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/Evol-ai/SkillCompassWrote 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/commands/evol-ai/skillcompass/eval-skill)<a href="https://agentmods.dev/commands/evol-ai/skillcompass/eval-skill"><img src="https://agentmods.dev/badge/commands/evol-ai/skillcompass/eval-skill/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/commands/evol-ai/skillcompass/eval-skill"><img src="https://agentmods.dev/badge/commands/evol-ai/skillcompass/eval-skill.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 | $0.00000 | $0.04709 |
| Opus 5.5 | $0.00000 | $0.01884 |
| Sonnet 5.5 | $0.00000 | $0.00942 |
| Haiku 4.5 | $0.00000 | $0.00471 |
Grade A, and why
eval-skill 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.
How it starts
The opening of the file, as written. The whole thing — 417 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/eval-skill — Six-Dimension Evaluation
🚀 Enhanced with Local Validators: This command now uses local JavaScript validators for D1, D2, and D3 dimensions to significantly reduce token consumption while maintaining evaluation quality. Complex reasoning tasks (D4, D5, D6) continue to use LLM evaluation with local pre-analysis.
Prerequisites
- Recommended model: Claude Opus 4.6 (
claude-opus-4-6). The 6-dimension rubric requires complex multi-dimensional reasoning, nuanced security analysis, and consistent scoring across dimensions. Sonnet and Haiku may produce inconsistent dimension scores, miss subtle security findings in D3, and generate unreliable D5 comparative assessments. If not using an Opus-class model, treat results as approximate.
Arguments
<path>(required): Path to the SKILL.md file to evaluate.--scope [gate|target|full](optional, default:full): Evaluation scope.gate: D1 + D3 only (~8K tokens). Outputs"partial": true.target --dimension D{N}: specified dimension + D3 gate (~12K tokens). Outputs"partial": true.full: all 6 dimensions (~40K tokens). Default behavior.
--dimension D{N}(optional): Used with--scope targetto specify which dimension.--format [json|md|all](optional, default:json): Output format.--feedback <path>(optional): Path to a feedback signal JSON file.--ci(optional): CI-friendly mode. Suppresses interactive prompts, outputs JSON only, sets exit code (0=all PASS, 1=CAUTION, 2=FAIL).
Error Handling
- File not found: Stop immediately. Output
"Error: File not found: {path}"(translate at display time). - Not a SKILL.md: Warn
"Warning: filename is not SKILL.md — continuing with evaluation."if applicable. - YAML malformed: Warn
"Warning: YAML frontmatter is malformed.", set D1 frontmatter_sub = 0, continue with remaining checks.
Steps
Step 1: Load Target
Parse arguments. Check current model — if not an Opus-class model, output this warning (translate to the session locale at display time):
⚠ Warning: Current model is {model_name}. For reliable 6D evaluation, Claude Opus 4.6 is recommended. Results may be less consistent with other models.
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 · 417 lines · 0 tokens per session scan A 9806ae0335dd
eval-skill is a command published in the GitHub repository Evol-ai/SkillCompass (216 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,709 tokens. 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.
Other commands, from other repositories
qec-sinter
Generate Sinter task templates and configure community benchmark harnesses for QECTOR decoders.
git-workflow
Run review, tests, and commit steps, then prepare a pull request.
ccc-audit
Audit the current project for dependency vulnerabilities, oversized bundles, type errors, dead code, hardcoded secrets, undocumented env vars and a missing CLAUDE.md. Use when you want a health score before a release or review.
verify
Run lint, type-check, tests, and a security scan before committing.
generate-tests
Generate comprehensive tests for specified code.
ui-snapshot.template
This prompt was authored for Claude-style slash workflows. In Codex runtime, adapt tool calls as follows.