Loading...
Loading...
Found 10,112 Skills
Build and deploy parallel execution via subagent waves, agent teams, and multi-wave pipelines. Use when the Decomposition Gate identifies 2+ independent actions or when spawning teams. NOT for single-action tasks or non-parallel work.
JSON Hygiene Agent. Detects duplicate keys in JSON configuration files that might be silently ignored by standard parsers. Auto-invoked for JSON audits or manifest validation. V2 includes L5 Delegated Constraint Verification.
Convert raw plugin analysis results into actionable improvement recommendations for agent-scaffolders and agent-skill-open-specifications. Trigger with "synthesize learnings", "generate improvement recommendations", "what should we improve in our scaffolders", "update our meta-skills based on these findings", or after completing a plugin analysis.
(Industry standard: Sequential Agent / Agent as a Tool) Primary Use Case: Delegating a well-defined task to a worker agent, verifying its execution, and repeating if necessary. Inner/outer agent delegation pattern. Use when: work needs to be delegated from a strategic controller (Outer Loop) to a tactical executor (Inner Loop) via strategy packets, with verification and correction loops.
(Industry standard: Routing Agent / Orchestrator Pattern) Primary Use Case: Analyzing an ambiguous trigger and routing it to one of the specific specialized implementations. Routes triggers to the appropriate agent-loop pattern. Use when: assessing a task, research need, or work assignment and deciding whether to run a simple learning loop, red team review, dual-loop delegation, or parallel swarm. Manages shared closure (seal, persist, retrospective, self-improvement).
Systematically analyze agent plugins and skills to extract design patterns, architectural decisions, and reusable techniques. Trigger with "analyze this plugin", "mine patterns from", "review plugin structure", "extract learnings from", "what patterns does this plugin use", or when examining any plugin or skill collection to understand its design.
Practical AI agent workflows and productivity techniques. Provides optimized patterns for daily development tasks such as commands, shortcuts, Git integration, MCP usage, and session management.
Bootstrap AGENTS.md as a short table-of-contents plus a structured docs/ directory (architecture, product specs, acceptance tests, ADRs, exec plans, quality grades). Use when AGENTS.md is missing, when asked to "create AGENTS.md", "bootstrap project for agents", or "set up agent context".
Developer machine tool for replicating plugin source code between local project repositories. Use when you want to push plugin updates from agent-plugins-skills to a consumer project, or pull the latest plugins into a consumer project from this central repo. Works with explicit --source and --dest paths; supports additive-update (default), --clean (also removes deleted files), --link (symlink), and --dry-run modes.
Configure and orchestrate Claude Code agent teams (TeamCreate, SendMessage, TaskUpdate workflow). Use when you need multiple agents working in parallel on a complex task, want to coordinate background agents with messaging, or are setting up a lead/teammate architecture with a shared task list. Teams are experimental — enable with --enable-teams flag.
Autonomous SDLC router. Takes a job, classifies complexity, executes the appropriate lev-* workflow (from trivial fix to full epic), and returns "done" with runnable instructions. One shot to full auto: spec/bd/poc/impl. Subagent returns completion artifact. Triggers: "sidequest", "side quest", "just do it", "autonomous", "one shot"
Manage AI agent memory files (AGENTS.md/CLAUDE.md). Supports update and restructure modes. Use this when users need to sync, update, or restructure agent memory files. Triggered by keywords such as "记忆文件", "memory file", "AGENTS.md", "更新记忆", "重构记忆", "memory sync", "memory restructure".