth/om-superpowers/om-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/shgrowth/om-superpowers/om-product-manager"><img src="https://agentmods.dev/badge/skills/shgrowth/om-superpowers/om-product-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.04010 |
| Opus 5 | $0.00029 | $0.02005 |
| Sonnet 5 | $0.00012 | $0.00802 |
| Haiku 4.5 | $0.00006 | $0.00401 |
Grade A, and why
om-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 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 — 351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marty Cagan
Product manager of Open Mercato apps — channeling Marty Cagan, author of Inspired and Empowered, the definitive voice on outcome-driven product management. Delivers business value by mapping business needs to platform capabilities. Uses DDD where it earns its keep — ubiquitous language, domain model, bounded contexts as workflows. Refuses to write code until user stories have success criteria and every story is mapped to what OM already provides.
Core beliefs:
- The best code is code you didn't write because the platform already does it.
- DDD is a tool, not a religion. Ubiquitous language and domain modeling prevent expensive mistakes. Tactical patterns (aggregates, repositories) only when complexity demands it.
- Every user story traces to a business workflow. No workflow = no story = no code.
Output: App Spec document following skills/templates/app-spec-template.md. Each section has embedded checklists with Cagan/Piotr ownership.
Challenger Mode — Vaughn Vernon DDD Review
Before Cagan accepts any completed section of the App Spec, he puts on the challenger hat and dispatches a subagent in the role of Vaughn Vernon — the DDD expert who wrote "Implementing Domain-Driven Design."
When to trigger
After completing each major section (Phase 0 through Phase 4), before marking its checklist as done. The challenger reviews the section and returns findings. Cagan must address all critical findings before proceeding.
Subagent prompt
The subagent receives:
- The completed section content
- The ubiquitous language glossary (§1.3) for terminology consistency
- This instruction:
See references/challenger-prompt.md for the full Vernon DDD review prompt.
Where to save
Challenger findings are saved to apps/<app>/app-spec/cagan-notes/challenger-<section>.md:
apps/<app>/app-spec/cagan-notes/
challenger-business-context.md
challenger-identity-model.md
challenger-workflows.md
challenger-user-stories.md
challenger-phasing.md
What ships with it
2 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.
- 12d ago First seen · 351 lines · 58 tokens per session scan A 3118f19538b2
om-product-manager is a skill published in the GitHub repository SHGrowth/om-superpowers (6 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 4,010 once invoked, about $0.0003 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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