lint

Solid

Run deterministic static analysis on the full agent setup (CLAUDE.md, skills, commands, hooks, agents, MCP configs). 108 rules + system-level analysis (token budget, trigger overlaps, dependencies). No LLM. Use when the user wants a fast lint check, CI gate, or structural health report.

AI & Automation 27 stars 3 forks Updated 4 days ago Apache-2.0

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Quality Score: 82/100

Stars 20%
48
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

<!-- evaluator-ignore: content/broken-references, security/mcp-least-privilege, security/ast-behavioral, content/allowed-tools-auto-approve --> # Lint Setup Run 108 deterministic rules + system-level analysis on the user's agent setup. No LLM involved. Fast, reproducible, CI-suitable. ## Hard Rules 1. **This skill does NOT read files qualitatively.** It does NOT apply rubrics. It does NOT run cross-type checks. For that, use `/review`. 2. **Present the data, don't judge.** Report findings as-is. Don't add qualitative commentary. 3. **If everything passes, say so clearly.** Don't manufacture problems. ## Step 1: Ask Output Preference Before doing anything else, ask the user: > Where should i present the results? > 1. **Terminal** - print the report here in the conversation > 2. **File** - write a markdown report to a file (you'll choose the path) Wait for their answer before proceeding. ## Step 2: Run Static Analysis Determine the setup path. If the user doesn't specify one, use the current working directory. ```bash uvx --from harness-eval harness-eval harness-lint <setup-path> --format json ``` If `uvx` is not available, fall back to `pip install harness-eval` and use `harness-eval` directly. Read the JSON output. ## Step 3: Present the Report Read `report-format.md` and format the results following that structure. Include all sections: inventory, token budget, context utilization, trigger analysis, dependencies, findings, and inspection summary. At the very...

Details

Author
redhat-community-ai-tools
Repository
redhat-community-ai-tools/harness-eval
Created
3 months ago
Last Updated
4 days ago
Language
Python
License
Apache-2.0

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