Agents
1,401 skills.
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huashu-prompt-savealchaincyf自动识别Prompt类型并分类保存（技术/内容/教学/产品/通用）。当用户提到"保存prompt"、"记录prompt"、"整理prompt"时使用。ilya-sutskever-perspectivealchaincyfIlya Sutskever的思维框架与表达方式。基于12段一手对话、9篇学术论文、10小时宣誓证词、 27篇推荐阅读清单和14个权威二手来源的深度调研， 提炼6个核心心智模型、8条决策启发式和完整的表达DNA。 用途：作为思维顾问，用Ilya的视角分析AI技术方向、安全策略、研究品味。 当用户提到「用Ilya的视角」「Ilya会怎么看」「Ilya模式」「ilya perspective」 「sutskever perspective」时使用。 即使用户只是说「帮我用Ilya的角度想想」「如果Ilya会怎么做」「切换到Ilya」也应触发。alchemy-mcpalchemyplatformUse the Alchemy MCP server (`https://mcp.alchemy.com/mcp`) for live blockchain data and admin work when MCP is wired into your AI client and the Alchemy CLI is NOT installed locally. Exposes 159 tools across 100+ chains for token prices, NFT metadata, transactions, simulation, tracing, account abstraction, Solana DAS, and app management. Use for live querying, analysis, admin work, or on-machine agent work — not for application code that ships to production. For application code, use the `alchemtoken-optimizeralexgreenshAudit a Claude Code or Codex setup for context-window waste, then fix it and measure the savings. Use when context feels tight.skill-upperalibabaCapture and review Agent Skill observations, and create, run, diagnose, or iteratively improve Skill evaluations (evals) with the skill-up CLI. Use when the user asks to record explicitly attributed Skill usage or feedback; review observations; turn an approved observation into a regression case; evaluate, test, regress, verify, fix, improve, iterate, or evolve a Skill; add or strengthen eval cases; write eval.yaml/case.yaml; run skill-up run/validate/list-cases/report/import/init; or migrate fragent-designeralirezarezvaniUse when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agenagent-protocolalirezarezvaniInter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.agent-workflow-designeralirezarezvaniDesign production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.agenthubalirezarezvaniMulti-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.autoresearch-agentalirezarezvaniAutonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation commboardalirezarezvaniRead, write, and browse the AgentHub message board for agent coordination. Use when the user runs /hub:board or asks to post, read, or inspect coordination messages between competing AgentHub agents.context-enginealirezarezvaniLoads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls. Use when starting any C-suite advisor session, when context looks stale or missing, or before sending company data to an external service.engineering-advanced-skillsalirezarezvaniIndex of 37 advanced engineering agent skills for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Use when browsing or choosing among the POWERFUL-tier engineering skills: agent design, RAG, MCP servers, CI/CD, database design, observability, security auditing, changelog/release automation, reliability (SLO/chaos/flags/operators), platform ops.evalalirezarezvaniEvaluate and rank agent results by metric or LLM judge for an AgentHub session. Use when the user runs /hub:eval or asks to score, compare, or pick a winner among completed AgentHub agents.extractalirezarezvaniTurn a proven pattern or debugging solution into a standalone reusable skill with SKILL.md, reference docs, and examples. Use when the user runs /si:extract or asks to package a recurring solution from memory into a skill.handoffalirezarezvaniCompact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or per-project .handoff/), redact secrets before write, suggest skills for the next session, and auto-load the latest handoff on the next SessionStart. First-run setup asks where to save so the project folder never gets cluttered. Use when the user says 'hand this off', 'handoff doc', 'summarize this for a new session', 'compact this conversation', 'I'mloopalirezarezvaniStart an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling. Use when the user runs /ar:loop or asks to run an autoresearch experiment continuously on a schedule.mcp-server-builderalirezarezvaniDesign and ship production-ready MCP (Model Context Protocol) servers from OpenAPI contracts instead of hand-written tool wrappers. Python and TypeScript support, schema validation, safe evolution. Use when exposing an existing API as an MCP server, building tool integrations for Claude or Codex or Cursor, or scaffolding an MCP project from scratch.promotealirezarezvaniGraduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote or asks to make a learned behavior permanent.prompt-engineer-toolkitalirezarezvaniTurns marketing prompts into tested, versioned production assets: A/B prompt evaluation against structured test cases, immutable prompt version history with diffs, ready-to-use marketing prompt templates (ad copy, email campaigns, social posts, landing pages, SEO meta), and an LLM-governance playbook for marketing teams (claim discipline, disclosure rules, human-review gates). Use when a marketing team relies on AI-generated content and needs prompt quality to be measurable and safe — or when thrag-architectalirezarezvaniUse when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality (precision@k, recall@k, NDCG). Examples: 'design a RAG system for our docs', 'what chunk size should I use for this corpus', 'evaluate my retriever against ground truth'. NOT for general LLM cost tuning (use llm-cost-optimizer) or agent loops over retrieval (use agenthub).rememberalirezarezvaniExplicitly save important knowledge to auto-memory with timestamp and context. Use when a discovery is too important to rely on auto-capture.self-evalalirezarezvaniHonestly evaluate AI work quality using a two-axis scoring system. Use after completing a task, code review, or work session to get an unbiased assessment. Detects score inflation, forces devil's advocate reasoning, and persists scores across sessions.self-improving-agentalirezarezvaniCurate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.senior-prompt-engineeralirezarezvaniUse when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools.setupalirezarezvaniSet up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator. Use when the user runs /ar:setup or asks to start optimizing a file with the autoresearch loop.skill-testeralirezarezvaniValidate, test, and score the quality of skills within the claude-skills ecosystem. Comprehensive meta-skill: structure validation, Python script testing (syntax + imports + runtime + output format), multi-dimensional quality scoring with letter grades and tier classification (BASIC/STANDARD/POWERFUL). Use when authoring a new skill, auditing existing skills for tier promotion, setting up pre-commit hooks for skill quality, or integrating skill QA into CI.spawnalirezarezvaniLaunch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.write-a-skillalirezarezvaniCreate new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, build, or author a new skill.alibabacloud-bailian-rag-knowledgebasealiyunAlibaba Cloud Bailian Knowledge Base Retrieval Tool. Use HTTPS API to query and retrieve knowledge base content. Use when: User needs to query knowledge base, retrieve document content, or answer questions based on knowledge base. Prerequisites: (1) Configure DashScope API Key (2) Activate Bailian Knowledge Base service.skybridgealpic-aiGuide developers through creating and updating ChatGPT and MCP apps. Covers the full lifecycle: brainstorming ideas against UX guidelines, bootstrapping projects, implementing tools/views, debugging, running dev servers, deploying and connecting apps to ChatGPT. Use when a user wants to create or update a ChatGPT app, MCP app, MCP server or use the Skybridge framework.gemini-computer-useam-willBuild and run Gemini 2.5 Computer Use browser-control agents with Playwright. Use when a user wants to automate web browser tasks via the Gemini Computer Use model, needs an agent loop (screenshot → function_call → action → function_response), or asks to integrate safety confirmation for risky UI actions.llm-councilam-willOrchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.role-creatoram-willCreate and update Codex custom agents using standalone custom-agent TOML files.swarm-planneram-will[EXPLICIT INVOCATION ONLY] Creates dependency-aware implementation plans optimized for parallel multi-agent execution.groove-admin-claude-hooksandreadellacorteInstall groove's Claude Code native shell hooks into .claude/settings.json. Enables deterministic session-end reminders, git activity capture, automatic session-capture drafts, and managed-path protection.groove-admin-cursor-hooksandreadellacorteInstall groove's Cursor native hooks into .cursor/hooks.json. Enables compaction-safe re-priming, session-end reminders, git activity capture, automatic session-capture drafts, and managed-path protection.groove-utilities-memory-doctorandreadellacorteCheck memory backend health and configuration.groove-utilities-memory-graduateandreadellacorteGraduate a workflow insight from learned/<topic>.md into AGENTS.md as a permanent constraint. Use when a lesson is stable enough to apply to every future session.groove-utilities-memory-installandreadellacorteSet up memory backend and configuration.groove-utilities-memory-mistakesandreadellacorteLog a workflow mistake, fix its root cause, and graduate the lesson to learned memory. Use when the agent makes an error you want to prevent recurring.groove-utilities-memory-promisesandreadellacorteCapture and resolve deferred items from a session ('we'll come back to that'). Use $ARGUMENTS as the promise text, or --list / --resolve N.groove-utilities-primeandreadellacorteLoad groove workflow context into the conversation. Run at the start of every session.ralph-loop-workflowandrelandgrafRun a coding agent in an autonomous loop via a /ralph command, gated by a preflight check that every CLI is installed, linked, and authenticated. Use when driving long-running autonomous development from a wide, outcome-focused prompt.vault-skill-factoryar9avGenerate a portable, self-contained Agent Skill from mature, curated Obsidian wiki pages — turning a cluster of verified knowledge into a reusable "digital expert" (SKILL.md + references/). Use this skill when the user says "/vault-skill-factory", "make a skill from my wiki", "turn these pages into a skill", "generate an agent skill from my vault", "package my notes on X as a skill", "build a domain-expert skill from my wiki", or wants to distill recurring, mature wiki knowledge into a shareablerecallarjunkmrmSearch past Claude Code, Codex, pi and Grok sessions. Triggers: /recall, "search old conversations", "find a past session", "recall a previous conversation", "search session history", "what did we discuss", "remember when we"laravel-ai-sdkasyrafhussinLaravel AI SDK for building AI-powered features. Use when creating agents, generating images or audio, working with embeddings, vector search, or testing AI features. Triggers on tasks involving laravel/ai, AI agents, tool-calling, structured output, streaming, embeddings, reranking, or AI faking in tests.laravel-mcpasyrafhussinLaravel MCP server development. Use when building MCP servers, tools, prompts, or resources for AI client integration. Triggers on tasks involving laravel/mcp, MCP tools, MCP prompts, MCP resources, or AI client protocols.atxpatxp-devAgent wallet, identity, and paid tools in one package. Register an agent, fund it via Stripe or USDC, then use the balance for web search, AI image generation, AI video generation, AI music creation, X/Twitter search, email send/receive, SMS and voice calls, contacts management, and 100+ LLM models. The funding and identity layer for autonomous agents that need to spend money, send messages, make phone calls, or call paid APIs.atxp-memoryatxp-devAgent memory management — cloud backup, restore, and local vector search of .md memory files