Plugin development toolkit with skills for creating agents, commands, hooks, MCP integrations, and comprehensive plugin structure guidance
Use this agent when the user asks to "create an agent", "generate an agent", "build a new agent", "make me an agent that...", or describes agent functionality they need. Trigger when user wants to create autonomous agents for plugins. Examples: <example> Context: User wants to create a code review agent user: "Create an agent that reviews code for quality issues" assistant: "I'll use the agent-creator agent to generate the agent configuration." <commentary> User requesting new agent creation, trigger agent-creator to generate it. </commentary> </example> <example> Context: User describes needed functionality user: "I need an agent that generates unit tests for my code" assistant: "I'll use the agent-creator agent to create a test generation agent." <commentary> User describes agent need, trigger agent-creator to build it. </commentary> </example> <example> Context: User wants to add agent to plugin user: "Add an agent to my plugin that validates configurations" assistant: "I'll use the agent-creator agent to generate a configuration validator agent." <commentary> Plugin development with agent addition, trigger agent-creator. </commentary> </example>
Use this agent when the user asks to "validate my plugin", "check plugin structure", "verify plugin is correct", "validate plugin.json", "check plugin files", or mentions plugin validation. Also trigger proactively after user creates or modifies plugin components. Examples: <example> Context: User finished creating a new plugin user: "I've created my first plugin with commands and hooks" assistant: "Great! Let me validate the plugin structure." <commentary> Plugin created, proactively validate to catch issues early. </commentary> assistant: "I'll use the plugin-validator agent to check the plugin." </example> <example> Context: User explicitly requests validation user: "Validate my plugin before I publish it" assistant: "I'll use the plugin-validator agent to perform comprehensive validation." <commentary> Explicit validation request triggers the agent. </commentary> </example> <example> Context: User modified plugin.json user: "I've updated the plugin manifest" assistant: "Let me validate the changes." <commentary> Manifest modified, validate to ensure correctness. </commentary> assistant: "I'll use the plugin-validator agent to check the manifest." </example>
Use this agent when the user has created or modified a skill and needs quality review, asks to "review my skill", "check skill quality", "improve skill description", or wants to ensure skill follows best practices. Trigger proactively after skill creation. Examples: <example> Context: User just created a new skill user: "I've created a PDF processing skill" assistant: "Great! Let me review the skill quality." <commentary> Skill created, proactively trigger skill-reviewer to ensure it follows best practices. </commentary> assistant: "I'll use the skill-reviewer agent to review the skill." </example> <example> Context: User requests skill review user: "Review my skill and tell me how to improve it" assistant: "I'll use the skill-reviewer agent to analyze the skill quality." <commentary> Explicit skill review request triggers the agent. </commentary> </example> <example> Context: User modified skill description user: "I updated the skill description, does it look good?" assistant: "I'll use the skill-reviewer agent to review the changes." <commentary> Skill description modified, review for triggering effectiveness. </commentary> </example>
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 "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.
This skill should be used when the user asks to "add MCP server", "integrate MCP", "configure MCP in plugin", "use .mcp.json", "set up Model Context Protocol", "connect external service", mentions "${CLAUDE_PLUGIN_ROOT} with MCP", or discusses MCP server types (SSE, stdio, HTTP, WebSocket). Provides comprehensive guidance for integrating Model Context Protocol servers into Claude Code plugins for external tool and service integration.
This skill should be used when the user asks about "plugin settings", "store plugin configuration", "user-configurable plugin", ".local.md files", "plugin state files", "read YAML frontmatter", "per-project plugin settings", or wants to make plugin behavior configurable. Documents the .claude/plugin-name.local.md pattern for storing plugin-specific configuration with YAML frontmatter and markdown content.
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimnpx claudepluginhub ai-integr8tor/anthropics-claude-plugins-official --plugin plugin-devBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
A curated directory of high-quality plugins for Claude Code.
⚠️ Important: Make sure you trust a plugin before installing, updating, or using it. Anthropic does not control what MCP servers, files, or other software are included in plugins and cannot verify that they will work as intended or that they won't change. See each plugin's homepage for more information.
/plugins - Internal plugins developed and maintained by Anthropic/external_plugins - Third-party plugins from partners and the communityPlugins can be installed directly from this marketplace via Claude Code's plugin system.
To install, run /plugin install {plugin-name}@claude-plugins-official
or browse for the plugin in /plugin > Discover
Internal plugins are developed by Anthropic team members. See /plugins/example-plugin for a reference implementation.
Third-party partners can submit plugins for inclusion in the marketplace. External plugins must meet quality and security standards for approval. To submit a new plugin, use the plugin directory submission form.
Each plugin follows a standard structure:
plugin-name/
├── .claude-plugin/
│ └── plugin.json # Plugin metadata (required)
├── .mcp.json # MCP server configuration (optional)
├── commands/ # Slash commands (optional)
├── agents/ # Agent definitions (optional)
├── skills/ # Skill definitions (optional)
└── README.md # Documentation
Please see each linked plugin for the relevant LICENSE file.
For more information on developing Claude Code plugins, see the official documentation.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Complete developer toolkit for Claude Code
Intelligent draw.io diagramming plugin with AI-powered diagram generation, multi-platform embedding (GitHub, Confluence, Azure DevOps, Notion, Teams, Harness), conditional formatting, live data binding, and MCP server integration for programmatic diagram creation and management.
Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.
Production-grade engineering skills for AI coding agents — covering the full software development lifecycle from spec to ship.
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams
Conversation-handoff document generator. Compacts the current conversation into a markdown handoff so a fresh agent can continue. References existing artifacts (PRDs, plans, ADRs, issues, commits) by path/URL — does not duplicate them. Enhanced from Matt Pocock's MIT-licensed handoff skill (https://github.com/mattpocock/skills) with: (1) stdlib Python tools (template generator, artifact deduplicator, skill recommender), (2) 3 reference docs citing 5+ authoritative sources each (handoff structure, deduplication discipline, next-session skill matching), (3) cs-handoff-author persona agent + /cs:handoff slash command. Matt's no-duplication discipline preserved verbatim per MIT. Use when user wants to hand off the current conversation to a fresh agent or starts a new session that picks up prior work.
Easily create hooks to prevent unwanted behaviors by analyzing conversation patterns
Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Triggers: 'research [topic]', 'look into [topic]', 'what do we know about [topic]', 'investigate [topic]', 'find me information on [topic]', 'do some research on [topic]', 'I need to understand [topic]', or any research request that doesn't obviously match a more-specific specialist skill. Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.
Audit datasets for completeness, consistency, accuracy, and validity. 3 stdlib-only Python tools: data profiler with DQS scoring, missing value analyzer with MCAR/MAR/MNAR classification, and multi-method outlier detector.
EU AI Act (Regulation (EU) 2024/1689) operational compliance specialist for compliance teams. Three deterministic tools: AI system risk classifier (Article 5 prohibited / Article 6 + Annex III high-risk / Article 50 limited-risk / minimal-risk per the binding regulation), conformity assessment planner (Article 43 Module A vs Module H + notified-body routing + Annex IV technical documentation checklist), obligation tracker (provider/deployer/importer/distributor obligations matrix per Title III Chapter 3 + GPAI obligations per Articles 51-55). 4 in-depth references: Titles I-XII Article-by-Article walkthrough, Annex III 8 high-risk categories with Article 6(2) carve-outs, GPAI obligations including systemic-risk threshold, cross-framework mapping to ISO 42001 + NIST AI RMF + GDPR. Stdlib-only. Built for compliance officers executing Article-level conformity work — not for executive AI strategy (see chief-ai-officer-advisor for that).