review

Solid

Full qualitative review of the agent setup. Reads every file, applies per-component rubrics, runs 21 cross-type optimization checks, and produces KEEP/REVIEW/REMOVE verdicts. Use when the user wants a deep review, redundancy check, or quality assessment of their setup.

Code & Development 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, content/allowed-tools-auto-approve --> # Review Setup Full qualitative review of the user's agent setup. Claude reads every file and evaluates quality, redundancy, coherence, and optimization opportunities. ## Hard Rules 1. **Never give a verdict without reading the files.** Lint counts are input data, not the verdict. A component with warnings can still be healthy. 2. **Read before you judge.** Read every file's actual content before assessing. 3. **Don't manufacture problems.** If the setup is good, say so. 4. **Always end with the evidence-based summary.** 5. **Record the exact start time** (note the timestamp from your first tool call in Step 2) and compute the exact duration at the end. ## 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 Lint for Context 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. This gives you per-component diagnostics, token budget, trigger overlaps, and dependency findings. Do NOT p...

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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