agent-team-builder
Designs and executes multi-agent teams to accomplish complex tasks through iterative collaboration, quality gates, and refinement loops. Use when a user wants to accomplish any non-trivial task that would benefit from specialised agents working in sequence or parallel - e.g. writing an article, building a software feature, conducting research, producing a marketing campaign, designing a system, creating educational content, or any task that naturally decomposes into research → planning → execution → review → refinement stages. Triggers on phrases like "build me a team to...", "use agents to...", "orchestrate agents for...", or when a task is complex enough that a single agent would benefit from decomposition into specialists.
What this skill does
# Agent Team Builder Design and execute a bespoke multi-agent team for any complex task. Always follow these four phases in order. ## Phase 1: Task Intake Ask the user the following (combine into one message, avoid multiple rounds of questioning): **Required:** - What is the task goal and any key constraints? - What does "done well" look like? (success criteria) - Tone, style, or audience if relevant **Quality gate preferences** (for each major stage): - Human approval: user reviews output and decides pass/loop - Automated review: a dedicated critic agent decides pass/loop, user only sees final output - Offer to configure per-stage during blueprint review Use `AskUserQuestion` for structured intake where choices are discrete. Use free-text follow-up for open-ended requirements. ## Phase 2: Team Design After intake, design the agent team: 1. **Decompose** the task into 4–8 specialist roles. See `references/team-patterns.md` for role libraries by task category. 2. **Define the workflow**: sequential pipeline, parallel branches, or hybrid. Most tasks follow: `Research → Plan → Execute → Review → Refine → Finalise`. 3. **Assign quality gates**: at each handoff point, decide (based on user preferences) whether the gate is human or automated (critic agent). 4. **Define loop conditions**: what triggers a revision loop vs. passing the gate? Be explicit. 5. **Name the team**: short kebab-case slug (e.g. `article-team`, `feature-team`). ## Phase 3: Blueprint Presentation Present the team design for approval before spawning anything. Format: ``` ## Team: [team-name] **Goal:** [one sentence] ### Agents | # | Role | Responsibility | Agent Type | |---|------|---------------|------------| | 1 | Researcher | ... | general-purpose | | 2 | Planner | ... | general-purpose | ... ### Workflow [Stage 1: Role → Role] → [GATE: human/automated] → [Stage 2: Role → Role] → ... ### Quality Gates - Gate 1 (after [stage]): [human/automated] — passes when: [criterion] - Gate 2 (after [stage]): [human/automated] — passes when: [criterion] ### Loop Conditions - If Gate 1 fails: [specific revision instruction to agent N] - Max iterations: [N] before escalating to user ``` Wait for explicit user approval. Offer to adjust roles, gates, or workflow before proceeding. ## Phase 4: Execution After approval, execute the team. See `references/execution-guide.md` for full tool syntax and patterns. **Execution sequence:** 1. Create the team with `TeamCreate` 2. Create all tasks with `TaskCreate` (establish dependencies with `addBlockedBy`) 3. Spawn the orchestrator agent via the `Task` tool — this agent manages all other agents 4. The orchestrator: spawns worker agents, monitors task completion, enforces quality gates, routes revision loops, and shuts down the team when done **Orchestrator responsibilities (communicate clearly in its prompt):** - Spawn each worker agent in sequence/parallel per the approved workflow - At each quality gate: run the gate (human via `AskUserQuestion` or automated via a critic `Task`) - On gate failure: send revision instructions back to the relevant agent, increment loop counter - On max iterations exceeded: surface the issue to the user and ask how to proceed - On all gates passed: compile final output and deliver to user, then shut down team **Keep the user informed:** After spawning, tell the user what's running and where to watch for gate approvals (if any are human-gated). ## Key Principles - **Iterative by default**: every pipeline should have at least one refinement loop - **Explicit gate criteria**: vague gates (e.g. "good quality") cause infinite loops — make criteria specific and measurable - **Max iterations**: always set a maximum (default: 3) to prevent runaway loops - **Fail loudly**: if an agent produces unusable output, escalate to the user rather than silently looping - **Right-size the team**: 4–6 agents is the sweet spot; more adds coordination overhead without quality gains
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