composition AI Agent Skills

Browse 646 skills related to composition

himalaya

CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).

orpc-contract-first

Guide for implementing oRPC contract-first API patterns in Dify frontend. Trigger when creating or updating contracts in web/contract, wiring router composition, integrating TanStack Query with typed contracts, migrating legacy service calls to oRPC, or deciding whether to call queryOptions directly vs extracting a helper or use-* hook in web/service.

python-design-patterns

Python design patterns including KISS, Separation of Concerns, Single Responsibility, and composition over inheritance. Use when making architecture decisions, refactoring code structure, or evaluating when abstractions are appropriate.

team-composition-analysis

This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.

web-component-design

Master React, Vue, and Svelte component patterns including CSS-in-JS, composition strategies, and reusable component architecture. Use when building UI component libraries, designing component APIs, or implementing frontend design systems.

vercel-composition-patterns

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

remotion

Best practices and comprehensive guide for Remotion - programmatic video creation in React with animations, compositions, and media handling

VideoReactAnimation+9

autonomous-agents

Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b

react-patterns

Modern React patterns and principles. Hooks, composition, performance, TypeScript best practices.

team-composition-analysis

This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests...

V3 CLI Modernization

CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation.

gemini-imagegen

This skill should be used when generating and editing images using the Gemini API (Nano Banana Pro). It applies when creating images from text prompts, editing existing images, applying style transfers, generating logos with text, creating stickers, product mockups, or any image generation/manipulation task. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images.

search-strategy

Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.

infographic-structure-creator

Generate or update infographic Structure components for this repo (TypeScript/TSX in src/designs/structures). Use when asked to design, implement, or modify structure layouts (list/compare/sequence/hierarchy/relation/geo/chart), including layout logic, component composition, and registration.

legacy-modernizer

Use when modernizing legacy systems, implementing incremental migration strategies, or reducing technical debt. Invoke for strangler fig pattern, monolith decomposition, framework upgrades.

vue-best-practices

MUST be used for Vue.js tasks. Strongly recommends Composition API with `<script setup>` and TypeScript as the standard approach. Covers Vue 3, SSR, Volar, vue-tsc. Load for any Vue, .vue files, Vue Router, Pinia, or Vite with Vue work. ALWAYS use Composition API unless the project explicitly requires Options API.

vue

Vue 3 Composition API, script setup macros, reactivity system, and built-in components. Use when writing Vue SFCs, defineProps/defineEmits/defineModel, watchers, or using Transition/Teleport/Suspense/KeepAlive.

interpreting-culture-index

Use when interpreting Culture Index surveys, CI profiles, behavioral assessments, or personality data. Supports individual interpretation, team composition (gas/brake/glue), burnout detection, profile comparison, hiring profiles, manager coaching, interview transcript analysis for trait prediction, candidate debrief, onboarding planning, and conflict mediation. Handles PDF vision or JSON input.

token-integration-analyzer

Token integration and implementation analyzer based on Trail of Bits' token integration checklist. Analyzes token implementations for ERC20/ERC721 conformity, checks for 20+ unusual token patterns, assesses contract composition and owner privileges, performs on-chain scarcity analysis, and evaluates how protocols handle non-standard tokens. Context-aware for both token implementations and token integrations.

server-components

This skill should be used when the user asks about "Server Components", "Client Components", "'use client' directive", "when to use server vs client", "RSC patterns", "component composition", "data fetching in components", or needs guidance on React Server Components architecture in Next.js.

Svelte Components

Svelte 5 component patterns for the Exceptionless SPA. Runes, reactivity, props, events, snippets, component organization, and shadcn-svelte integration. Keywords: Svelte 5, $state, $derived, $effect, $props, runes, onclick, snippets, {@render}, reactive, component composition, shadcn-svelte

swiftui-expert-skill

Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, modern APIs, Swift concurrency, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI patterns.

media-processing

Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.

ai-multimodal

Process and generate multimedia content using Google Gemini API. Capabilities include analyzing audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understanding images (captioning, object detection, OCR, visual Q&A, segmentation), processing videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extracting from documents (PDF tables, forms, charts, diagrams, multi-page), generating images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

sequential-thinking

Use when complex problems require systematic step-by-step reasoning with the ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.

garmin-health-analysis

Talk to your Garmin data naturally - "what was my fastest speed snowboarding?", "how did I sleep last night?", "what was my heart rate at 3pm?". Access 20+ metrics (sleep stages, Body Battery, HRV, VO2 max, training readiness, body composition, SPO2), download FIT/GPX files for route analysis, query elevation/pace at any point, and generate interactive health dashboards. From casual "show me this week's workouts" to deep "analyze my recovery vs training load".

withings-health

Fetches health data from the Withings API including weight, body composition (fat, muscle, bone, water), activity, and sleep. Use this skill when the user asks about their Withings data, weight history, body metrics, daily steps, sleep quality, or any health measurement from Withings devices.

rlm

Use RLM (Recursive Language Models) for verified code execution, calculations, data analysis, and task decomposition. Executes Python code iteratively until producing verified results - no LLM guessing.

withings-family

Fetches health data from the Withings API for multiple family members including weight, body composition (fat, muscle, bone, water), activity, and sleep. Use this skill when the user asks about their or their family's Withings data, weight history, body metrics, daily steps, sleep quality, or any health measurement from Withings devices.

vue-expert

Use when building Vue 3 applications with Composition API, Nuxt 3, or Quasar. Invoke for Pinia, TypeScript, PWA, Capacitor mobile apps, Vite configuration.

deep-research

Deep Research Agent specializes in complex, multi-step research tasks that require planning, decomposition, and long-context reasoning across tools and files by we-crafted.com/agents/deep-research

component-identification-sizing

tech-leads-club

Identifies architectural components in codebases and calculates size metrics for decomposition planning. Use when analyzing codebase structure, planning monolithic decomposition, identifying oversized components, calculating component statistics, or when the user asks about component analysis, codebase sizing, or architectural decomposition.

legacy-migration-planner

tech-leads-club

Use when planning legacy system migrations, codebase modernization, monolith decomposition, microservices consolidation, cross-language rewrites, or framework upgrades. Invoke for strangler fig pattern, incremental migration strategy, or refactoring roadmaps.

decomposition-planning-roadmap

tech-leads-club

Creates structured decomposition plans and roadmaps for migrating monolithic applications. Use when planning decomposition, creating migration roadmaps, prioritizing decomposition work, tracking decomposition progress, or when the user asks about decomposition planning, migration strategy, or architectural roadmap.

react-composition-patterns

tech-leads-club

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

compose-expert

Advanced Compose Multiplatform UI patterns for shared composables. Use when working with visual UI components, state management patterns (remember, derivedStateOf, produceState), recomposition optimization (@Stable/@Immutable visual usage), Material3 theming, custom ImageVector icons, or determining whether to share UI in commonMain vs keep platform-specific. Delegates navigation to android-expert/desktop-expert. Complements kotlin-expert (handles Kotlin language aspects of state/annotations).

autonomous-skill

Use when a user wants to execute long-running tasks that require multiple sessions to complete. This skill manages task decomposition, progress tracking, and autonomous execution using Claude Code headless mode with automatic continuation. Trigger phrases: "autonomous", "long-running task", "multi-session", "autonomous skill".

Gemini ImageGen

Generate and edit images using Google Gemini's native image generation models (Nano Banana / Nano Banana Pro). Supports text-to-image, image editing with reference images, multi-image composition, and character consistency. Use when the user asks to generate images via Gemini, create AI illustrations, edit photos with Gemini, or needs high-quality image generation with the Google API. Requires GEMINI_API_KEY. Triggers: "generate image with gemini", "nano banana", "gemini image", "create illustration", "AI generate picture", "text to image".

Skills Planner

Plan which skills are needed to fulfill user requirements. Use when the user wants to design an agent workflow, plan skill composition, or determine what skills are needed for a task. Input includes user requirements and existing skills list. Output includes recommended existing skills, new skills to create, and a system prompt for the composed agent.

gemini-imagegen

Generate and edit images using Google Gemini's native image generation models (Nano Banana / Nano Banana Pro). Supports text-to-image, image editing with reference images, multi-image composition, and character consistency. Use when the user asks to generate images via Gemini, create AI illustrations, edit photos with Gemini, or needs high-quality image generation with the Google API. Requires GEMINI_API_KEY. Triggers: "generate image with gemini", "nano banana", "gemini image", "create illustration", "AI generate picture", "text to image".

skills-planner

Plan which skills are needed to fulfill user requirements. Use when the user wants to design an agent workflow, plan skill composition, or determine what skills are needed for a task. Input includes user requirements and existing skills list. Output includes recommended existing skills, new skills to create, and a system prompt for the composed agent.

moai-foundation-philosopher

Strategic thinking framework integrating First Principles Analysis, Stanford Design Thinking, and MIT Systems Engineering for deeper problem-solving. Use when performing architecture decisions, technology selection trade-offs, root cause analysis, cognitive bias detection, or first principles decomposition. Do NOT use for code quality validation (use moai-foundation-quality instead) or implementation workflows (use moai-workflow-ddd instead).

moai-library-shadcn

Provides shadcn/ui component library expertise for React applications with Tailwind CSS. Use when implementing UI components, design systems, or component composition with shadcn/ui, Radix primitives, or Tailwind-based component libraries. Do NOT use for non-React frameworks or custom CSS-only styling (use moai-domain-frontend instead).

moai-workflow-thinking

Sequential Thinking MCP and UltraThink mode for deep analysis, complex problem decomposition, and structured reasoning workflows. Use when performing multi-step analysis, architecture decisions, technology selection trade-offs, breaking change assessment, or when --ultrathink flag is specified. Do NOT use for simple decisions or straightforward implementation tasks.

vue

Use when editing .vue files, creating Vue 3 components, writing composables, or testing Vue code - provides Composition API patterns, props/emits best practices, VueUse integration, and reactive destructuring guidance

vue

Vue.js progressive JavaScript framework. Use when building Vue components, working with reactivity (ref, reactive, computed, watch), or implementing Vue Composition API patterns.

pca-decomposition

Reduce dimensionality of multivariate data using PCA with varimax rotation. Use when you have many correlated variables and need to identify underlying factors or reduce collinearity.

contribution-analysis

Calculate the relative contribution of different factors to a response variable using R² decomposition. Use when you need to quantify how much each factor explains the variance of an outcome.

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