agent-teams
Team composition knowledge for Claude Code Agent Teams - when to suggest teams, optimal sizing, spawn prompt patterns
What this skill does
# Agent Teams Composition Skill You have expertise in composing and orchestrating Claude Code Agent Teams. Use this knowledge when the user's task would benefit from parallel multi-session work. ## When to Suggest Agent Teams Proactively suggest agent teams when: - The user asks for comprehensive code review (suggest 3-reviewer team) - The task involves work across multiple layers (frontend + backend + database) - The user describes a bug with unclear root cause (suggest competing hypothesis investigation) - The user wants to evaluate multiple technologies or approaches (suggest research panel) - The task can be clearly split into independent, file-separated workstreams Do NOT suggest agent teams when: - The task is sequential or involves same-file edits - A single session or subagent would suffice - The coordination overhead would exceed the benefit - The user is on a tight token budget ## Team Templates ### Full Review (3 teammates) Security reviewer + Performance reviewer + Test coverage reviewer. Each reviews independently, then lead synthesizes findings. ### Feature Dev (3 teammates) Architect (plan approval required) + Implementer + Test writer. Architect plans first, implementer follows, test writer validates. ### Debug Squad (3-5 teammates) Each teammate investigates a different hypothesis. Adversarial debate structure -- teammates challenge each other's theories. ### Cross-Platform (3 teammates) iOS developer + Android developer + Shared architect. Each platform teammate owns their own directory. Architect coordinates API contracts. ### Full-Stack (3 teammates) Frontend + Backend + Database. Clear file ownership per layer. Coordinate on API contracts first. ### Research Panel (3 teammates) Simplicity advocate + Performance advocate + Devil's advocate. Each evaluates from a different perspective, then synthesize. ## Spawn Prompt Formula Every spawn prompt should include: 1. Role: "You are the [role] teammate responsible for [domain]" 2. Files: "You own files in [directories]. Do not modify files outside your scope." 3. Focus: "Specifically look for / implement [details]" 4. Context: "[Project-specific information the teammate needs]" 5. Deliverable: "Report your findings as [format] / Implement [specific output]" ## Cross-Platform Awareness - macOS and Linux: full support (in-process + tmux split panes) - Windows: in-process mode only (automatic with auto setting) - Always use `--teammate-mode auto` (default) for automatic detection ## Related Documentation - `~/.claude/docs/AGENT-TEAMS.md` - Full guide with examples - `~/.claude/docs/reference/workflows/agent-teams.md` - Decision framework - `~/.claude/commands/assemble-team.md` - Quick team assembly command
Related in AI Agents
skill-development
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reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
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agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
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skill-master
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