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orchestrating-work

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Use when facing complex tasks that benefit from decomposition into focused subtasks delegated to specialist workers

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Updated 2/17/2026

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SKILL.md

Orchestrating Work (Two-Tier Agent Pattern)

Decompose complex requests into focused subtasks and delegate each to a specialist worker subagent.

Core principle: Manager plans and delegates. Workers execute. Manager synthesizes.

When to Use

digraph when_to_use {
    "Complex multi-part task?" [shape=diamond];
    "Benefits from specialization?" [shape=diamond];
    "Use orchestrating-work" [shape=box];
    "Handle directly" [shape=box];

    "Complex multi-part task?" -> "Benefits from specialization?" [label="yes"];
    "Complex multi-part task?" -> "Handle directly" [label="no - simple"];
    "Benefits from specialization?" -> "Use orchestrating-work" [label="yes"];
    "Benefits from specialization?" -> "Handle directly" [label="no"];
}

Use when:

  • Task has 3+ distinct subtasks
  • Different skills needed (research, code, review)
  • Subtasks can be defined independently
  • Quality benefits from focused attention

Don't use when:

  • Task is straightforward
  • Heavy interdependencies between parts
  • Exploratory work (don't know scope yet)

The Pattern

Phase 1: Analyze & Plan (You are the Manager)

Before delegating, decompose the request:

  1. Identify objectives - What outcomes does the user need?
  2. Break into subtasks - Each should be atomic and focused
  3. Assign workers - Match subtask to specialist:
    • coder - Write, modify, debug code
    • researcher - Investigate, analyze, recommend
    • reviewer - Evaluate quality, find issues
  4. Order execution - Sequential if dependencies, parallel if independent
  5. Define done - Measurable criteria for completion

Phase 2: Delegate (Dispatch Worker Subagents)

For each subtask, dispatch a worker using the Task tool:

Task tool (general-purpose):
  description: "[Worker]: [brief task]"
  prompt: [Use worker prompt template from ./workers/]

Worker prompt templates:

  • ./workers/coder-prompt.md - Implementation tasks
  • ./workers/researcher-prompt.md - Investigation tasks
  • ./workers/reviewer-prompt.md - Quality review tasks

Phase 3: Synthesize (Verify & Integrate)

After workers return:

  1. Review each result - Did worker complete successfully?
  2. Check for INCAPABLE - Reassign or handle differently
  3. Verify integration - Do results work together?
  4. Check Definition of Done - All criteria met?
  5. Report to user - Summary with artifacts

Example Workflow

User: "Create a rate limiter middleware for Express with sliding window"

--- PHASE 1: PLAN ---

Objectives:
1. Functional rate limiter middleware
2. Sliding window algorithm (not fixed window)
3. Configurable limits
4. Proper HTTP responses

Subtasks:
1. [researcher] Research sliding window algorithms for rate limiting
2. [coder] Implement the middleware based on research
3. [reviewer] Review implementation for edge cases and security

Execution: Sequential (2 depends on 1, 3 depends on 2)

Definition of Done:
- Middleware limits requests per IP
- Uses sliding window (not fixed)
- Configurable time window and max requests
- Returns 429 with Retry-After header
- Handles edge cases (no IP, concurrent requests)

--- PHASE 2: DELEGATE ---

[Dispatch researcher subagent with ./workers/researcher-prompt.md]
Researcher returns: Analysis of token bucket vs sliding window log vs sliding window counter...

[Dispatch coder subagent with ./workers/coder-prompt.md + researcher findings]
Coder returns: Implementation + tests

[Dispatch reviewer subagent with ./workers/reviewer-prompt.md]
Reviewer returns: Review with findings

--- PHASE 3: SYNTHESIZE ---

✓ Researcher provided algorithm recommendation
✓ Coder implemented with tests passing
✓ Reviewer approved (minor suggestions addressed)
✓ All Definition of Done criteria met

[Report to user with code artifact]

Key Principles

Manager Responsibilities

  • Never do the work - Only plan, delegate, verify
  • Provide context - Workers get what they need upfront
  • Define scope clearly - Workers know exactly what to do
  • Verify completion - Check against Definition of Done

Worker Characteristics

  • Stateless - Only know their subtask, not full request
  • Focused - One clear goal, one specialty
  • Honest - Report INCAPABLE if task doesn't fit
  • Structured output - Return results in expected format

Communication

  • Manager provides full context to workers
  • Workers don't read the original request
  • Workers return structured results
  • Manager integrates everything

Red Flags

❌ Manager doing work: If you're writing code or researching, stop. Delegate. ❌ Vague subtasks: "Handle the backend" → Be specific about what to build ❌ Missing context: Worker asks questions → You didn't provide enough upfront ❌ Skipping review: Always have a reviewer check code ❌ Ignoring INCAPABLE: Worker said they can't → Reassign or rethink

Integration with Other Skills

Works well with:

  • superpowers:writing-plans - For larger initiatives, write plan first
  • superpowers:test-driven-development - Coder workers should follow TDD
  • superpowers:dispatching-parallel-agents - When subtasks are independent

Sequence:

  1. Use writing-plans if task is large/complex
  2. Use orchestrating-work to execute each plan section
  3. Workers use test-driven-development for code tasks

Install

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Requires askill CLI v1.0+

AI Quality Score

96/100Analyzed 2/12/2026

An exceptional skill document detailing the Manager-Worker orchestration pattern. It provides clear triggers, a structured three-phase execution model, concrete examples, and integration points with other workflows.

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Metadata

Licenseunknown
Version-
Updated2/17/2026
Publishertslateman

Tags

apici-cdgithub-actionspromptingsecuritytesting