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Found 1,231 Skills
Explain code functionality in detail.
Comprehensive React/TypeScript frontend code review with optional parallel agents
Use after run-plan completes to independently verify the implementation. Reads only the plan document and inspects the codebase from scratch — information-isolated from the execution context. Produces a structured review document with PASS/FAIL verdict. Triggers when the user says "review the work", "verify the implementation", "check if the plan was executed correctly".
Use when executing implementation plans. Dispatches independent subagents for individual tasks with code review checkpoints between iterations for rapid, controlled development.
Analyzes git commits and changes within a timeframe or commit range, providing structured summaries for code review, retrospectives, work logs, or session documentation.
Full task lifecycle: create → assign → monitor → review → reject/complete. Use when asked to "add a feature", "fix a bug", "create a task", "加个功能", "修个 bug", or "/ak-task <description>".
Use skill if you are writing or reviewing framework-agnostic TypeScript and need strict typing, tsconfig/lint decisions, safer refactors, or guidance on generics, unions, and typed boundaries.
Use when writing or reviewing n8n SDK code that wires IF, Switch, Merge, error outputs, or any multi-input/multi-output connection. Triggers on .add(), .to(), .input(n), .output(n), .onTrue, .onFalse, .onCase, .onError, useDataOfInput, merge, switch, IF nodes, error branches, fan-out, fan-in, or any review of the workflow's connections object.
Use when writing or reviewing Kotlin type declarations to choose @JvmInline value class over data class where appropriate, including Compose stability implications.
Codex code review closeout: local dirty changes, PR branch vs main, parallel tests.
Security-first skill vetting protocol for AI agents. Use before installing any skill from the platform skill market, skillhub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns to determine whether a skill is safe to install.
Use PAL MCP to orchestrate multiple AI models (Gemini, OpenAI, Grok, Ollama) for code reviews, debugging, planning, and CLI bridging