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Found 3,223 Skills
Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says "DSE", "design space exploration", "sweep parameters", "optimize", "find best config", or wants iterative parameter tuning.
Turn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.
Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished, submission-ready PDF. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow.
Scan skills to extract cross-cutting principles and distill them into rules — append, revise, or create new rule files
Library-agnostic Flutter/Dart code review checklist covering widget best practices, state management patterns (BLoC, Riverpod, Provider, GetX, MobX, Signals), Dart idioms, performance, accessibility, security, and clean architecture.
Statistical rule discovery through measurement of Go codebases: Count patterns, derive confidence-scored rules, produce Style Vector fingerprint. Use when analyzing codebase conventions, extracting implicit coding rules, profiling a repo before onboarding or PR automation. Use for "analyze codebase", "find coding patterns", "what conventions does this repo use", "extract rules", or "codebase DNA". Do NOT use for code review, bug fixes, refactoring, or performance optimization.
Deterministic 3-phase GitHub PR review comment extraction: Authenticate, Mine, Validate. Use when mining tribal knowledge from PR reviews, extracting coding standards from review history, or building datasets for the Code Archaeologist agent. Use for "mine PRs", "extract review comments", "tribal knowledge", or "PR review history". Do NOT use for analyzing patterns, generating rules, or interpreting comments — that is the Code Archaeologist agent's responsibility.
Persistent markdown files as working memory for complex tasks: plan, track progress, store findings. Use when tasks have 3+ phases, require research, span many tool calls, or risk context drift. Use for "plan", "break down", "track progress", "multi-step", or complex tasks. Do NOT use for simple lookups, single-file edits, or questions answerable in one response.
Deterministic audit of cron/scheduled job scripts for reliability, error handling, logging, cleanup, and concurrency safety. Use when user says "audit cron", "check cron script", "cron best practices", "scheduled job review", or "bash script audit". Do NOT use for crontab scheduling syntax, systemd timers, or general shell linting without a cron/scheduled-job context.
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).
Systematic detection and prioritization of neglected code quality issues: stale TODOs, unused imports, deprecated functions, high complexity, dead code. Use when user requests "code cleanup", "find TODOs", "technical debt scan", or "quality of life fixes". Do NOT use for bug fixing (use systematic-debugging), feature work (use test-driven-development), or formatting-only (use code-linting).
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.