src/dot-agents/skills/code-reviewer/SKILL.md
Provides structured code review against plans and standards. Use when a feature is complete and needs validation, when reviewing code before merge, or when assessing quality and test coverage—e.g., "finished step X", "ready for review", "validate architecture", "check quality and tests".
npx skillsauth add jjjermiah/dotagents code-reviewerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You MUST complete a thorough code review before marking any work as done. Reviews without systematic checking always miss critical issues. Every time.
Validate completed work against original plans, identify deviations, assess code quality/maintainability/test coverage/security, and provide actionable recommendations with clear severity labels.
Announce your review start: "Beginning code review using code-reviewer skill."
Complete ALL six steps. Skipping any step means missing issues:
After completing all steps: "Code review complete. [N] critical, [N] important, [N] suggestions."
You MUST return reviews in this exact structure. No exceptions.
Overview (1-3 sentences summarizing overall quality)
Findings (bulleted), each with:
Reviews without severity labels = ambiguous priority. Reviews without fix recommendations = incomplete.
Tests / verification suggestions (always include if you found issues)
Final statement: "Review complete using code-reviewer skill."
Before finalizing: Verify you checked every file and followed all six review steps.
development
Guides creation, validation, and packaging of AI agent skills with token-efficient design, progressive disclosure patterns, and YAML frontmatter best practices. Use when building new skills, updating existing skills, validating skill structure against standards, or packaging for distribution—e.g., "create skill", "validate SKILL.md", "package skill for sharing", "check description format".
tools
Investigate and integrate weakly documented SDK/library modules (especially Azure SDKs) into code. Use when asked to "investigate module", "SDK", "client class", or when docs are missing/weak and you need to discover APIs, models, or usage patterns to implement integration.
tools
Write production-ready one-off scripts and automation utilities with proper error handling and safety patterns. Use when developing bash automation, Python CLI tools, shell scripts, system administration scripts, or command-line batch processing—e.g., "write a script to process files", "python one-liner for data conversion", "bash automation for backups", "shell script with error handling".
development
R package testing with testthat 3rd edition. Use when writing R tests, fixing failing tests, debugging errors, or reviewing coverage—e.g., "write testthat tests", "fix failing R tests", "snapshot testing", "test coverage".