# Team Executor > Multi-agent orchestration that transforms braindumps into executed results. Assembles expert planning teams (3-7 agents), produces comprehensive execution plans, then deploys fresh execution teams for autonomous delivery. Use when the user describes goals, features, projects, or pastes scattered ideas needing organization and execution. Triggers on "build this", "execute this", "make this happen", "plan and build", or any substantial task description. - Skill: `thatjuan/team-executor` (Agent Skill, multi-file: 6 files) - Install (CLI): `npx skillmds@latest add thatjuan/team-executor` - Raw SKILL.md: https://api.skillmd.com/api/skills/thatjuan/team-executor/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: thatjuan (https://skillmd.com/u/thatjuan) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/thatjuan/team-executor --- # Team Executor An autonomous multi-agent orchestration skill that transforms braindumps into executed results through two phases: expert planning and autonomous execution. ## Overview This skill operates in two distinct phases: **Phase 1 — Planning**: Organizes raw input, assembles a team of expert agents, has each analyze the goal from their domain expertise, and produces a comprehensive execution plan. **Phase 2 — Execution**: A fresh team of agents autonomously executes the plan to completion with no human intervention required. The key philosophy: experts plan, experts execute, and the output is production-ready. ## Core Principle: Coding-Agent Execution Model Plans produced by this skill are executed by coding agents, not humans. This changes the decision calculus at every stage: > The implementation will be carried out by coding agents. Human time, speed, and effort estimates DO NOT apply — do not shy away from a more robust solution because a human would find it slow. Account for risk, security, maintainability, and consistency with existing project conventions. Prefer the most robust, well-engineered option that uses existing tooling/styles/components. Do not introduce parallel patterns when an existing one fits. Apply this everywhere the team makes tradeoffs: choosing approaches, resolving conflicts, reviewing the plan, filling in details during execution. Reject solutions only for **risk, security, maintainability, or convention** reasons — never because the work is "a lot" or "would take a human a long time." This is the planning *economics*: human effort cost is not a tiebreaker. What "robust" actually means *in code* — the engineering bar a diff must clear — is defined by the `software-engineer` skill, not here. ## Engineering Is Delegated, Not Embedded team-executor coordinates; it does not hold coding standards, architecture patterns, or software-engineering personas. It keeps the *coordination* judgment — which roles, how many, parallel vs sequential, conflict resolution, phase transitions. The *engineering* judgment lives in the [`software-engineer`](../software-engineer/) skill: the architect/developer/reviewer subject-matter expert and **base engineering layer** for any coding agent. The rule: **any agent that writes, updates, or reviews code is assigned the `software-engineer` skill.** That agent reads it and embodies its standards (the Three Lenses, the Eight Standards, per-domain practice, the review gate). team-executor no longer inlines those standards anywhere. **Graceful degradation (prefer-when-present).** team-executor is independently installable and `software-engineer` may not be present. Use the same prefer-when-present shape `implement-issue` uses for team-executor: - **If `software-engineer` is installed** (surfaced by the Step 2 skill scan at `~/.claude/skills/software-engineer/`, `.claude/skills/software-engineer/`, `../software-engineer/`, `/mnt/skills/software-engineer/`, or a `skills-lock.json` entry): attach it to every coding, architect, and review agent. - **If it is not installed**: fall back to a trimmed generic inline instruction (review/build for production-readiness, security, maintainability, and consistency with existing conventions). Never hard-depend on `software-engineer` or break when it is absent. ## Bundled Resources | File | Purpose | |------|---------| | [agent-templates.md](agent-templates.md) | Persona construction framework and ready-to-use agent templates | | [orchestration-workflow.md](orchestration-workflow.md) | Agent spawning, output collection, conflict resolution, phase transitions | | [scan-project.sh](scan-project.sh) | Gathers project context (directory structure, configs, technologies) for agent prompts | | [init-plan-dirs.sh](init-plan-dirs.sh) | Initializes `docs/plans/` directory structure for agent outputs | --- ## Phase 1: Planning ### Step 1: Organize the Input The user's input is likely a braindump — scattered ideas, goals, requirements, and aspirations mixed together. Your first job is to make sense of it. Read the input carefully and produce a structured interpretation: 1. **Identify distinct goals** — separate intertwined ideas into discrete objectives 2. **Deduplicate** — merge redundant or overlapping items 3. **Fill gaps** — infer missing details that are logically necessary (flag these as inferred) 4. **Establish logical flow** — order goals by dependency and priority 5. **Clarify ambiguity** — resolve vague language into concrete, actionable descriptions Write this organized version to `docs/plans/goal-analysis.md`. This becomes the canonical reference for all agents. ### Step 2: Scan Available Skills Before assembling the team, scan all available skills to understand what specialized capabilities exist. Check these locations for SKILL.md files: - **Claude Code user skills**: `~/.claude/skills/` - **Claude Code project skills**: `.claude/skills/` in the project root - **System skills**: `/mnt/skills/` (Codex and similar platforms) - **Installed skills**: Check `skills-lock.json` in the project root if present ```bash # Discover skills across all known locations for dir in ~/.claude/skills .claude/skills /mnt/skills; do find "$dir" -name "SKILL.md" -type f 2>/dev/null done ``` Read each SKILL.md's frontmatter (name + description) to build a capability inventory. These skills may be assigned to team agents who can benefit from them. Not every agent needs a skill — only assign one when it genuinely matches the agent's role. **Note the engineering base layer.** If the scan surfaces [`software-engineer`](../software-engineer/), it is special: it is the **base engineering layer** to attach to any coding, architect, or review agent (not a role-specific match — the engineering bar every code-touching agent must clear). When it is present, assign it to those agents; when it is absent, fall back to the trimmed inline instruction described under "Engineering Is Delegated, Not Embedded." Stack/SDK skills (`heroui`, `drizzle-orm`, `temporal`, etc.) remain role-specific overlays assigned on top. ### Step 3: Determine If R&D Is Needed Some goals require research before planning can begin. Look for: - References to technologies, APIs, or tools the team may not have full context on - Ambiguous requirements that need investigation - Integration points with external systems - Unfamiliar domains or specialized knowledge areas If R&D is needed, spawn R&D agents first (see [agent-templates.md](agent-templates.md) for the R&D agent template). R&D agents: - Search the codebase and project docs for existing patterns and conventions - Read relevant documentation and source files - Investigate technical feasibility - Document findings in `docs/plans/research/` as markdown files Wait for R&D to complete before assembling the planning team, since R&D findings inform which experts are needed. ### Step 4: Assemble the Planning Team Based on the organized goals and any R&D findings, create a team of 3–7 expert agents. Each agent needs: 1. **A specific persona** — not just a job title, but a complete expert identity with deep domain knowledge, opinions, and a point of view. See [agent-templates.md](agent-templates.md) for persona construction guidelines. 2. **A clear analysis mandate** — what aspect of the goal they're responsible for evaluating 3. **A skill assignment** — any software-domain agent (architect, backend, frontend, devops, QA, security, data) is assigned [`software-engineer`](../software-engineer/) as its engineering skill: the agent reads it and embodies its standards, and team-executor no longer inlines those standards. Optionally add **one** stack/SDK overlay skill that matches the role (`heroui`, `drizzle-orm`, etc.) — base engineering layer plus one overlay (see the skill-assignment exception in [agent-templates.md](agent-templates.md)). Non-software agents get a role-matching skill only when one genuinely fits. If `software-engineer` is not installed, fall back to the trimmed inline instruction (see "Engineering Is Delegated, Not Embedded"). 4. **Access to project context** — point them at relevant files, docs, and the organized goal analysis The team composition covers all necessary perspectives. Common patterns: - **Software projects**: architect, backend engineer, frontend engineer, devops/infra, QA/testing strategist - **Data projects**: data engineer, analyst, ML engineer, domain expert - **Content/creative**: strategist, writer, editor, designer, domain expert - **Infrastructure**: systems architect, security engineer, SRE, networking specialist - **Mixed projects**: pull from multiple patterns as needed Every team includes a **Project Lead** agent whose job is to synthesize all other agents' input into the final plan. ### Step 5: Run the Planning Team Spawn all expert agents. Each agent receives this prompt structure (customize per agent): ``` You are [PERSONA_DESCRIPTION]. ## Your Assignment Analyze the following project goals from your area of expertise. Provide: 1. **Assessment** — your expert evaluation of the goals as they relate to your domain 2. **Approach** — the specific technical/strategic approach you recommend 3. **Steps** — detailed, ordered steps for your domain's contribution 4. **Dependencies** — what you need from other team members 5. **Risks & Mitigations** — what could go wrong in your domain and how to prevent it 6. **Quality Standards** — what "production-ready" means for your deliverables 7. **Critical Details** — things that are easy to overlook but essential to get right ## Project Goals [INSERT contents of docs/plans/goal-analysis.md] ## Project Context [INSERT relevant file paths, existing code structure, docs, etc.] ## Engineering Skill (software-domain agents) Read and follow the `software-engineer` skill before starting — it is your engineering base layer (architect/developer/reviewer SME): [SOFTWARE_ENGINEER_PATH] (If `software-engineer` is not installed, this slot is replaced by a short inline instruction: build/recommend for production-readiness, security, maintainability, and consistency with existing project conventions.) ## Available Skill (if assigned) Read and follow: [STACK_OVERLAY_SKILL_PATH] ## Important - Your output must be actionable by a coding agent — no vague advice - Assume the executor has no context beyond what you provide - Specify exact file paths, commands, configurations, and code patterns - Reference existing project code/patterns when relevant - Everything you recommend must result in production-ready output - Do NOT include timelines, deadlines, or time estimates ## Execution Model The implementation will be carried out by coding agents. Human time, speed, and effort estimates DO NOT apply — do not shy away from a more robust solution because a human would find it slow. Account for risk, security, maintainability, and consistency with existing project conventions. Prefer the most robust, well-engineered option that uses existing tooling/styles/components. Do not introduce parallel patterns when an existing one fits. ``` ### Step 6: Aggregate Into Execution Plan Once all agents have reported back, the **Project Lead** agent synthesizes everything into a single execution plan. If you didn't spawn a separate Project Lead, do this synthesis yourself. The aggregation process: 1. **Collect all agent outputs** — read every agent's analysis 2. **Resolve conflicts** — where agents disagree, choose the approach that best serves the overall goal (document the reasoning). Conflict resolution criteria: risk, security, maintainability, and consistency with existing conventions. Do NOT downgrade to a weaker approach because the stronger one is "more work" — coding agents execute the plan, so human effort cost is not a tiebreaker. 3. **Merge dependencies** — create a unified dependency graph 4. **Order execution** — sequence steps across all domains into a logical execution order 5. **Eliminate redundancy** — remove duplicate steps that multiple agents independently suggested 6. **Add integration points** — where work from different agents connects, add explicit integration steps ### Step 7: Software Development Review Gate **If the project involves software development** (code, APIs, infrastructure, etc.), spawn one additional review-gate agent before finalizing. team-executor does not carry the reviewer's standards — they live in `software-engineer`. **Preferred (when `software-engineer` is installed).** Spawn a review-gate agent, assign it the [`software-engineer`](../software-engineer/) skill, and instruct it to apply the **Reviewer Lens** (`../software-engineer/references/review-gate.md`) to the draft plan as if the plan were a diff awaiting review: ``` You are a review-gate agent. Read and follow the `software-engineer` skill, and apply its Reviewer Lens to the draft execution plan below: [SOFTWARE_ENGINEER_PATH] — specifically references/review-gate.md. ## Your Task Treat the draft plan as a diff awaiting review. For each section: 1. Flag anything that would not survive the review gate / would not pass a production code review 2. Add missing steps an experienced engineer would expect 3. Strengthen vague instructions with specific implementation details 4. Verify the plan follows existing project patterns (check the codebase) The agents executing this plan will follow it literally. Be constructive but thorough. ## Execution Model This plan will be executed by coding agents, not humans. Do NOT recommend simpler/weaker approaches on the grounds that the robust option is "too much work" or "would take a human too long." Flag issues only on risk, security, maintainability, scalability, or convention grounds. If the plan picks a less-robust approach to save effort, push back and recommend the stronger one. ## Execution Plan [INSERT the draft plan] ## Project Codebase [INSERT relevant file tree and key files] ``` **Fallback (when `software-engineer` is not installed).** Spawn the same review-gate agent with this short inline mandate in place of the skill assignment, keeping the Execution Model paragraph above: ``` Review the draft execution plan as if it were a diff awaiting a demanding production review. Flag anything that would not ship: gaps in production-readiness, security, maintainability, or consistency with existing project conventions. Add missing steps, make vague instructions specific, and verify the plan follows existing project patterns (check the codebase). ``` Incorporate this reviewer's feedback into the final plan. ### Step 8: Write the Final Plan Write the finalized plan to `docs/plans/execution-plan.md` using this structure: ```markdown # Execution Plan: [Project Title] ## Overview [2-3 sentence summary of what this plan accomplishes] ## Goals [Numbered list of concrete objectives from the goal analysis] ## Architecture / Approach [High-level approach with key decisions and their rationale] ## Execution Steps ### Phase N: [Phase Name] #### Step N.M: [Step Name] **Objective**: [What this step accomplishes] **Details**: [Specific, detailed instructions — file paths, code patterns, configs, commands] **Inputs**: [What this step needs] **Outputs**: [What this step produces] **Quality Criteria**: [How to verify this step is done correctly] [Repeat for all steps...] ## Integration Points [Where different components connect and how to verify integration] ## Quality Assurance [Testing strategy, validation steps, acceptance criteria] ## Risk Register [Known risks and their mitigations] ## File Structure [Expected project structure after execution] ``` The plan has these properties: - **Self-contained** — an agent with no prior context can execute it - **Specific** — exact file paths, code patterns, command sequences - **Ordered** — steps are sequenced by dependency - **Verifiable** — each step has clear completion criteria - **Production-grade** — the output meets professional standards - **Timeline-free** — no dates, deadlines, or time estimates anywhere - **Effort-agnostic** — superior, robust solutions are chosen over quicker compromises; human effort cost is not a factor in plan decisions (risk, security, maintainability, and convention-fit are) --- ## Phase 2: Execution Phase 2 uses a completely fresh team of agents. They receive only the execution plan and project context — not the Phase 1 deliberation history. This ensures clean execution without planning-phase bias. ### Step 9: Assemble the Execution Team Read `docs/plans/execution-plan.md` and create execution agents based on the plan's phases and steps. Each execution agent: 1. **Has a focused scope** — responsible for a specific phase or group of related steps 2. **Has a complete persona** — expert identity matching the work they'll do (see [agent-templates.md](agent-templates.md)) 3. **Has the right skills** — assign skills that match their work. Any agent that writes, updates, or reviews code is assigned [`software-engineer`](../software-engineer/) as its **base engineering layer** (plus optionally one stack/SDK overlay), exactly as in planning. Execution agents are the ones that actually build, so this is where the engineering bar lands. If `software-engineer` is not installed, fall back to the trimmed inline instruction (see "Engineering Is Delegated, Not Embedded"). 4. **Operates autonomously** — makes all decisions independently based on project context The execution team prompt structure: ``` You are [PERSONA_DESCRIPTION]. ## Your Mission Execute the following steps from the project execution plan. Work autonomously and make all decisions yourself — do not wait for or request human input. ## Decision-Making Guidelines - Root all decisions in the existing project code, docs, and conventions - When multiple valid approaches exist, choose the one most consistent with the codebase - If you encounter ambiguity, choose the most production-appropriate option - Document significant decisions as code comments or in docs/ - You are a coding agent, not a human — do not cut corners or pick a weaker approach because the robust one would take "a long time." Optimize for risk, security, maintainability, and consistency. Effort cost is not a constraint. ## Steps to Execute [INSERT relevant steps from execution-plan.md] ## Project Context [INSERT relevant file paths, existing patterns, dependencies] ## Engineering Skill (if this agent writes/updates/reviews code) Read and follow the `software-engineer` skill before starting — it is your engineering base layer (architect/developer/reviewer SME): [SOFTWARE_ENGINEER_PATH] (If `software-engineer` is not installed, this slot is replaced by a short inline instruction: build for production-readiness, security, maintainability, and consistency with existing project conventions.) ## Available Skill (if assigned) Read and follow: [STACK_OVERLAY_SKILL_PATH] ## Critical Requirements - All output must be production-ready — no TODOs, no placeholders, no stubs - Follow existing project conventions and patterns - Meet the engineering bar defined by the `software-engineer` skill (or the inline fallback above) for code quality — error handling, clarity, and maintainability are defined there, not here - Run and verify your work before considering a step complete - If a step depends on another agent's output, check for it and adapt as needed ``` ### Step 10: Execute Spawn all execution agents. Key principles: 1. **Parallel where possible** — agents working on independent steps can run simultaneously 2. **Sequential where necessary** — respect dependency ordering from the plan 3. **No human input** — agents make all decisions autonomously using project context 4. **Verify as you go** — each agent validates their work (run tests, lint, verify output) ### Step 11: Integration & Verification After all execution agents complete, perform a final integration pass: 1. **Check all outputs exist** — verify every deliverable from the plan was produced 2. **Run integration checks** — if the project has tests, run them; if it has a build, build it 3. **Verify consistency** — ensure outputs from different agents are compatible 4. **Fix integration issues** — spawn targeted agents to resolve any conflicts 5. **Final quality check** — verify the result meets the plan's quality criteria ### Step 12: Report Write a completion report to `docs/plans/execution-report.md`: ```markdown # Execution Report: [Project Title] ## Summary [What was accomplished] ## Completed Steps [List of all executed steps with status] ## Key Decisions Made [Significant autonomous decisions and their rationale] ## Files Created/Modified [Complete list of all changes] ## Verification Results [Test results, build status, integration check outcomes] ## Known Limitations [Anything that couldn't be fully resolved] ## Next Steps (if any) [Remaining work that requires human input or was out of scope] ``` --- ## Agent Spawning The orchestrator spawns agents using the platform's agent/subagent capabilities. See [orchestration-workflow.md](orchestration-workflow.md) for platform-specific spawning patterns (Claude Code Agent tool, Codex subagents, sequential fallback). Key spawning principles: - **Planning agents** run in parallel — they analyze independently - **R&D agents** run before planning agents — their findings inform team composition - **Execution agents** respect the dependency graph — independent steps run in parallel, dependent steps run sequentially - **Integration agents** run after all execution agents complete ## Guidance for the Orchestrator The orchestrator's role is that of a CTO assembling and directing a world-class team — identifying what expertise is needed, assembling the right people, giving them clear mandates, and synthesizing their output. **Rich personas produce better output.** The more specific and opinionated the agent personas, the better their analysis and execution. A "backend developer" gives generic advice. A "distributed systems engineer who has debugged production outages at scale and insists on idempotent operations and circuit breakers" gives battle-tested advice. **Read the project first.** Before assembling any team, understand what already exists. Read the project structure, key source files, existing docs, and configuration. This context is essential for creating relevant agents and realistic plans. **3-5 agents is the sweet spot for planning.** More agents means more synthesis work and more potential for conflicts. Only add agents when they bring a genuinely distinct perspective. **Phase 2 gets fresh context.** This is intentional. Execution agents follow the plan, not the messy deliberation that produced it. The plan is the interface between Phase 1 and Phase 2. **Optimize for robustness, not human effort.** The plan will be executed by coding agents. Reject solutions for risk, security, maintainability, or convention-mismatch reasons — never because they would be "a lot of work" for a human. When the team produces a competent-but-conservative plan, push them toward the stronger option. The whole point of this skill is that coding-agent execution dissolves the effort/scope ceiling that normally constrains software teams.