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 desikai-lab/Marrow --skill pr-reviewgit clone --depth 1 https://github.com/desikai-lab/MarrowWrote 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/desikai-lab/marrow/pr-review)<a href="https://agentmods.dev/skills/desikai-lab/marrow/pr-review"><img src="https://agentmods.dev/badge/skills/desikai-lab/marrow/pr-review/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/desikai-lab/marrow/pr-review"><img src="https://agentmods.dev/badge/skills/desikai-lab/marrow/pr-review.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 | $0.00059 | $0.00308 |
| Opus 5 | $0.00030 | $0.00154 |
| Sonnet 5 | $0.00012 | $0.00062 |
| Haiku 4.5 | $0.00006 | $0.00031 |
Grade A, and why
pr-review 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 9d 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.
What it actually says
PR Review Checklist
Use this playbook whenever opening or reviewing a pull request.
Before opening a PR
- Run
ruff check .— zero violations required. - Run the full test suite:
pytest tests/— all passing, no regressions. - Confirm branch is named per ADR-0035 convention (
feature/,td/,hotfix/). - Verify branch is off latest
main(git log --oneline main..HEAD).
PR description
- Title: one-line summary matching the task title.
- Body: link to the task ID and feature bundle path.
- Note any deliberate deviations from the architecture doc.
After merge
- Delete the feature branch.
- Update
session.md: setnext_agent_role: Discovery Agentand write SESSION EXIT. - Mark the task
doneviacomplete_tasks.
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.
- 9d ago First seen · 40 lines · 59 tokens per session scan A 2cf6047e2698
pr-review is a skill published in the GitHub repository desikai-lab/Marrow (5 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 308 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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