Agents
1,401 skills.
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kg-extractruvnetExtract entities and relations from source files to build a knowledge graphkg-traverseruvnetPathfinder traversal of the knowledge graph starting from a seed entityloop-workerruvnetRun Ruflo background workers using Claude Code native /loop schedulingmanaged-agentruvnetRun an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtimememory-bridgeruvnetBridge Claude Code auto-memory into AgentDB with ONNX embeddings, deduplicate, and enable unified cross-project searchmemory-managementruvnetAgentDB memory system with HNSW vector search. Provides 150x-12,500x faster pattern retrieval, persistent storage, and semantic search capabilities for learning and knowledge management. Use when: need to store successful patterns, searching for similar solutions, semantic lookup of past work, learning from previous tasks, sharing knowledge between agents, building knowledge base. Skip when: no learning needed, ephemeral one-off tasks, external data sources available, read-only exploration.memory-searchruvnetSOTA semantic search — hybrid (sparse+dense), Graph RAG multi-hop, MMR diversity reranking, recency weightingmonitor-streamruvnetStream live swarm events using the Monitor tool for real-time observabilityneural-trainruvnetTrain SONA + MicroLoRA neural patterns from successful task completions; runs the DISTILL + CONSOLIDATE phases of the 4-step pipelineneural-trainingruvnetNeural pattern training with SONA (Self-Optimizing Neural Architecture), MoE (Mixture of Experts), and EWC++ for knowledge consolidation. Use when: pattern learning, model optimization, knowledge transfer, adaptive routing. Skip when: simple tasks, no learning required, one-off operations.observe-traceruvnetTrace agent execution by collecting spans and building a trace tree for a taskperformance-analysisruvnetComprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarmsReasoningBank IntelligenceruvnetImplement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.ReasoningBank with AgentDBruvnetImplement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.rvf-manageruvnetManage RVF (Ruflo Vector Format) files for portable agent memory and cross-platform transfersession-persistruvnetPersist and restore agent sessions across conversations with state snapshotsstream-chainruvnetStream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflowsswarm-advancedruvnetAdvanced swarm orchestration patterns for research, development, testing, and complex distributed workflowsswarm-initruvnetInitialize a multi-agent swarm with anti-drift configuration. Use when starting a complex multi-file task that needs 3+ coordinated agents (feature implementation, refactor across modules, security audit). Skip for single-file edits or quick questions.V3 MCP OptimizationruvnetMCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.V3 Memory UnificationruvnetUnify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).V3 Swarm Coordinationruvnet15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.vector-embedruvnetGenerate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW indexwasm-agentruvnetCreate and manage sandboxed WASM agents for isolated code executionwasm-galleryruvnetBrowse, publish, and install WASM agents from the community galleryworker-integrationruvnetWorker-Agent integration for intelligent task dispatch and performance trackingworkflow-createruvnetAuthor a workflow — either an MCP workflow template (persisted, lifecycle) or a native .claude/workflows/*.js orchestration script (agent/parallel/pipeline fan-out)workflow-runruvnetRun a workflow — drive an MCP workflow lifecycle (execute/pause/resume/cancel) or invoke + resume a native .claude/workflows/*.js orchestration via the Workflow tooldev-event-kickoffsamberBefore answering any event-organizing request that opens a new project or a new session, run this router first - it maps the task onto the 71-skill samber/dev-event-organizer-skills collection, or says plainly that none fits, and bootstraps or resumes the project's shared context so the next session starts warm. This fires on a conversational state, not on a subject - invoke it at every event project start even when the collection's skills are already in daily use on another event, at every recudeveloper-platform-kickoffsamberBefore starting any developer-platform, public-API, or integration work - or whenever no other platform skill has been chosen - route the task to the right skill in samber/developer-platform-skills, or say plainly that none fits, then bootstrap or resume the project's shared platform context. Fires at every API or platform project start, at each recurring platform review, and whenever routing is unclear. Use whenever the user mentions a developer platform kickoff, a new public API program, an inmcp-server-offeringsamberDesign a SaaS product's MCP server as a product surface AI agents operate - sizing the build investment, curating a 5-15 workflow-tool agent surface instead of mirroring API endpoints, MCP Apps interactive UI, named write-tool safety patterns (scoped credentials, read-only lockdown, human-in-the-loop approval, risk-tiered server-side gates, dry-run preflight, idempotency and spend caps), remote hosting with OAuth 2.1, versioning the tool surface, MCP registry discoverability, and measuring agentcreate-agent-with-sanity-contextsanity-ioBuild AI agents with structured access to Sanity content via Sanity Context. Use when setting up a Sanity-powered chatbot, connecting an AI assistant to Sanity content, or adding client-side tools to an agent. Covers Studio setup, agent implementation, and advanced patterns. Always use this skill when users mention building a chatbot with Sanity, creating an AI assistant for their content, setting up the Sanity Context MCP server, integrating Sanity with Claude/GPT/any LLM, making content searchdial-your-contextsanity-ioInteractive session to create Instructions field content for the Sanity Context MCP server. Use this skill whenever users mention tuning agent context, improving agent responses to Sanity data, configuring MCP instructions, setting up content filters, or when their agent gives wrong results from Sanity queries. Also trigger when users say their agent is confused about schema relationships, needs data-specific guidance, or wants to optimize which content the agent can access.shape-your-agentsanity-ioInteractive session to craft a system prompt for an AI agent powered by the Sanity Context MCP server. Use this skill when users want to define agent personality, set tone/voice, establish boundaries and guardrails, configure refusal behaviors, or control how their agent communicates. Trigger when users mention their agent sounds wrong, needs to refuse certain requests, has the wrong tone, or they want to set communication rules and policies.sequential-thinkingsecondskySystematic step-by-step reasoning with revision and branching. Use for complex problems, multi-stage analysis, design planning, problem decomposition, or encountering unclear scope, alternative approaches needed, revision requirements.claude-automation-recommendersecondskyAnalyze 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.claude-md-improversecondskyAudit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project memory optimization".sap-ai-coresecondskyGuides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models, building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, managing prompt templates via the Prompt Registry, or integrating AI capasap-cloud-sdk-ai-pythonsecondskyIntegrates the SAP Cloud SDK for AI for Python (sap-ai-sdk-gen, formerly generative-ai-hub-sdk) into Python applications. Use when building Python apps with SAP AI Core, Generative AI Hub, or the Orchestration Service: chat completion, embeddings, streaming, LangChain integration, templating, content filtering, data masking, and document grounding. Supports OpenAI GPT models, Llama, Gemini, Amazon Nova, and other foundation models via SAP BTP.fluesfkislevLetting agents control many desktop software, with one pip install, and no MCPs.freerideshaivpidadiManages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates openclaw.json. Use when the user mentions free AI, OpenRouter, model switching, rate limits, or wants to reduce AI costs.cavemanshawncheeToken-saving terse mode — no filler, no narration, just resultssmuxshawnpanaControl tmux panes and communicate between AI agents. Use this skill whenever the user mentions tmux panes, cross-pane communication, sending messages to other agents, reading other panes, managing tmux sessions, or interacting with processes running in tmux. Includes tmux-bridge CLI for agent-to-agent messaging and raw tmux commands for direct session control.advisor-orchestrator-workershubhamsabooUse when a task is too large for one model pass, needs parallel research or generation across many subtasks (like researching a dozen competitors at once), or the user asks to orchestrate multiple models, split work across a model team, run an advisor-worker loop, have a stronger model review the plan while cheap workers execute, or says "too big for one model" or "fan this out". Not for single-file edits or tasks one model handles in one pass.agent-evaluationsickn33Evaluate agent behavior with versioned cases and explicit verifiers. Use when comparing agent or prompt changes, reproducing failures, or running agent regression tests.agent-manager-skillsickn33Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.agent-memory-mcpsickn33A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).agent-orchestration-improve-agentsickn33Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.agent-orchestration-multi-agent-optimizesickn33Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.agent-tool-buildersickn33Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.