Ask for missing deployment settings and summarize the requested configuration without deploying it.
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Analyzes code files and reports statistics including line counts, file counts by extension, and total size. Use this skill whenever the user wants to understand the composition of a codebase - asking about "how many lines of code", "what file types exist", "code distribution", or needing a quick audit of project size and structure. Make sure to invoke this skill when users mention analyzing codebases, counting lines, checking file distributions, or auditing code.
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See how to installReview the instructions the agent will receive before you install.
Analyzes code files and generates statistics about a codebase.
When invoked, this skill will:
node_modules/, .git/, dist/, and build/ unless the user explicitly asks to count them. These are dependencies, repository metadata, or generated output rather than project source.Always use this exact format for the output:
# Code Statistics
## Summary
- Total Files: <count>
- Total Lines: <count>
- Total Size: <size_bytes> bytes
## Files by Extension
| Extension | Files | Lines |
|-----------|-------|-------|
| .go | 12 | 1500 |
| .md | 5 | 200 |
## Top 5 File Extensions by Line Count
1. .go — 1500 lines
2. .md — 200 lines
## Largest Files (top 5)
1. main.go (500 lines)
2. util.go (300 lines)
If a file has no extension, group it under (no ext) in both extension sections.
Bash with find to locate project files, pruning the excluded directoriesBash with wc -l to count lines per file(no ext)No reviews yet. Tell others what you thought.
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Ask for missing deployment settings and summarize the requested configuration without deploying it.
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Decode the marker fixture used by the DeepSeek Harness integration example.
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Capture and review Agent Skill observations, and create, run, diagnose, or iteratively improve Skill evaluations (evals) with the skill-up CLI. Use when the user asks to record explicitly attributed Skill usage or feedback; review observations or user-supplied traces/transcripts; turn an approved observation into a regression case; evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill; add or strengthen eval cases; write eval.yaml/case.yaml; run skill-up run/validate/list-cases/report/import/init; or migrate from Anthropic evals.json. Plugin observation capture/review require either the Codex skill-up plugin or an observer-enabled DSH skill-up plugin. User-supplied external evidence can be reviewed without a plugin; evaluation remains multi-engine.
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