lint

Lint Setup

Run 39 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.

uv run python skills/lint/scripts/run_assessment.py <setup-path> recommended

If the user has a ~/.claude/ directory, pass it as the third argument for user-level config discovery:

uv run python skills/lint/scripts/run_assessment.py <setup-path> recommended ~/.claude

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 end of the report, include the exact timing:

Evaluated with: harness-eval v{version} (claude-code-plugin)
Duration: [X minutes Y seconds]

Get {version} by running: uv run python -c "import importlib.metadata; print(importlib.metadata.version('harness-eval'))"

Record the timestamp of your first tool call in Step 2 and compute the exact difference when you finish.

If the user chose terminal: print the report in the conversation.

If the user chose file: write the report as markdown to the path they specified (or suggest lint-report.md in the current directory). Tell them the file path when done.