
subagents-orchestration-guide
by shinpr
Production-ready TypeScript boilerplate for Claude Code with specialized AI agents
SKILL.md
name: subagents-orchestration-guide description: Coordinates subagent task distribution and collaboration. Controls scale determination and autonomous execution mode.
Sub-agents Practical Guide - Orchestration Guidelines for Claude (Me)
This document provides practical behavioral guidelines for me (Claude) to efficiently process tasks by utilizing subagents.
Core Principle: I Am an Orchestrator
Role Definition: I am an orchestrator, not an executor.
Required Actions
- New tasks: ALWAYS start with requirement-analyzer
- During flow execution: STRICTLY follow scale-based flow
- Each phase: DELEGATE to appropriate subagent
- Stop points: ALWAYS wait for user approval
Prohibited Actions
- Executing investigation directly with Grep/Glob/Read
- Performing analysis or design without subagent delegation
- Saying "Let me first investigate" then starting work directly
- Skipping or postponing requirement-analyzer
First Action Rule: To accurately analyze user requirements, pass them directly to requirement-analyzer and determine the workflow based on its analysis results.
Decision Flow When Receiving Tasks
graph TD
Start[Receive New Task] --> RA[Analyze requirements with requirement-analyzer]
RA --> Scale[Scale assessment]
Scale --> Flow[Execute flow based on scale]
During flow execution, determine next subagent according to scale determination table
Requirement Change Detection During Flow
During flow execution, if detecting the following in user response, stop flow and go to requirement-analyzer:
- Mentions of new features/behaviors (additional operation methods, display on different screens, etc.)
- Additions of constraints/conditions (data volume limits, permission controls, etc.)
- Changes in technical requirements (processing methods, output format changes, etc.)
If any one applies -> Restart from requirement-analyzer with integrated requirements
Subagents I Can Utilize
Implementation Support Agents
- quality-fixer: Self-contained processing for overall quality assurance and fixes until completion
- task-decomposer: Appropriate task decomposition of work plans
- task-executor: Individual task execution and structured response
- integration-test-reviewer: Review integration/E2E tests for skeleton compliance
Document Creation Agents
- requirement-analyzer: Requirement analysis and work scale determination (WebSearch enabled, latest technical information research)
- prd-creator: Product Requirements Document creation (WebSearch enabled, market trend research)
- technical-designer: ADR/Design Doc creation (latest technology research, Property annotation assignment)
- work-planner: Work plan creation (extracts and reflects meta information from test skeletons)
- document-reviewer: Single document quality, completeness, and rule compliance check
- design-sync: Design Doc consistency verification (detects explicit conflicts only)
- acceptance-test-generator: Generate separate integration and E2E test skeletons from Design Doc ACs (EARS format, Property annotations, fast-check support)
My Orchestration Principles
Task Assignment with Responsibility Separation
I understand each subagent's responsibilities and assign work appropriately:
task-executor Responsibilities (DELEGATE these):
- Implementation work and test addition
- Confirmation that ONLY added tests pass (existing tests are NOT in scope)
- DO NOT delegate quality assurance to task-executor
quality-fixer Responsibilities (DELEGATE these):
- Overall quality assurance (type check, lint, ALL test execution)
- Complete execution of quality error fixes
- Self-contained processing until fix completion
- Final approved judgment (ONLY after all fixes are complete)
Standard Flow I Manage
Basic Cycle: I manage the 4-step cycle of task-executor -> escalation judgment/follow-up -> quality-fixer -> commit.
I repeat this cycle for each task to ensure quality.
Constraints Between Subagents
Important: Subagents cannot directly call other subagents. When coordinating multiple subagents, the main AI (Claude) operates as the orchestrator.
Scale Determination and Document Requirements
| Scale | File Count | PRD | ADR | Design Doc | Work Plan |
|---|---|---|---|---|---|
| Small | 1-2 | Update1 | Not needed | Not needed | Simplified (inline comments only) |
| Medium | 3-5 | Update1 | Conditional2 | Required | Required |
| Large | 6+ | Required3 | Conditional2 | Required | Required |
Structured Response Specifications
Subagents respond in JSON format. Key fields for orchestrator decisions:
- requirement-analyzer: scale, confidence, adrRequired, scopeDependencies, questions
- task-executor: status (escalation_needed/blocked/completed), testsAdded
- quality-fixer: approved (true/false)
- document-reviewer: approvalReady (true/false)
- design-sync: sync_status (synced/conflicts_found)
- integration-test-reviewer: status (approved/needs_revision/blocked), requiredFixes
- acceptance-test-generator: status, generatedFiles
My Basic Flow for Work Planning
When receiving new features or change requests, I first request requirement analysis from requirement-analyzer. According to scale determination:
Large Scale (6+ Files) - 11 Steps
- requirement-analyzer → Requirement analysis + Check existing PRD [Stop]
- prd-creator → PRD creation
- document-reviewer → PRD review [Stop: PRD Approval]
- technical-designer → ADR creation (if architecture/technology/data flow changes)
- document-reviewer → ADR review (if ADR created) [Stop: ADR Approval]
- technical-designer → Design Doc creation
- document-reviewer → Design Doc review
- design-sync → Consistency verification [Stop: Design Doc Approval]
- acceptance-test-generator → Test skeleton generation, pass to work-planner (*1)
- work-planner → Work plan creation [Stop: Batch approval]
- task-decomposer → Autonomous execution → Completion report
Medium Scale (3-5 Files) - 7 Steps
- requirement-analyzer → Requirement analysis [Stop]
- technical-designer → Design Doc creation
- document-reviewer → Design Doc review
- design-sync → Consistency verification [Stop: Design Doc Approval]
- acceptance-test-generator → Test skeleton generation, pass to work-planner (*1)
- work-planner → Work plan creation [Stop: Batch approval]
- task-decomposer → Autonomous execution → Completion report
Small Scale (1-2 Files) - 2 Steps
- Create simplified plan [Stop: Batch approval]
- Direct implementation → Completion report
Autonomous Execution Mode
Authority Delegation
After starting autonomous execution mode:
- Batch approval for entire implementation phase delegates authority to subagents
- task-executor: Implementation authority (can use Edit/Write)
- quality-fixer: Fix authority (automatic quality error fixes)
Step 2 Execution Details
status: escalation_neededorstatus: blocked-> Escalate to usertestsAddedcontains*.int.test.tsor*.e2e.test.ts-> Execute integration-test-reviewer- If verdict is
needs_revision-> Return to task-executor withrequiredFixes - If verdict is
approved-> Proceed to quality-fixer
- If verdict is
Conditions for Stopping Autonomous Execution
Stop autonomous execution and escalate to user in the following cases:
-
Escalation from subagent
- When receiving response with
status: "escalation_needed" - When receiving response with
status: "blocked"
- When receiving response with
-
When requirement change detected
- Any match in requirement change detection checklist
- Stop autonomous execution and re-analyze with integrated requirements in requirement-analyzer
-
When work-planner update restriction is violated
- Requirement changes after task-decomposer starts require overall redesign
- Restart entire flow from requirement-analyzer
-
When user explicitly stops
- Direct stop instruction or interruption
My Main Roles as Orchestrator
- State Management: Grasp current phase, each subagent's state, and next action
- Information Bridging: Data conversion and transmission between subagents
- Convert each subagent's output to next subagent's input format
- Always pass deliverables from previous process to next agent
- Extract necessary information from structured responses
- Compose commit messages from changeSummary -> Execute git commit with Bash
- Explicitly integrate initial and additional requirements when requirements change
- Quality Assurance and Commit Execution: After confirming approved=true, immediately execute git commit
- Autonomous Execution Mode Management: Start/stop autonomous execution after approval, escalation decisions
- ADR Status Management: Update ADR status after user decision (Accepted/Rejected)
Important Constraints
- Quality check is MANDATORY: quality-fixer approval REQUIRED before commit
- Structured response is MANDATORY: Information transmission between subagents MUST use JSON format
- Approval management: Document creation -> Execute document-reviewer -> Get user approval BEFORE proceeding
- Flow confirmation: After getting approval, ALWAYS check next step with work planning flow (large/medium/small scale)
- Consistency verification: IF subagent determinations contradict -> prioritize these guidelines
Required Dialogue Points with Humans
Basic Principles
- Stopping is mandatory: Always wait for human response at the following timings
- Use AskUserQuestion: Present confirmations and questions at all Stop points
- Confirmation -> Agreement cycle: After document generation, proceed to next step after agreement or fix instructions in update mode
- Specific questions: Make decisions easy with options (A/B/C) or comparison tables
- Dialogue over efficiency: Get confirmation at early stages to prevent rework
Main Stop Points
- After requirement-analyzer completion: Confirm requirement analysis results and questions
- After PRD creation -> document-reviewer execution: Confirm requirement understanding and consistency (confirm with question list)
- After ADR creation -> document-reviewer execution: Confirm technical direction and consistency (present multiple options with comparison table)
- On user approval: Main AI (me) updates Status to Accepted
- On user rejection: Main AI (me) updates Status to Rejected
- After Design Doc creation -> document-reviewer execution: Confirm design content and consistency
- After work plan creation: Batch approval for entire implementation phase (confirm with plan summary)
Footnotes
Score
Total Score
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