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Found 64 Skills
Watch for the 11 known AI-coding-agent failure modes (fabrication, scope_creep, security_vulnerability, etc.) — consult this skill before edits, dependency adds, completion claims, or anything that could trip a known supervision concern. Quote the snake_case failure-mode ids verbatim when flagging risks.
Code review a pull request
Comprehensive pre-merge validation checklist for Python/React pull requests. Use before approving or merging any PR. Covers code quality checks (linting, formatting, type checking), test coverage requirements, documentation updates, migration safety, API contract compatibility, accessibility compliance, bundle size impact, and deployment readiness. Provides a systematic checklist that ensures nothing is missed before merge. Does NOT cover security review depth (use code-review-security).
Multi-dimensional code review with structured reports. Analyzes correctness, readability, performance, security, testing, and architecture. Triggers on "review code", "code review", "审查代码", "代码审查".
Automated code review with security, performance, and best practices analysis. Use when reviewing pull requests or analyzing code for vulnerabilities, performance issues, or maintainability concerns.
Meta-skill for validating the integrity and quality of other skills. automatically checks for SKILL.md existence, script syntax errors (via Godot CLI), and metadata completeness. Use this skill to verify the entire skill library. Trigger keywords: validation, continuous_integration, quality_assurance, syntax_check, metadata_check.
Deep Python code review of changed files using git diff analysis. Focuses on production quality, security vulnerabilities, performance bottlenecks, architectural issues, and subtle bugs in code changes. Analyzes correctness, efficiency, scalability, and production readiness of modifications. Use for pull request reviews, commit reviews, security audits of changes, and pre-deployment validation. Supports Django, Flask, FastAPI, pandas, and ML frameworks.
Validates code changes against DeepRead's mandatory patterns and standards defined in AGENTS.md. Use this after writing or modifying code to catch violations before committing.
Open source contribution best practices. Creating quality pull requests, writing good issues, following project conventions, and collaborating effectively with maintainers.
Multi-agent code review with specialized perspectives (security, performance, patterns, simplification, tests)
Triage unresolved PR review comments, produce a severity-ordered fix plan, then resolve or fix each issue with subagents. Use when addressing PR feedback before merge.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.