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 coalesce-labs/catalyst --skill review-securitygit clone --depth 1 https://github.com/coalesce-labs/catalystWrote 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/coalesce-labs/catalyst/review-security)<a href="https://agentmods.dev/skills/coalesce-labs/catalyst/review-security"><img src="https://agentmods.dev/badge/skills/coalesce-labs/catalyst/review-security/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/coalesce-labs/catalyst/review-security"><img src="https://agentmods.dev/badge/skills/coalesce-labs/catalyst/review-security.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 | $0.00217 | $0.01484 |
| Opus 5.5 | $0.00087 | $0.00594 |
| Sonnet 5.5 | $0.00043 | $0.00297 |
| Haiku 4.5 | $0.00022 | $0.00148 |
Grade A, and why
review-security 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 1mo 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
5 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.
- 1mo ago First seen · 61 lines · 217 tokens per session scan A f509e83455b1
review-security is a skill published in the GitHub repository coalesce-labs/catalyst (20 stars, last pushed 17d ago), with no licence file. It adds 217 tokens to every session and 1,484 once invoked, about $0.0009 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 2026-09-16.
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Experimental declared review depth for linked-intent development. Use when a LID project's instruction file declares a review depth in prose (e.g. "Review depth - I review through LLD; below that, consolidate to one review") or the user asks to batch phase reviews, consolidate stops, or let go below a phase depth.…
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add
Create a new Clawness rule from a natural language description. Describe what you want enforced and this will generate the YAML rule file with proper tags, triggers, and examples.
review
Run an adversarial code review on staged changes or a specific file. Spawns the code-critic agent to find bugs, performance issues, and missed edge cases. Use before merging PRs or committing.
memory-to-skill
Turn workflows from your MemSearch memory into reusable skills. Use when the user asks to make/create/extract/distill a skill from what they just did or from past work, review skill candidates, install a distilled skill, or 'turn this into a skill'. Manages MemSearch procedural-memory candidates under…