Agents
1,401 skills.
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remembergithub9.3KTransforms lessons learned into domain-organized memory instructions (global or workspace). Syntax: `/remember [>domain [scope]] lesson clue` where scope is `global` (default), `user`, `workspace`, or `ws`.rust-mcp-server-generatorgithub9.2KGenerate a complete Rust Model Context Protocol server project with tools, prompts, resources, and tests using the official rmcp SDKremembering-conversationsobra9.2KYou MUST invoke this skill before saying "I don't know," guessing, or treating any topic as new, no matter how trivial the question seems. It supplements other memory systems, which only hold partial records. Searching past conversations is the only way to recover what was actually said.parallel-feature-developmentwshobson9.2KCoordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing a large feature into independent work streams, when two or more agents need to implement different layers of the same system simultaneously, when establishing file ownership to prevent merge conflicts in a shared codebase, when designing interface contracts so parallel implementers can build against each other'sgo-mcp-server-generatorgithub9.2KGenerate a complete Go MCP server project with proper structure, dependencies, and implementation using the official github.com/modelcontextprotocol/go-sdk.microsoft-skill-creatorgithub9.1KCreate agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.task-coordination-strategieswshobson9.1KDecompose complex tasks, design dependency graphs, and coordinate multi-agent work with proper task descriptions and workload balancing. Use this skill when breaking down work for agent teams, managing task dependencies, or monitoring team progress.remember-interactive-programminggithub9.1KA micro-prompt that reminds the agent that it is an interactive programmer. Works great in Clojure when Copilot has access to the REPL (probably via Backseat Driver). Will work with any system that has a live REPL that the agent can use. Adapt the prompt with any specific reminders in your workflow and/or workspace.finalize-agent-promptgithub9.1KFinalize prompt file using the role of an AI agent to polish the prompt for the end user.copilot-instructions-blueprint-generatorgithub9KTechnology-agnostic blueprint generator for creating comprehensive copilot-instructions.md files that guide GitHub Copilot to produce code consistent with project standards, architecture patterns, and exact technology versions by analyzing existing codebase patterns and avoiding assumptions.what-context-neededgithub9KAsk Copilot what files it needs to see before answering a questionphp-mcp-server-generatorgithub9KGenerate a complete PHP Model Context Protocol server project with tools, resources, prompts, and tests using the official PHP SDKteam-communication-protocolswshobson9KStructured messaging protocols for agent team communication including message type selection, plan approval, shutdown procedures, and anti-patterns to avoid. Use this skill when establishing communication norms for a newly spawned team, when deciding whether to send a direct message or a broadcast, when a team-lead needs to review and approve an implementer's plan before work begins, when orchestrating a graceful team shutdown after all tasks are complete, or when debugging why teammates are notteam-composition-patternswshobson8.9KDesign optimal agent team compositions with sizing heuristics, preset configurations, and agent type selection. Use this skill when deciding how many agents to spawn for a task, when choosing between a review team versus a feature team versus a debug team, when selecting the correct subagent_type for each role to ensure agents have the tools they need, when configuring display modes (tmux, iTerm2, in-process) for a CI or local environment, or when building a custom team composition for a non-staworkiq-copilotgithub8.9KGuides the Copilot CLI on how to use the WorkIQ CLI/MCP server to query Microsoft 365 Copilot data (emails, meetings, docs, Teams, people) for live context, summaries, and recommendations.mcp-deploy-manage-agentsgithub8.9KSkill converted from mcp-deploy-manage-agents.prompt.mdokx-aiokx8.9KOperate OKX.AI agents and marketplace workflows. Use when the user wants to register or update an Agent identity; discover, publish, buy, or manage Agent services(tasks), including signal services; create or fulfill marketplace services; manage or view subscriptions; view copy-trade records; review delivered work, rate agent-service orders, request or respond to an evaluation; monitor task/order execution statussuggest-awesome-github-copilot-agentsgithub8.9KSuggest relevant GitHub Copilot Custom Agents files from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing custom agents in this repository, and identifying outdated agents that need updates.structured-autonomy-implementgithub8.9KStructured Autonomy Implementation Promptjava-mcp-server-generatorgithub8.8KGenerate a complete Model Context Protocol server project in Java using the official MCP Java SDK with reactive streams and optional Spring Boot integration.swift-mcp-server-generatorgithub8.8KGenerate a complete Model Context Protocol server project in Swift using the official MCP Swift SDK package.structured-autonomy-generategithub8.8KStructured Autonomy Implementation Generator Promptmcp-create-adaptive-cardsgithub8.8KSkill converted from mcp-create-adaptive-cards.prompt.mdmcp-create-declarative-agentgithub8.8KSkill converted from mcp-create-declarative-agent.prompt.mdemblem-ai-prompt-examplesemblemcompany8.8KCurated prompt and usage examples for research, portfolio review, quote requests, approval-gated drafts, NFT discovery, prediction-market analysis, and assistant workflows. Emphasis is review-first, trust-boundary-aware use of external data, and explicit confirmation before any value-moving action. Use when the user wants example prompts, phrasing guidance, or sample requests for end-user EmblemAI tasks.kotlin-mcp-server-generatorgithub8.8KGenerate a complete Kotlin MCP server project with proper structure, dependencies, and implementation using the official io.modelcontextprotocol:kotlin-sdk library.mcp-copilot-studio-server-generatorgithub8.8KGenerate a complete MCP server implementation optimized for Copilot Studio integration with proper schema constraints and streamable HTTP supportdeclarative-agentsgithub8.8KComplete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integrationtypespec-create-agentgithub8.8KGenerate a complete TypeSpec declarative agent with instructions, capabilities, and conversation starters for Microsoft 365 Copilotgenshijininterfacex-co-jp8.8K超圧縮コミュニケーションモード。原始人のように話してトークン使用量を約75%削減。 技術的正確性は完全に維持。強度レベル: 丁寧・通常（デフォルト）・極限の3段階。 「原始人モード」「短く」「簡潔に」「トークン節約」と言うか、/genshijin で起動。ruby-mcp-server-generatorgithub8.7KGenerate a complete Model Context Protocol server project in Ruby using the official MCP Ruby SDK gem.agent-platform-skill-registrygoogle8.6KInteract with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities.agentselevenlabs8.5KBuild voice AI agents with ElevenLabs. Use when creating voice assistants, customer service bots, interactive voice characters, or any real-time voice conversation experience, and when configuring an agent's tools, workflows, or procedures, including creating, editing, compiling, and publishing procedure drafts on an agent branch over the SDKs or REST API.mem-searchthedotmack8.5KUse this when the user asks to search memory, "did we already solve this?", "how did we do X last time?", or wants work from previous sessions.task-observerrebelytics8.5KMonitors task execution for skill improvement opportunities. Use during ANY multi-step task, agentic workflow, or work session. Captures patterns, user corrections and methodology worth preserving as reusable skills. Also triggers in post-task feedback discussions and when the user mentions skill observations, the observation log, or skill taxonomy. Also known as \"One Skill to Rule Them All\" — trigger on this phrase too. IMPORTANT: invoke this skill before the FIRST tool call of any session angenshijin-compressinterfacex-co-jp8.4K自然言語メモリファイル（CLAUDE.md, todos, 設定）を原始人形式に圧縮し入力トークン削減。 技術内容・コード・URL・構造は完全保持。圧縮版が原ファイルを上書き、人間可読版は FILE.original.md として保存。「/genshijin-compress <filepath>」「メモリファイル圧縮」で起動。genshijin-crewinterfacex-co-jp8.4K原始人スタイル subagent への委譲判断ガイド。`genshijin-investigator` (コード位置特定)、 `genshijin-builder` (1-2ファイル編集)、`genshijin-reviewer` (diff レビュー) を inline作業 or vanilla `Explore` の代わりにスポーンするタイミングを示す。subagent 出力は原始人圧縮 → 主コンテキストに戻る tool-result が約60%縮小 → 長セッション持続。 Trigger: 「subagent 委譲」「genshijin-crew 使用」「investigator/builder/reviewer 起動」「コンテキスト節約」「圧縮 agent 出力」。gemini-agents-apigoogle8KManages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations.claude-automation-recommenderanthropics7.9KAnalyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.n8n-mcp-tools-expertczlonkowski7.8KExpert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, organizing workflows into folders, managing credentials, auditing instance security, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns. IMPORTANT — Always consult this skill before calling any n8n-mcp tool — it prevents common mistakes like wrong nodeType formats, incorrect parameter structures, acargo-aigetcargohq7.7KBuild and configure AI agents inside Cargo — create an agent, choose its model and temperature, write its prompt, attach knowledge for retrieval (RAG), connect MCP tool servers, manage memories, and deploy releases. Triggers: \"create an agent\", \"make an agent that\", \"give the agent our docs\", \"attach this knowledge base\", \"attach this library to the agent\", \"add resources to the agent release\", \"connect an MCP server\", \"expose our tools as an MCP server\", \"use Cargo from Claude unlazyleonxlnx7.6KEnforces completion discipline for substantial autonomous work by writing acceptance gates before execution, decomposing work with the Depth Tree, running approved checks, and re-verifying evidence before reporting. Use when an agent faces a long or multi-part task, work that has returned half-done, an exhaustive audit or build, parallel leaves or pipelines, or explicit triggers such as /unlazy, $unlazy, "tree N", "gates", and "do not stop until it is done".cargo-contentgetcargohq7.6KManage the knowledge a Cargo workspace holds — upload files (PDF, CSV, text), rename and organize them, and build native or connector-backed libraries that sync from an external source, so agents can retrieve them (RAG). Triggers: \"upload this PDF\", \"add these docs as knowledge\", \"build a knowledge base\", \"sync our help center into Cargo\", \"what files are in the workspace\", \"index this folder\", \"attach our pricing sheet\". Skip when: wiring the file or library into an agent — use camanaged-deep-agentslangchain-ai7.5KINVOKE THIS SKILL when building, testing, or deploying Managed Deep Agents in LangSmith with the mda CLI. Walks a user through their first agent end to end — interviewing them about what they want to build, mapping it onto what MDA can actually do, then scaffolding and deploying it. Covers the file-based project layout; define_deep_agent / defineDeepAgent; instructions, skills, memory, identity, tools, middleware, sandboxes, schedules, channels, and evals; mda init/build/dev/deploy/logs/delete; planning-with-files-zhtothmanadi7.5K用於多步驟 AI 代理工作的持久化檔案規劃。將 task_plan.md、findings.md 與 progress.md 保存在磁碟上，生命週期鉤子會注入選定的專案規劃內容。自動恢復只讀取專案規劃檔案；只有明確執行 session-catchup.py --metadata 才會檢查本機同一專案的代理工作階段中繼資料，--replay 則會輸出有界且以 nonce 框定的摘錄。選用的閘門模式只會在主機支援時要求繼續，而且絕不執行 Markdown 中宣告的命令。此技能沒有網路上傳路徑。適用於研究或需要超過 5 次工具呼叫的工作。觸發詞：任務規劃、專案計畫、制定計畫、分解任務、多步驟規劃、進度追蹤、檔案規劃、幫我規劃、拆解專案amazon-bedrockaws7.3KBuilds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating/porting/converting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedExcepswarmlangchain-ai7.3KDispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.getting-startedcrewaiinc7.3KCrewAI architecture decisions and project scaffolding. Use when starting a new crewAI project, choosing between LLM.call() vs Agent.kickoff() vs Crew.kickoff() vs Flow, scaffolding with 'crewai create flow', setting up YAML config (agents.yaml, tasks.yaml), wiring @CrewBase crew.py, writing Flow main.py with @start/@listen, building experimental conversational Flows with handle_turn()/chat(), or using {variable} interpolation.memory-managementanthropics7.2KTwo-tier memory system that makes Claude a true workplace collaborator. Decodes shorthand, acronyms, nicknames, and internal language so Claude understands requests like a colleague would. CLAUDE.md for working memory, memory/ directory for the full knowledge base.agent-platform-prompt-managementgoogle7.2KManages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.