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 jassics/awesome-claude-security --skill safety-evaluationgit clone --depth 1 https://github.com/jassics/awesome-claude-securityWrote 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/jassics/awesome-claude-security/safety-evaluation)<a href="https://agentmods.dev/skills/jassics/awesome-claude-security/safety-evaluation"><img src="https://agentmods.dev/badge/skills/jassics/awesome-claude-security/safety-evaluation/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/jassics/awesome-claude-security/safety-evaluation"><img src="https://agentmods.dev/badge/skills/jassics/awesome-claude-security/safety-evaluation.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 | $0.00071 | $0.00653 |
| Opus 5.5 | $0.00028 | $0.00261 |
| Sonnet 5.5 | $0.00014 | $0.00131 |
| Haiku 4.5 | $0.00007 | $0.00065 |
Grade A, and why
safety-evaluation 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 2mo 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
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 2mo ago First seen · 57 lines · 71 tokens per session scan A f2df721a0e10
safety-evaluation is a skill published in the GitHub repository jassics/awesome-claude-security (10 stars, last pushed 2mo ago), licensed GPL-3.0. It adds 71 tokens to every session and 653 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
goal-test
A local experiment for testing a goal command that keeps an AI coding session working until a stated condition is judged complete. It uses a separate language model to evaluate the conversation after each assistant turn.
prompt-testing
Use when comparing two prompt variants, defining quality/efficiency/robustness metrics, or deciding whether to adopt a challenger prompt over a baseline.
mutation-test
Mutation testing with two engines. Uses the project's NATIVE mutation runner (StrykerJS / Infection / mutmut / PIT / cargo-mutants) when one is configured — installing it on explicit consent when it is not — for a reproducible, comparable score; and an LLM-guided engine for the mutation classes native mutators cannot…
wicked-garden-data-engineer
ETL pipeline design, data quality assessment, schema validation, and performance optimization as a delegated worker skill. Use when: designing or reviewing ETL/ELT pipelines, assessing dataset quality (completeness, uniqueness, validity, consistency, timeliness), validating data against schemas, optimizing…
wicked-garden-data
Data engineering, analysis, and ML toolkit. One skill, routed sub-actions: analyze (interactive EDA on a CSV/Excel/data file), profile / validate / quality (schema-level data engineering ops), ml review / ml pipeline (model review + training-pipeline design), pipeline design / pipeline review (ETL architecture), and…
evals:hill-climb
Hill-climb a skill, agent, rule, or CLAUDE.md against its eval suite. Use when changing one to raise an eval score, when building or readying the suite a climb runs on, when judging whether a score change beat noise, or when testing whether an instruction still earns its tokens.