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Found 52 Skills
Automated commit analysis and regression detection for AItrader. 自动化提交分析和回归检测。 Use this skill when: - Running regression checks after code changes (代码修改后运行回归检测) - Analyzing git commit history (分析 git 提交历史) - Using AI to analyze code changes (使用 AI 分析代码变更) - Checking if fix commits are still correctly applied (检查修复是否正确应用) - Before merging PRs (合并 PR 前) Keywords: commit, regression, analysis, git, fix, validation, AI, 提交, 回归, 分析
Use when generating performance hypotheses backed by git history and code evidence.
Use when creating "changelog", "release notes", "version updates", generating "CHANGELOG.md", or asking about "git history to changelog", "commit summary", "what changed since last release"
Generate feature-based and confidentiality-safe English LinkedIn Experience drafts directly from commit messages. Use when asked to write LinkedIn experience text from real commit activity for all-time or a specific date range (`since`/`until` in YYYY-MM-DD), while avoiding repository statistics and internal/confidential implementation details.
Periodic cross-repo reflection analyzing 30 days of git history, extracting patterns via RAGS loop, and auto-creating skills
Build feature command
Post-mortem diagnostic analysis of failed or stuck workflows. Detects stuck loops, missing artifacts, abandoned work, scope drift, and crash/interruption patterns through git history and plan file analysis. Produces a structured diagnostic report with anomaly confidence levels, root cause hypotheses, and recommended remediation. READ-ONLY: never modifies files. Use for "forensics", "what went wrong", "why did this fail", "stuck loop", "diagnose workflow", "post-mortem", "workflow failure", or "session crashed". Do NOT use for debugging code bugs (use systematic-debugging), reviewing code quality (use systematic-code-review), or fixing issues (forensics only diagnoses).
Git expert for atomic commits, rebasing, and history management with style detection
Get git records for specified users and days, perform code review for each commit, and generate detailed code review reports
Detect codebase bloat through progressive analysis: dead code, duplication, complexity, documentation bloat. Use when context usage high, quarterly maintenance, pre-release cleanup, before refactoring. Do not use when active feature development, time-sensitive bugs, codebase < 1000 lines.
Explains the intent behind source code by finding original session transcripts. Use explain with a function, file, or line of code to understand why it exists.
Trace design decisions and concepts through session history, handoffs, and git. Triggers: "trace decision", "how did we decide", "where did this come from", "design provenance", "decision history".