4 082 agent workflow skills from 665 authors. They configure the agents themselves: memory, prompts, context and other skills. Half of them fit into 1 830 tokens or less — that is what one costs your context window when the agent loads it. 769 ship runnable scripts rather than instructions alone. 5 of them cannot work without an MCP server, most often task. We also found 541 copies of these same skills sitting in other people's repositories — counted once here, not 541 times.
4 082 unique 665 authors 2 734 updated this month 466 from vendors
Troubleshoot Claude Code extensions and behavior. Triggers on: debug, troubleshoot, not working, skill not loading, hook not running, agent not found.
Claude Code hook system for pre/post tool execution. Triggers on: hooks, PreToolUse, PostToolUse, hook script, tool validation, audit logging.
Model Context Protocol (MCP) server patterns for building integrations with Claude Code. Triggers on: mcp server, model context protocol, tool handler, mcp resource, mcp tool.
Guide for creating new Agent Skills. Use this skill when you need to create a new skill.
Interactive skill creation assistant that guides users through building new Agent Skills for Claude Code. Use when creating new skills, building custom capabilities, or when the user runs /new-skill command. Helps design skill structure, craft descriptions, create scripts, and organize supporting files.
Updated API skill
This skill should be used when designing or implementing systems with multiple AI agents that coordinate to accomplish tasks. Triggers on "multi-agent", "orchestrator", "sub-agent", "coordination", "delegation", "parallel agents", "sequential pipeline", "fan-out", "map-reduce", "spawn agents", "agent hierarchy".
This skill should be used when moving from design to implementation. Triggers on "let's build", "implement this", "looks good let's code", "ready to implement". Presents options for parallel agent competition (cookoff), single subagent, or local implementation. Each agent creates own plan from shared design for genuine variation.
This skill should be used to update terminal window title with context. Triggers automatically at session start via hook. Also triggers on topic changes during conversation (debugging to docs, frontend to backend). Updates title with emoji + project + current topic.
Spawns multiple AI coding agents to work on related GitHub issues concurrently using git worktrees. Use when breaking down a large feature into multiple issues, running parallel agents with --print flag, or managing wave-based execution of related tasks.
Manage information from Wechat and Send Messages, Only could be activated with the MCP Server `WeChatMCP`. Check it before using any tools in this MCP server
Context management specialist for multi-agent workflows and long-running tasks. Use when coordinating multiple agents, preserving context across sessions, or managing complex project state. Focuses on context compression and distribution.
This skill should be used when demonstrating skill structure and format. Provides example patterns for creating new skills.
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits.
This skill should be used when the user asks to "diagnose context problems", "fix lost-in-middle issues", "debug agent failures", "understand context poisoning", or mentions context degradation, attention patterns, context clash, context confusion, or agent performance degradation. Provides patterns for recognizing and mitigating context failures.
This skill should be used when the user asks to "evaluate agent performance", "build test framework", "measure agent quality", "create evaluation rubrics", or mentions LLM-as-judge, multi-dimensional evaluation, agent testing, or quality gates for agent pipelines.
This skill should be used when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph", "track entities", or mentions memory architecture, temporal knowledge graphs, vector stores, entity memory, or cross-session persistence.
This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.
This skill should be used when the user asks to "design agent tools", "create tool descriptions", "reduce tool complexity", "implement MCP tools", or mentions tool consolidation, architectural reduction, tool naming conventions, or agent-tool interfaces.
This skill should be used when the user wants to "create a skill", "add a skill to plugin", "write a new skill", "improve skill description", "organize skill content", or needs guidance on skill structure, progressive disclosure, or skill development best practices for Claude Code plugins.
Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos).
Edit or improve the AI system prompt used in DBX Studio's AI chat. Invoke when the user wants to change how the AI responds, its tone, tool usage order, or response format.
The philosophy and practical benefits of agent fungibility in multi-agent software development. Why homogeneous, interchangeable agents outperform specialized role-based systems at scale.
Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.
| This skill should be used when coordinating multiple subagents, implementing orchestrator patterns, or managing parallel agent workflows. "multi-agent workflow", "delegate to agents", "run agents in parallel", "launch multiple agents".
> Pedantic backend pre-commit and atomic commit Skill for Django/Optimo-style repos. Enforces local AGENTS.md / CLAUDE.md, pre-commit hooks, .security/* helpers, and Monty’s backend engineering taste – with no AI signatures in commit messages.
Dispatch multiple agents to work on independent problems concurrently. Use when facing 3+ independent failures or tasks.
Execute plans using fresh subagent per task with code review between tasks. Use for high-quality iterative implementation.
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
Implement persistent memory patterns for AI agents using AgentDB - session memory, long-term storage, pattern learning, and context management for stateful agents, chat systems, and intelligent assistants
Rapidly creates atomic, focused skills optimized with evidence-based prompting, specialist agents, and systematic testing. Each micro-skill does one thing exceptionally well using self-consistency, program-of-thought, and plan-and-solve patterns. Enhanced with agent-creator principles and functionality-audit validation. Perfect for building composable workflow components.
Implement machine learning solutions including model architectures, training pipelines, optimization strategies, and performance improvements. This skill spawns a specialist ML implementation agent...
Comprehensive framework for analyzing, creating, and refining prompts for AI systems. Use when creating prompts for Claude, ChatGPT, or other language models, improving existing prompts, or applying evidence-based prompt engineering techniques. Applies structural optimization, self-consistency patterns, and anti-pattern detection to transform prompts into highly effective versions.
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
Creates Claude Code skills where each skill is tied to a specialist agent optimized with evidence-based prompting techniques. Use this skill when users need to create reusable skills that leverage specialized agents for consistent high-quality performance. The skill ensures that each created skill spawns an appropriately crafted agent that communicates effectively with the parent Claude Code instance using best practices.
Advanced skill creation system for Claude Code that combines deep intent analysis, evidence-based prompting principles, and systematic skill engineering. Use when creating new skills or refining existing skills to ensure they are well-structured, follow best practices, and incorporate sophisticated prompt engineering techniques. This skill transforms skill creation from template filling into a strategic design process.
Creates ergonomic slash commands (/command) that provide fast, unambiguous access to micro-skills, cascades, and agents. Enhanced with auto-discovery, intelligent routing, parameter validation, and command chaining. Generates comprehensive command catalogs for all installed skills with multi-model integration.
Analyze skill library to identify coverage gaps, redundant overlaps, optimization opportunities, and provide recommendations for skill portfolio improvement
Chain agent outputs as inputs in sequential or parallel pipelines for data flow orchestration
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization
Create ergonomic slash commands for fast access to micro-skills with auto-discovery and parameter validation
Comprehensive framework for analyzing, creating, and refining prompts for AI systems using evidence-based techniques
Active diagnostic tool for analyzing prompt quality, detecting anti-patterns, identifying token waste, and providing optimization recommendations
Complex multi-agent swarm orchestration with task decomposition, distributed execution, and result synthesis
| Use when launching a new product end-to-end from market research through post-launch monitoring. Orchestrates 15+ specialist agents across 5 phases in a 10-week coordinated workflow including research, development, marketing, sales preparation, launch execution, and ongoing optimization. Employs hierarchical coordination with parallel execution for efficiency and comprehensive coverage.
Waypoint plans methodology and session survival patterns for Claude Code. Use when working on long-running features, need to resume after context reset, want to document task progress, or need to survive session interruptions. Covers three-file structure (plan/context/tasks), SESSION PROGRESS tracking, quick resume instructions, update frequency, and context handoff patterns.
Context tracking and decision logging patterns for intentional memory management in Claude Code Waypoint Plugin. Use when you need to remember user preferences, track decisions, capture context across sessions, learn from corrections, or maintain project-specific knowledge. Covers when to persist context, how to track decisions, context boundaries, storage mechanisms, and memory refresh strategies.