lawyer-analyst
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learning-path-builder
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lsp-setup
Auto-discovers and configures Language Server Protocol (LSP) servers for your project's languages
markitdown
Convert documents (PDF, Word, Excel, PowerPoint, images, HTML) to Markdown using microsoft/markitdown. Use for document analysis, content extraction, preprocessing for LLMs, or batch document conversion. Supports images with OCR/LLM descriptions, audio transcription, and ZIP archives.
mcp-manager
Conversational interface for managing MCP (Model Context Protocol) server configurations in Claude Code
meeting-synthesizer
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dspy-output-refinement-constraints
This skill should be used when the user asks to "refine DSPy outputs", "enforce constraints", "use dspy.Refine", "select best output", "use dspy.BestOfN", mentions "output validation", "constraint checking", "multi-attempt generation", "reward function", or needs to improve output quality through iterative refinement or best-of-N selection with custom constraints.
dspy-miprov2-optimizer
This skill should be used when the user asks to "optimize a DSPy program", "use MIPROv2", "tune instructions and demos", "get best DSPy performance", "run Bayesian optimization", mentions "state-of-the-art DSPy optimizer", "joint instruction tuning", or needs maximum performance from a DSPy program with substantial training data (200+ examples).
dspy-haystack-integration
This skill should be used when the user asks to "integrate DSPy with Haystack", "optimize Haystack prompts using DSPy", "use DSPy to improve Haystack pipeline", mentions "Haystack pipeline optimization", "combining DSPy and Haystack", "extract DSPy prompt for Haystack", or wants to use DSPy's optimization capabilities to automatically improve prompts in existing Haystack pipelines.
dspy-optimize-anything
Universal text artifact optimizer using GEPA's optimize_anything API for code, prompts, agent architectures, configs, and more
dspy-rag-pipeline
This skill should be used when the user asks to "build a RAG pipeline", "create retrieval augmented generation", "use ColBERTv2 in DSPy", "set up a retriever in DSPy", mentions "RAG with DSPy", "context retrieval", "multi-hop RAG", or needs to build a DSPy system that retrieves external knowledge to answer questions with grounded, factual responses.
dspy-react-agent-builder
This skill should be used when the user asks to "create a ReAct agent", "build an agent with tools", "implement tool-calling agent", "use dspy.ReAct", mentions "agent with tools", "reasoning and acting", "multi-step agent", "agent optimization with GEPA", or needs to build production agents that use tools to solve complex tasks.
dspy-gepa-reflective
This skill should be used when the user asks to "optimize an agent with GEPA", "use reflective optimization", "optimize ReAct agents", "provide feedback metrics", mentions "GEPA optimizer", "LLM reflection", "execution trajectories", "agentic systems optimization", or needs to optimize complex multi-step agents using textual feedback on execution traces.
dspy-signature-designer
This skill should be used when the user asks to "create a DSPy signature", "define inputs and outputs", "design a signature", "use InputField or OutputField", "add type hints to DSPy", mentions "signature class", "type-safe DSPy", "Pydantic models in DSPy", or needs to define what a DSPy module should do with structured inputs and outputs.
dspy-simba-optimizer
This skill should be used when the user asks to "optimize with SIMBA", "use Bayesian optimization", "optimize agents with custom feedback", mentions "SIMBA optimizer", "mini-batch optimization", "statistical optimization", "lightweight optimizer", or needs an alternative to MIPROv2/GEPA for programs with rich feedback signals.
dspy-bootstrap-fewshot
This skill should be used when the user asks to "bootstrap few-shot examples", "generate demonstrations", "use BootstrapFewShot", "optimize with limited data", "create training demos automatically", mentions "teacher model for few-shot", "10-50 training examples", or wants automatic demonstration generation for a DSPy program without extensive compute.
dspy-finetune-bootstrap
This skill should be used when the user asks to "fine-tune a DSPy model", "distill a program into weights", "use BootstrapFinetune", "create a student model", "reduce inference costs with fine-tuning", mentions "model distillation", "teacher-student training", or wants to deploy a DSPy program as fine-tuned weights for production efficiency.
dspy-evaluation-suite
This skill should be used when the user asks to "evaluate a DSPy program", "test my DSPy module", "measure performance", "create evaluation metrics", "use answer_exact_match or SemanticF1", mentions "Evaluate class", "comparing programs", "establishing baselines", or needs to systematically test and measure DSPy program quality with custom or built-in metrics.
dspy-custom-module-design
This skill should be used when the user asks to "create custom DSPy module", "design a DSPy module", "extend dspy.Module", "build reusable DSPy component", mentions "custom module patterns", "module serialization", "stateful modules", "module testing", or needs to design production-quality custom DSPy modules with proper architecture, state management, and testing.
dspy-debugging-observability
This skill should be used when the user asks to "debug DSPy programs", "trace LLM calls", "monitor production DSPy", "use MLflow with DSPy", mentions "inspect_history", "custom callbacks", "observability", "production monitoring", "cost tracking", or needs to debug, trace, and monitor DSPy applications in development and production.
dspy-advanced-module-composition
This skill should be used when the user asks to "compose DSPy modules", "use Ensemble optimizer", "combine multiple programs", "use dspy.MultiChainComparison", mentions "ensemble voting", "module composition", "sequential pipelines", or needs to build complex multi-module DSPy programs with ensemble patterns or multi-chain comparison.
style-guide
Apply language-specific style guide rules to your code. Use when writing or reviewing code to ensure consistency with best practices.
track-manager
Manage Conductor tracks, phases, and tasks. Use when working with track status, updating task markers, or navigating between tracks.
context-loader
Load project context efficiently for Conductor workflows. Use when starting work on a track, implementing features, or needing project context without consuming excessive tokens.
pact-architecture-patterns
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pact-prepare-research
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worktree-cleanup
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pact-security-patterns
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pact-testing-strategies
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pact-agent-teams
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pact-coding-standards
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n8n-workflow-patterns
Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, or scheduled tasks.
pact-memory
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worktree-setup
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n8n-expression-syntax
Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expression errors, or working with webhook data in workflows.
n8n-code-python
Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in n8n Code nodes.
n8n-code-javascript
Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with $helpers, working with dates using DateTime, troubleshooting Code node errors, or choosing between Code node modes.
n8n-validation-expert
Interpret validation errors and guide fixing them. Use when encountering validation errors, validation warnings, false positives, operator structure issues, or need help understanding validation results. Also use when asking about validation profiles, error types, or the validation loop process.
n8n-node-configuration
Operation-aware node configuration guidance. Use when configuring nodes, understanding property dependencies, determining required fields, choosing between get_node detail levels, or learning common configuration patterns by node type.
n8n-mcp-tools-expert
Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns.
r3f-postprocessing
React Three Fiber post-processing - @react-three/postprocessing, bloom, DOF, screen effects. Use when adding visual effects, color grading, blur, glow, or creating custom screen-space shaders.
r3f-physics
React Three Fiber physics with Rapier - RigidBody, colliders, forces, joints, sensors. Use when adding physics simulation, collision detection, character controllers, or creating interactive physics-based experiences.
r3f-textures
React Three Fiber textures - useTexture, texture loading, environment maps, texture configuration. Use when loading images, working with PBR texture sets, cubemaps, HDR environments, or optimizing texture usage.
r3f-shaders
React Three Fiber shaders - GLSL, shaderMaterial, uniforms, custom effects. Use when creating custom visual effects, modifying vertices, writing fragment shaders, or extending built-in materials.
r3f-interaction
React Three Fiber interaction - pointer events, controls, gestures, selection. Use when handling user input, implementing click detection, adding camera controls, or creating interactive 3D experiences.
r3f-animation
React Three Fiber animation - useFrame, useAnimations, spring physics, keyframes. Use when animating objects, playing GLTF animations, creating procedural motion, or implementing physics-based movement.
r3f-fundamentals
React Three Fiber fundamentals - Canvas, hooks (useFrame, useThree), JSX elements, events, refs. Use when setting up R3F scenes, creating components, handling the render loop, or working with Three.js objects in React.
r3f-geometry
React Three Fiber geometry - built-in shapes, BufferGeometry, instancing with Drei. Use when creating 3D shapes, custom meshes, point clouds, lines, or optimizing with instanced rendering.
r3f-lighting
React Three Fiber lighting - light types, shadows, Environment component, IBL. Use when adding lights, configuring shadows, setting up environment lighting, or optimizing lighting performance.
r3f-loaders
React Three Fiber asset loading - useGLTF, useLoader, Suspense patterns, preloading. Use when loading 3D models, textures, HDR environments, or managing loading states.
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