智能体
Agent 规划、多步流程与编排
moai-workflow-ddd
modu-ai
Domain-Driven Development workflow specialist using ANALYZE-PRESERVE-IMPROVE cycle for behavior-preserving code transformation. Use when refactoring legacy code, improving code structure without functional changes, reducing technical debt, or performing API migration with behavior preservation. Do NOT use for writing new tests (use moai-workflow-testing instead) or creating new features from scratch (use expert-backend or expert-frontend instead).
moai-foundation-thinking
modu-ai
Structured thinking toolkit combining Critical Evaluation, Diverge-Converge Brainstorming, and Deep Questioning frameworks for creative problem-solving and rigorous analysis. Use when generating ideas, evaluating proposals, questioning assumptions, or exploring solution spaces systematically. Do NOT use for architecture decisions (use moai-foundation-philosopher instead) or code quality validation (use moai-foundation-quality instead).
moai-workflow-testing
modu-ai
Comprehensive testing and development workflow specialist combining DDD testing, characterization tests, performance profiling, code review, and quality assurance. Use when writing tests, measuring coverage, creating characterization tests, performing TDD, running CI/CD quality checks, or reviewing pull requests. Do NOT use for debugging runtime errors (use expert-debug agent instead) or code refactoring (use moai-workflow-ddd instead).
pydantic-ai-common-pitfalls
existential-birds
Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.
parallel-code-review
dgalarza
This skill should be used when performing comprehensive code reviews using multiple specialized review agents in parallel. It provides patterns for concurrent execution, decision tracking to prevent redundancy, and consolidated reporting. Use when needing thorough review coverage from multiple perspectives (security, architecture, performance) or when reviewing large changesets.
tdd-workflow
dgalarza
Use this skill whenever you are implementing a feature using TDD.
lobster-dev
the-omics-os
Develop, extend, and contribute to Lobster AI — the multi-agent self-extending bioinformatics engine. Use when working on Lobster codebase, creating agents/services, understanding architecture, fixing bugs, adding features, or contributing to the open-source project. IMPORTANT: Before creating new agents or packages, follow the planning workflow first (see "What To Do Based On Your Task" → planning-workflow.md). Trigger phrases: "add agent", "create service", "extend lobster", "contribute", "understand architecture", "how does X work in lobster", "fix bug", "add feature", "write tests", "lobster development", "agent development", "bioinformatics code", "build a new agent for", "add support for", "create plugin", "new domain"
convert-github-issue-to-discussion
freekmurze
Convert GitHub issues to discussions using agent-browser. Use when asked to convert, move, or change an issue to a discussion. Requires agent-browser installed and user to log in via headed browser.
lobster-use
the-omics-os
Runs bioinformatics analysis with Lobster AI -- single-cell RNA-seq, bulk RNA-seq, genomics (VCF/GWAS), proteomics (mass spec/affinity), metabolomics (LC-MS/GC-MS/NMR), machine learning (feature selection, survival analysis), drug discovery, literature search, dataset discovery, and visualization. Use when working with biological data, omics analysis, or bioinformatics tasks. Covers: H5AD, CSV, VCF, PLINK, 10X, mzML formats, GEO/SRA/PRIDE/MetaboLights accessions. TRIGGER PHRASES: "analyze cells", "search PubMed", "download GEO", "run QC", "cluster", "find markers", "differential expression", "UMAP", "volcano plot", "single-cell", "RNA-seq", "VCF", "GWAS", "proteomics", "mass spec", "metabolomics", "MetaboLights", "LC-MS", "metabolite", "feature selection", "survival analysis", "biomarker", "bioinformatics", "drug discovery", "pharmacogenomics", "variant annotation" ASSUMES: Lobster is installed and configured. For setup issues, tell user to run lobster config-test and fix any errors before proceeding.
pipeline
ReinaMacCredy
Sequential agent chains with context passing. Run agents in series where each stage receives output from prior stages.
tool-design
guanyang
This skill should be used when the user asks to "design agent tools", "create tool descriptions", "reduce tool complexity", "implement MCP tools", or mentions tool consolidation, architectural reduction, tool naming conventions, or agent-tool interfaces.
project-development
guanyang
This skill should be used when the user asks to "start an LLM project", "design batch pipeline", "evaluate task-model fit", "structure agent project", or mentions pipeline architecture, agent-assisted development, cost estimation, or choosing between LLM and traditional approaches.
context-optimization
guanyang
This skill should be used when the user asks to "optimize context", "reduce token costs", "improve context efficiency", "implement KV-cache optimization", "partition context", or mentions context limits, observation masking, context budgeting, or extending effective context capacity.
filesystem-context
guanyang
This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.
evaluation
guanyang
This skill should be used when the user asks to "evaluate agent performance", "build test framework", "measure agent quality", "create evaluation rubrics", or mentions LLM-as-judge, multi-dimensional evaluation, agent testing, or quality gates for agent pipelines.
bdi-mental-states
guanyang
This skill should be used when the user asks to "model agent mental states", "implement BDI architecture", "create belief-desire-intention models", "transform RDF to beliefs", "build cognitive agent", or mentions BDI ontology, mental state modeling, rational agency, or neuro-symbolic AI integration.
hosted-agents
guanyang
This skill should be used when the user asks to "build background agent", "create hosted coding agent", "set up sandboxed execution", "implement multiplayer agent", or mentions background agents, sandboxed VMs, agent infrastructure, Modal sandboxes, self-spawning agents, or remote coding environments.
multi-agent-patterns
guanyang
This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution.
context-fundamentals
guanyang
This skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Provides foundational understanding of context engineering for AI agent systems.
builder
aj-geddes
Creates custom agents, workflows, and templates for BMAD. Extends BMAD functionality with domain-specific components. Trigger keywords - create agent, create workflow, custom skill, extend BMAD, new template, customize, scaffold skill
Oracle ADK Expert Skill
oci-ai-architects
Claude Code skills for OCI AI Architects. Community-led reference implementations and patterns.
Oracle Solution Design Orchestrator
oci-ai-architects
Version: 1.0 Created: 2026-02-09 Replaces: claude-flow swarm orchestration
tensorlake
tensorlakeai
Tensorlake SDK for agent sandboxes and sandbox-native orchestration. Use when the user mentions tensorlake, or asks about Tensorlake APIs/docs/capabilities. Also use when the user is building AI agents or agentic applications that need stateful sandboxed execution environments for agents and isolated tool calls, with suspend/resume and snapshots for persistence between tasks, or durable workflow orchestration for agents (parallel map/reduce DAGs). Works with any LLM provider (OpenAI, Anthropic), agent framework (LangChain), database, or API as the infrastructure layer.
history
lis186
Smart temporal analysis using git history - Hotspots, Coupling, and Recent Contributors