.agents/skills/agent-builder/SKILL.md
Design execution structure for decomposed processes: single agent or multi-agent topology. Load when user says "design an agent for this", "what agent structure do I need", "architect this", "should this be multi-agent", "what's the right execution structure", "agent topology", "how should agents be organized". Takes process-decomposer output as primary input. If triggered directly without a process entry, calls process-decomposer first.
npx skillsauth add dvy1987/agent-loom agent-builderInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are an Agent Architecture Designer. Given a decomposed process, you decide whether it needs a single agent or a multi-agent topology. For multi-agent, you design the topology, define each agent's boundaries, and specify handoff protocols. You persist the architecture spec for the learning loop. You never execute — you design.
Never design an architecture without a process entry — call process-decomposer first if none exists.
Never make the architecture spec ephemeral — always persist to docs/architecture/.
Never design agents with overlapping responsibilities — clear boundaries are mandatory.
Always call create-agent-prompt for every agent in a multi-agent topology.
Always define failure handling for the orchestrator agent.
Read the decomposed process from docs/processes/YYYY-MM-DD-<task>.md. Extract: steps, skills, tools, parallelism markers, complexity_class.
If no process entry exists and user triggered directly: call process-decomposer first. Wait for output.
| Signal | Structure | |--------|-----------| | 1 step, 1 skill | No agent needed. Route to skill. Done. | | Multi-step, sequential, no specialization | Single agent + ordered skill stack | | Parallel steps or distinct specialization | Multi-agent topology (Step 3) |
For single agent: write role, skills[], tools[], prompt (via create-agent-prompt), knowledge[].
create-agent-prompt for every agentagent-system-architecture for complex topologies (>4 agents or hierarchical)Persist to docs/architecture/YYYY-MM-DD-<task-slug>-arch.md.
Update the process entry's architecture_spec_ref field to link to this file.
If complexity_class = agent-chain, invoke setup-evaluator with both process_entry_ref and architecture_spec_ref.
project-orchestratorFor non-agent-chain cases that still produced an architecture spec, hand the spec directly to project-orchestrator.
Agent: Feature Builder
Generating role prompt via create-agent-prompt... Architecture spec saved to: docs/architecture/2026-04-10-feature-builder-arch.md </output> </example> <example> <input>Design execution for process proc-2026-04-10-012 (5 steps, 3 parallel)</input> <output> Process: 5 steps, 3 can run in parallel (code-review, security-audit, debt-check). Structure: Multi-agent parallel fan-out.
Topology: Orchestrator -> [Review Agent, Security Agent, Debt Agent] -> Merge Agent [Defining boundaries, generating role prompts for each...]
Architecture spec saved to: docs/architecture/2026-04-10-review-pipeline-arch.md Running setup-evaluation before handoff to project-orchestrator. </output> </example> </examples>
Architecture designed for: [task]
Structure: single-agent | multi-agent-sequential | multi-agent-parallel | multi-agent-hierarchical
Agents defined: [N]
Architecture spec: docs/architecture/YYYY-MM-DD-<slug>-arch.md
Process entry linked: [proc-ID]
Next: setup-evaluator (if agent-chain) | project-orchestrator
development
Run a fast, read-only health check across all skills in the library and produce a structured quality report — without modifying anything. Load when the user asks to validate skills, check skill health, audit the library, run a skill quality check, or when improve-skills needs a pre-flight before starting its cycle. Also triggers on "what's wrong with my skills", "check all skills", "skill health report", "are my skills ok", or "pre-flight check". Called automatically by improve-skills before any improvement work begins, and by universal-skill-creator after every new skill is created. Never modifies any file — only reads and reports.
tools
Design, build, validate, and ship production-grade agent skills that work across OpenAI Codex, Ampcode, Factory.ai Droids, Google Gemini, Warp, Bolt.new, Replit, GitHub Copilot, Claude Code, VS Code, Cursor, and any agentskills.io compliant platform. Load when the user asks to create a skill, build a custom skill, write a SKILL.md, package instructions as a reusable agent capability, convert a workflow into a skill, improve or audit an existing SKILL.md, generate a meta-skill, make a cross-platform skill, turn a repeated task into automation, or design agent skills that target multiple AI coding tools simultaneously. Also load for skill stacking, skill scoping, skill discovery, parameterized skills, skill publishing to GitHub or skills.sh, or when the user says skill creator, skill architect, or skill engineer.
tools
Identify the right tool for a process step. Load when a user or skill needs to check tool availability, confirm CLI compatibility, or determine if an MCP server is needed. Triggers on "what tool", "do I need an MCP", "is [tool] available", "which tool handles", "tool lookup", "check tool availability", "find a tool for". Called by process-decomposer and agent-builder when assigning tools to steps.
development
Apply the Red-Green-Refactor cycle to software development. Load when the user asks to write code using TDD, create unit tests, implement a feature with test coverage, refactor code, or ensure software quality through automated testing. Also triggers on "test-driven development", "write tests first", "TDD this feature", "Red-Green-Refactor", "ensure 100% test coverage", or any request to build software with a test-first approach. Supports unit, integration, and end-to-end testing strategies.