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Found 2,233 Skills
BMad Autonomous Development — orchestrates parallel story implementation pipelines. Builds a dependency graph, updates PR status from GitHub, picks stories from the backlog, and runs each through create → dev → review → PR in parallel — each story isolated in its own git worktree — using dedicated subagents with fresh context windows. Loops through the entire sprint plan in batches, with optional epic retrospective. Use when the user says "run BAD", "start autonomous development", "automate the sprint", "run the pipeline", "kick off the sprint", or "start the dev pipeline". Run /bad setup or /bad configure to install and configure the module.
Self-referential loop until task completion with architect verification
Research and extract an engineer's coding style, patterns, and best practices from their GitHub contributions. Creates structured knowledge base for replicating their expertise.
Deep Angular 21 clean code audit with parallel specialist agents and senior team lead. Scans architecture, signals, stores, AI slop, ViewModel patterns, and more. Guarantees craftsman-level output. Use whenever the user says 'clean code', 'audit Angular', 'review frontend', 'check quality', 'anti-patterns', wants Angular code reviewed, or needs senior-level code standards enforced — even if they don't say 'clean code' explicitly.
Agent skill for worker-specialist - invoke with $agent-worker-specialist
Agent skill for automation-smart-agent - invoke with $agent-automation-smart-agent
Multi-agent QA review team for code changes. This skill should be used when the user asks to "review my code", "run QA", "qa-team", "review this branch", "code review", "check my changes", or wants a comprehensive multi-perspective code review of the current branch's changes. Spawns parallel specialist agents (security, database, reliability, compatibility, data integrity, performance, frontend, copy) that independently review the diff and produce a converged report. Also includes two generalist reviewers for convergence validation.
AI Agent Harness Design Patterns - Memory, Permission, Context Engineering, Delegation, Skill, Hook, Bootstrap. Chinese Version.
Use when the user says "silly sausage", "silly-sausage", invokes /silly-sausage, or expresses lighthearted exasperation at a mistake the agent made. Also triggers on the phrase appearing anywhere in user input — no slash required.
Run an interactive naming session for a project. Use when the user wants to name a project, app, package, tool, or repo. Presents names in rounds, tracks preferences, and refines suggestions based on selections.
Use when the agent needs access to information beyond its training data — knowledge sources, RAG pipelines, or grounding data.
Optimizer that refines and professionalizes AI agent skills through real usage — saves tokens, eliminates redundancy, and tightens instructions so skills cost less to run. Learns from mistakes, reviews quality, and improves over time. Observes skill execution in the current conversation, analyzes up to four sources (conversation friction, file diffs, user feedback, static diagnostic) plus accumulated lessons, and proposes concrete improvements to the target skill's SKILL.md. Works with Claude Code and compatible SKILL.md-based agent frameworks. Use after executing any skill: `/skill-optimizer [name]` or `/skill-optimizer` to auto-detect. `--review` processes accumulated lessons.