agent-patterns
Multi-agent design patterns for Claude Code and AI development systems. Covers custom subagents, built-in subagents (Explore/Plan/General-purpose), fungible vs specialized agents, delegation, orchestration, batch workflows, context hygiene, and failure recovery. Use when: designing multi-agent systems, creating custom subagents, delegating bulk operations, orchestrating parallel work, choosing between fungible and specialized agents, configuring agent frontmatter, or debugging agent coordination issues.
What this skill does
# Agent Patterns
Multi-agent design, delegation, and orchestration in Claude Code and AI-assisted development. Default to fungible agents for large-scale software dev; use specialized agents only for peer review or discourse-based workflows.
Subagents in Claude Code are specialized AI assistants that run in isolated context windows with custom system prompts, specific tool access, and independent permissions. They preserve main conversation context by keeping exploration, test runs, and verbose operations out of the primary thread.
Key constraint: subagents cannot spawn other subagents. Multi-step orchestration requires chaining subagents from the main conversation.
## Quick Reference
| Pattern | Description | When to Use |
| ------------------------- | ------------------------------------------------- | -------------------------------------------- |
| Fungible swarm | Identical agents pick tasks from a shared board | Large-scale software dev, resilient systems |
| Sequential pipeline | Each agent builds on previous output | Multi-step workflows with clear dependencies |
| Hierarchical | Manager decomposes, workers execute in parallel | Complex tasks with independent subtasks |
| Peer collaboration | Agents iterate until consensus | Code review, quality-critical outputs |
| Orchestrator delegation | Main conversation chains subagents | Multi-phase workflows, parallel specialists |
| Two-stage review | Spec compliance check, then code quality check | High-stakes code, complex requirements |
| Question-first delegation | Agent asks clarifying questions before proceeding | Ambiguous tasks, expensive-to-redo work |
| Review loop enforcement | Fix-review cycle with max iteration escalation | Any review workflow needing convergence |
| Built-in Subagent | Model | Tools | Purpose |
| ----------------- | -------- | --------- | ------------------------------------------------- |
| Explore | Haiku | Read-only | File discovery, code search, codebase exploration |
| Plan | Inherits | Read-only | Codebase research during plan mode |
| General-purpose | Inherits | All tools | Complex research, multi-step operations |
| Bash | Inherits | Terminal | Running terminal commands in separate context |
| Claude Code Guide | Haiku | Read-only | Answering questions about Claude Code features |
| Configuration | Value |
| ------------------------ | --------------------------------------------------------------------------------- |
| Custom agent location | `.claude/agents/*.md` (project), `~/.claude/agents/*.md` (user) |
| CLI agents | `--agents '{...}'` (session only, JSON format) |
| Plugin agents | Plugin `agents/` directory (lowest priority) |
| Required fields | `name`, `description` |
| Optional fields | `tools`, `disallowedTools`, `model`, `permissionMode`, `skills`, `hooks`, `color` |
| Model values | `sonnet`, `opus`, `haiku`, `inherit` (default) |
| Permission modes | `default`, `acceptEdits`, `dontAsk`, `bypassPermissions`, `plan` |
| Nesting limit | Subagents cannot spawn other subagents (one level only) |
| Foreground vs background | Foreground blocks main conversation; background runs concurrently |
| Batch size | 5-8 items per agent (standard tasks) |
| Parallel agents | 2-4 simultaneously |
## When to Use Subagents vs Main Conversation
| Use Subagents When | Use Main Conversation When |
| --------------------------------------------------------------- | ---------------------------------------------------------- |
| Task produces verbose output (test suites, logs, API responses) | Task needs frequent back-and-forth or iterative refinement |
| Enforcing specific tool restrictions or permissions | Multiple phases share significant context |
| Work is self-contained and can return a summary | Making a quick, targeted change |
| Parallel independent research paths | Latency matters (subagents start fresh and gather context) |
## Tool Access Patterns
| Agent Role | Recommended Tools | Rationale |
| ------------------ | --------------------------------------- | --------------------------------------------- |
| Read-only reviewer | `Read, Grep, Glob` | Cannot modify code; safe for audits |
| File creator | `Read, Write, Edit, Glob, Grep` | NO Bash; avoids heredoc approval spam |
| Script runner | `Read, Write, Edit, Glob, Grep, Bash` | Full access for build/deploy tasks |
| Research agent | `Read, Grep, Glob, WebFetch, WebSearch` | External data access for documentation lookup |
Subagents inherit all tools by default (including MCP tools). Use `tools` as an allowlist or `disallowedTools` as a denylist to restrict access. MCP tools are not available in background subagents.
## Common Mistakes
| Mistake | Correct Pattern |
| ----------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------- |
| Expecting subagents to spawn sub-subagents | Subagents cannot nest; chain subagents from the main conversation instead |
| Giving Bash tool to agents that only create files | Use Write and Edit tools only; Bash causes approval spam from heredoc usage |
| Omitting `disallowedTools` for sensitive operations | Use `disallowedTools` to explicitly deny dangerous tools even when inheriting |
| Spawning too many agents (5+) for a small task | Start with 2-3 agents; coordination overhead outweighs benefit at higher counts |
| Burying critical instructions past line 300 of agent prompt | Put critical rules immediately after frontmatter; models deprioritize late instructions |
| Using specialized agents for large-scale software dev | Use fungible agents with a shared task board; specialized agents create single points of failure |
| Not including "FIX issues found" in delegation prompts | Without explicit action directive, agents only report problems without making changes |
| Setting model to Haiku for content generation | Default to Sonnet; Haiku only for script execution, fast lookups, or pass/fail checks |
| Not writing clear descriptions for custom agents | Claude uses the `description` field to decide when to auto-delegate; vague descriptions prevent delegation |
| Using MCP tools in background subagents | MCP tools are not available in background subagents; run in foreground instead |
| Not preloading skills into subagentsRelated 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
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