Agent Workflow Claude Skills
4 122 agent workflow skills from 665 authors. They configure the agents themselves: memory, prompts, context and other skills. Half of them fit into 1 844 tokens or less — that is what one costs your context window when the agent loads it. 778 ship runnable scripts rather than instructions alone. 5 of them cannot work without an MCP server, most often task. We also found 589 copies of these same skills sitting in other people's repositories — counted once here, not 589 times.
4 122 unique 665 authors 4 updated this month 506 from vendors
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.
Create and manage Claude Code skills with auto-activation, progressive disclosure, and memory patterns. Use when creating skills, modifying skill-rules.json, understanding triggers (keywords, intent, file, content), working with hooks (UserPromptSubmit, PreToolUse, Stop), debugging activation, implementing guardrails, or building memory-aware skills that persist context across sessions. Covers 500-line rule, session tracking, enforcement levels (block, suggest, warn), plan-approval workflows, and best practices.
Use this skill for requests related to Pydantic AI framework - building agents, tools, dependencies, structured outputs, and model integrations.
Master protocol for deconstructing agent frameworks to inform derivative system architecture. Use when (1) analyzing an agent framework's codebase comprehensively, (2) comparing multiple frameworks to select best practices, (3) designing a new agent system based on prior art, (4) documenting architectural decisions with evidence, or (5) conducting technical due diligence on AI agent implementations. This skill orchestrates sub-skills for data substrate, execution engine, cognitive architecture, and synthesis phases.
Analyze the protocol layer between agent harness and LLM model. Use when (1) understanding message wire formats and API contracts, (2) examining tool call encoding/decoding mechanisms, (3) evaluating streaming protocols and partial response handling, (4) identifying agentic chat primitives (system prompts, scratchpads, interrupts), (5) comparing multi-provider abstraction strategies, or (6) understanding how frameworks translate between native LLM APIs and internal representations.
Analyze context management, memory systems, and state continuity in agent frameworks. Use when (1) understanding how prompts are assembled, (2) evaluating eviction policies for context overflow, (3) mapping memory tiers (short-term/long-term), (4) analyzing token budget management, or (5) comparing context strategies across frameworks.
Analyze coordination patterns, handoff mechanisms, and state sharing in multi-agent systems. Use when (1) understanding how agents transfer control, (2) evaluating shared vs isolated state patterns, (3) mapping communication protocols between agents, (4) assessing multi-agent orchestration approaches, or (5) comparing coordination models across frameworks.
Use when facing 3+ independent failures that can be investigated without shared state or dependencies. Dispatches multiple Claude agents to investigate and fix independent problems concurrently.
Advanced prompt engineering techniques for optimal AI responses. Use this when crafting prompts, optimizing AI interactions, or designing system prompts for applications.
Automatically backs up files, saves diffs, uses agents/skills, and ensures modular code (<200 lines) before any implementation. Use this skill for ALL code changes to ensure safe, reversible, and clean implementations.
Guide for creating new Claude skills. Use this when creating a new skill, updating existing skills, or learning best practices for skill development.
Create, update, test, and manage Agent Skills. Use when creating new skills, debugging existing ones, or organizing skill libraries. Based on official Claude Code documentation.
Use when executing implementation plans with independent tasks in the current session. Dispatches fresh subagent for each task with code review between tasks.
Analyze coding agent session transcripts to improve existing skills or create new ones. Use when asked to improve a skill based on a session, or extract a new skill from session history.
Use when facing 3+ independent failures that can be investigated without shared state or dependencies - dispatches multiple Claude agents to investigate and fix independent problems concurrently
Use when you've developed a broadly useful skill and want to contribute it upstream via pull request - guides process of branching, committing, pushing, and creating PR to contribute skills back to upstream repository
Use when executing implementation plans with independent tasks in the current session - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates
Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
Use when the user says "use the DevTools skill" or when they need help debugging a web app with Chrome DevTools MCP (UI bugs, incorrect behavior, console errors, network/API failures, or performance/lag), especially if the user seems inexperienced and needs guided, step-by-step diagnosis.
Diagnoses and debugs A2A agent communication issues including agent status, message routing, transport connectivity, and log analysis. Use when agents aren't responding, messages aren't being delivered, routing is incorrect, or when debugging orchestrator, coder-agent, tester-agent communication problems.
Creates new Agent Skills for Claude Code following best practices and documentation. Use when the user wants to create a new skill, extend Claude's capabilities, or package domain expertise into a reusable skill.
This skill is a practical, 'use-it-while-debugging' reference for getting a LiveKit + Letta voice agent working reliably.
This skill should be used when the user asks to "track work across sessions", "create an epic", "manage issue waves", "post a checkpoint", "claim an issue", "recover from compaction", "coordinate multiple agents", "update memory bank", "store large documents", or mentions GitHub Issues as persistent memory, multi-session work, context survival, agent collaboration, SERENA MCP memory, or project-level context. Provides complete protocols for using GitHub Issues as permanent memory that survives context exhaustion, with integrated SERENA MCP memory bank for project-level context and large document storage.
Production-ready patterns and best practices for MCP servers - architecture, security, performance, and maintenance
Create powerful MCP prompts that guide AI interactions with templates, arguments, and context injection
Quick start guide for creating MCP servers with the rmcp crate - installation, concepts, and first server
Use PROACTIVELY this agent when you need to design and create optimal Claude Code subagents, update existing agents with new capabilities, revise agent configurations, analyze project requirements to identify specialized roles, or craft precise agent configurations with appropriate tool permissions and model tiers. When the user specify "Create or Update subagent [name]", this skill must be triggered.
Creates custom output styles for Claude Code that modify system prompts and behavior. Use when the user asks to create output styles, customize Claude's response format, generate output-style files, or mentions output style configuration.
Use this skill when you need to report on a troubleshooting session
Creates and maintains Agent Skills with effective triggers and progressive disclosure. Use when user requests to create a skill, generate a SKILL.md, build custom capabilities, or mentions "create skill", "new skill", or "skill configuration".
Activates when the user asks about Agent Skills, wants to find reusable AI capabilities, needs to install skills, or mentions skills for Claude. Use for discovering, retrieving, and installing skills.
One-click installer and configurator for Gate MCP (mcporter) in OpenClaw. Use when the user wants to (1) Install mcporter CLI tool, (2) Configure Gate MCP server connection, (3) Verify Gate MCP setup, or (4) Troubleshoot Gate MCP connectivity issues.
Help users create high-quality skills by discovering and incorporating proven methodologies from domain experts. Use this skill BEFORE skill-creator when users want to create a new skill - it enhances skill-creator by first identifying expert frameworks and best practices to incorporate. Triggers on requests like "help me create a skill for X" or "I want to make a skill that does Y". This skill guides methodology selection, then hands off to skill-creator for the actual skill generation.
Automatically share skills, migrate local skills to code repositories, open source skills, skill version management, configure git remote
Translate SKILL.md and README.md files into multiple languages for sharing skills internationally
Skill permission analysis, one-time authorization, analyze skill permissions, batch authorization
Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent, agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop
\"Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent,\" agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop