agent-builder
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
What this skill does
# Agent Builder Build AI agents for any domain - customer service, research, operations, creative work, or specialized business processes. ## The Core Philosophy > **The model already knows how to be an agent. Your job is to get out of the way.** An agent is not complex engineering. It's a simple loop that invites the model to act: ``` LOOP: Model sees: context + available capabilities Model decides: act or respond If act: execute capability, add result, continue If respond: return to user ``` **That's it.** The magic isn't in the code - it's in the model. Your code just provides the opportunity. ## The Three Elements ### 1. Capabilities (What can it DO?) Atomic actions the agent can perform: search, read, create, send, query, modify. **Design principle**: Start with 3-5 capabilities. Add more only when the agent consistently fails because a capability is missing. ### 2. Knowledge (What does it KNOW?) Domain expertise injected on-demand: policies, workflows, best practices, schemas. **Design principle**: Make knowledge available, not mandatory. Load it when relevant, not upfront. ### 3. Context (What has happened?) The conversation history - the thread connecting actions into coherent behavior. **Design principle**: Context is precious. Isolate noisy subtasks. Truncate verbose outputs. Protect clarity. ## Agent Design Thinking Before building, understand: - **Purpose**: What should this agent accomplish? - **Domain**: What world does it operate in? (customer service, research, operations, creative...) - **Capabilities**: What 3-5 actions are essential? - **Knowledge**: What expertise does it need access to? - **Trust**: What decisions can you delegate to the model? **CRITICAL**: Trust the model. Don't over-engineer. Don't pre-specify workflows. Give it capabilities and let it reason. ## Progressive Complexity Start simple. Add complexity only when real usage reveals the need: | Level | What to add | When to add it | |-------|-------------|----------------| | Basic | 3-5 capabilities | Always start here | | Planning | Progress tracking | Multi-step tasks lose coherence | | Subagents | Isolated child agents | Exploration pollutes context | | Skills | On-demand knowledge | Domain expertise needed | **Most agents never need to go beyond Level 2.** ## Domain Examples **Business**: CRM queries, email, calendar, approvals **Research**: Database search, document analysis, citations **Operations**: Monitoring, tickets, notifications, escalation **Creative**: Asset generation, editing, collaboration, review The pattern is universal. Only the capabilities change. ## Key Principles 1. **The model IS the agent** - Code just runs the loop 2. **Capabilities enable** - What it CAN do 3. **Knowledge informs** - What it KNOWS how to do 4. **Constraints focus** - Limits create clarity 5. **Trust liberates** - Let the model reason 6. **Iteration reveals** - Start minimal, evolve from usage ## Anti-Patterns | Pattern | Problem | Solution | |---------|---------|----------| | Over-engineering | Complexity before need | Start simple | | Too many capabilities | Model confusion | 3-5 to start | | Rigid workflows | Can't adapt | Let model decide | | Front-loaded knowledge | Context bloat | Load on-demand | | Micromanagement | Undercuts intelligence | Trust the model | ## Resources **Philosophy & Theory**: - `references/agent-philosophy.md` - Deep dive into why agents work **Implementation**: - `references/minimal-agent.py` - Complete working agent (~80 lines) - `references/tool-templates.py` - Capability definitions - `references/subagent-pattern.py` - Context isolation **Scaffolding**: - `scripts/init_agent.py` - Generate new agent projects ## The Agent Mindset **From**: "How do I make the system do X?" **To**: "How do I enable the model to do X?" **From**: "What's the workflow for this task?" **To**: "What capabilities would help accomplish this?" The best agent code is almost boring. Simple loops. Clear capabilities. Clean context. The magic isn't in the code. **Give the model capabilities and knowledge. Trust it to figure out the rest.**
Related in Design
contribute
IncludedLocal-only OSS contribution command center. Auto-refreshes the user's in-flight PR and issue state on invoke so conversations start with full context — no need to brief Claude on what's in flight. Helps the user find issues to contribute to on GitHub, builds per-repo dossiers of what each upstream expects (CLA, DCO, branch convention, AI policy, draft-first, review bots, issue templates), runs deterministic gates before any external action so AI-assisted contributions don't reach maintainers as slop. State is markdown-only: candidate files at ~/.contribute-system/candidates/, repo dossiers at ~/.contribute-system/research/, append-only event log at ~/.contribute-system/log.jsonl. No database, no cloud calls. Use when the user asks about their PRs / issues / contributions, wants to find new work to take on, claim an issue, build/refresh a repo's dossier, or draft a Design Issue or PR. Trigger with "/contribute", "what's my PR status", "find a contribution", "claim issue X", "draft a Design Issue for Y", "refresh dossier for Z".
architectural-analysis
IncludedUser-triggered deep architectural analysis of a codebase or scoped subtree across eight modes — information architecture, data flow, integration points, UI surfaces, interaction patterns, data model, control flow, and failure modes. This skill should be used when the user asks to "diagram this codebase," "map the architecture," "show the data flow," "give me an ERD," "trace control flow," "find the integration points," "verify the layout pattern," "audit the UX architecture," or any similar request whose primary deliverable is mermaid diagrams plus cited reports under docs/architecture/. Dispatches haiku/sonnet sub-agents in parallel for per-mode exploration, then verifies every citation mechanically before any node lands in a diagram. Not for one-off prose explanations of code (use code-explanation) or for high-level system design from scratch (use system-design).
mcp
IncludedModel Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
react-native-skia
IncludedDesign, build, debug, and optimise high-polish animated graphics in React Native or Expo using @shopify/react-native-skia, Reanimated, and Gesture Handler. Use when the user wants canvas-driven UI, shaders, paths, rich text, image filters, sprite fields, Skottie, video frames, snapshots, web CanvasKit setup, or performance tuning for custom motion-heavy elements such as loaders, hero art, cards, charts, progress indicators, particle systems, or gesture-driven surfaces. Also use when the user asks for fluid, glow, glass, blob, parallax, 60fps/120fps, or GPU-friendly animated effects in React Native, even if they do not explicitly say "Skia". Do not use for ordinary form/layout work with standard views.
plaid
IncludedProduct Led AI Development — guides founders from idea to launched product. Six capabilities: Idea (discover a product idea), Validate (pressure-test the idea against fatal flaws, problem reality, competition, and 2-week MVP feasibility), Plan (vision intake + document generation), Design (translate image references into a design.md spec), Launch (go-to-market strategy), and Build (roadmap execution). Use when someone says "PLAID", "plaid idea", "help me find an idea", "product idea", "idea from my business", "idea from my expertise", "plaid validate", "validate my idea", "pressure-test", "is this idea good", "find fatal flaws", "validate the problem", "plan a product", "define my vision", "generate a PRD", "product strategy", "plaid design", "design from image", "translate image to design", "create design.md", "extract design tokens", "plaid launch", "go-to-market", "launch plan", "GTM strategy", "launch playbook", "plaid build", "build the app", "start building", or "execute the roadmap".
nextjs-framer-motion-animations
IncludedAdds production-safe Motion for React or Framer Motion animations to Next.js apps, including reveal, hover and tap micro-interactions, whileInView, stagger, AnimatePresence, layout and layoutId transitions, reorder, scroll-linked UI, and lightweight route-content transitions. Use when the user asks to add, refactor, or debug Motion or Framer Motion in App Router or Pages Router codebases, especially around server/client boundaries, reduced motion, LazyMotion, bundle size, hydration, or route transitions. Avoid for GSAP-style timelines, WebGL or 3D scenes, heavy scroll storytelling, or CSS-only effects unless Motion is explicitly requested.