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Found 582 Skills
Sentry JavaScript frontend bug pattern review based on real production errors. Use when reviewing React/TypeScript frontend code for common bug patterns. Trigger keywords: "javascript bug review", "frontend errors", "react error patterns", "sentry frontend bugs".
Use when asked to fix, resolve, or address a GitHub PR — including review comments, Copilot suggestions, and CI test failures. Triggers on phrases like "fix PR", "fix PR comments", "resolve review", "address Copilot feedback", "fix review comments", "fix CI", "fix failing tests on PR", or when given a PR number to fix.
Iterative codebase quality audit with multi-agent validation and escalating-depth SEEK/VALIDATE/FIX/RECURSE cycle. Use for quality audit, code audit, codebase review, technical debt audit, refactoring opportunities, module quality check, or architecture review.
Orchestrate a multi-phase implementation workflow for this repository with artifact files under .ai/<project-name>/<letter>/ and fresh codex exec child runs per phase. Use when the user wants one prompt to drive context gathering, planning, plan assessment, implementation, build verification, and review iterations while keeping the main session context clean.
Polish Chinese technical blogs, remove redundant expressions, enhance professionalism and logic, eliminate "AI tone", and ensure code standardization.
React 19 performance patterns and composition architecture for Vite + Cloudflare projects. 50+ rules ranked by impact — eliminating waterfalls, bundle optimisation, re-render prevention, composition over boolean props, server/client boundaries, and React 19 APIs. Use when writing, reviewing, or refactoring React components. Triggers: 'react patterns', 'react review', 'react performance', 'optimise components', 'react best practices', 'composition patterns', 'why is it slow', 'reduce re-renders', 'fix waterfall'.
Agent skill for analyze-code-quality - invoke with $agent-analyze-code-quality
Leverage OpenAI Codex/GPT models for autonomous code implementation. Triggers: "codex", "use gpt", "gpt-5", "let openai", "full-auto", "用codex", "让gpt实现". Use this skill whenever the user wants to delegate coding tasks to OpenAI models, run code reviews via codex, or execute tasks in a sandboxed environment.
Comprehensive codebase reading engine. Systematically reads actual source code line by line through a 6-phase protocol — scoping, structural mapping, execution tracing, deep reading, pattern synthesis, and structured reporting. Source code is the source of truth. Use when needing to truly understand how code works, not just what documentation claims.
Phase 2 of the issue process — Read the issue report + read the code, identify the true root cause and assess the repair risk, and finally provide the user with 2-3 repair plan options for them to decide. This phase is **not about starting to modify code** — after analysis, show the conclusion to the user first, and only proceed to Phase 3 after the user confirms the plan. The prerequisite dependency easysdd-issue-report has been completed. Trigger scenarios: The user says "analyze this bug", "find the root cause", "locate the issue", and the {slug}-report.md already exists in the issue directory.
When to ship vs not ship. The single ship gate, six auto-decision principles for plan reviews, and the Confusion Protocol for when to stop and ask.
You are a **Jira Workflow Steward**, the delivery disciplinarian who refuses anonymous code. If a change cannot be traced from Jira to branch to commit to pull request to release, you treat the wor...