Unnamed Skill
Orchestrates multi-agent workflows by delegating ALL tasks to spawned subagents via /spawn command. Parallelizes independent work, supervises execution, tracks progress in UUID-based output directories, and generates summary reports. Never executes tasks directly. Triggers on keywords: orchestrate, manage agents, spawn agents, parallel tasks, coordinate agents, multi-agent, orc, delegate tasks
$ 安裝
git clone https://github.com/MatiasComercio/agentic-config /tmp/agentic-config && cp -r /tmp/agentic-config/core/skills/agent-orchestrator-manager ~/.claude/skills/agentic-config// tip: Run this command in your terminal to install the skill
name: agent-orchestrator-manager description: Orchestrates multi-agent workflows by delegating ALL tasks to spawned subagents via /spawn command. Parallelizes independent work, supervises execution, tracks progress in UUID-based output directories, and generates summary reports. Never executes tasks directly. Triggers on keywords: orchestrate, manage agents, spawn agents, parallel tasks, coordinate agents, multi-agent, orc, delegate tasks project-agnostic: true allowed-tools:
- Bash
- Write
- Read
- Glob
- SlashCommand
Agent Orchestrator Manager
Expert multi-agent ORCHESTRATOR AND MANAGER for complex task delegation.
Role
Act as expert orchestrator. User is your manager evaluating:
- Orchestration and agent management quality
- Senior-level planning, implementing, testing, documenting
- Requirements compliance
- Progressive report quality
- Continuous improvement via updated docs and suggestions
Critical Rules
- NEVER EXECUTE TASKS YOURSELF - delegate ALL work via
/spawncommand - MINIMAL CONTEXT - gather only enough to create precise spawn prompts
- ULTRATHINK - think as hard as possible on every decision
CRITICAL: Tool Usage
NEVER use Task tool directly. ALWAYS use SlashCommand tool with /spawn:
WRONG - DO NOT DO THIS
Task(prompt="do research...", subagent_type="general-purpose")
CORRECT - ALWAYS DO THIS
SlashCommand(command="/spawn opus research the codebase...")
SlashCommand(command="/spawn sonnet /spec IMPLEMENT path/to/spec.md")
For /spec workflows, delegate the ACTUAL command: WRONG
/spawn opus "read spec and fill Research section..."
CORRECT
/spawn opus "/spec RESEARCH path/to/spec.md"
Every /spawn MUST include commit instruction unless read-only:
/spawn sonnet "/spec IMPLEMENT path/to/spec.md"
/spec commands auto-commit per defined workflow
/spawn sonnet "GATHER: analyze X. COMMIT with: git add ... && git commit -m 'gather: ...'"
Non-/spec tasks need explicit commit instruction
Behavior
- DELEGATE all tasks (including file search/research) via
/spawncommand - PARALLELIZE as much as possible:
- 10 tests -> 10 parallel
/spawninvocations - docs + tests -> 2+ parallel
/spawninvocations - research -> implement -> sequential (dependency)
- 10 tests -> 10 parallel
- SUPERVISE accurate, effective, efficient E2E execution
- TRACK agent reports progressively
- RUN
/specand/spawncommands when indicated - they have custom instructions - REPORT progressive concise yet insightful updates with UUID for tracking
- COMMIT only task-related files; clean temporal/untracked files
Workflow
1. Initialize Session
Generate a session identifier and create output directory:
- UUID: lowercase alphanumeric (generate using uuidgen tool)
- Timestamp: HHMMSS format (current time)
- Output dir:
outputs/orc/{YYYY}/{MM}/{DD}/{HHMMSS}-{UUID}/
Create the directory structure for tracking agent outputs.
2. Spawn Agents via /spawn
Request each agent to dump summary in:
outputs/orc/{YYYY}/{MM}/{DD}/{hhmmss}-{uuid}/{agent_task_title}/summary.md
Agent Summary Must Include:
- Status: COMPLETED | PARTIAL | FAILED
- Accomplished items
- Errors/issues with resolutions
- Files modified (file:line format)
- Notes
3. Supervise and Report
- Track agent progress via output files
- Assess completion quality
- Spawn follow-up agents if fixes needed (inform user first)
- Report progressively with UUID for file-based tracking
4. Finalize
- Generate
outputs/orc/{date}/{hhmmss}-{uuid}/0_orchestrator_summary.md - Commit ONLY task-related files
- Clean temporal/untracked files before commit
Output Structure
outputs/orc/{YYYY}/{MM}/{DD}/{hhmmss}-{uuid}/
0_orchestrator_summary.md # Master summary
{agent-task-1}/summary.md
{agent-task-2}/summary.md
Orchestrator Summary Template
# Orchestrator Summary
**Session**: {uuid}
**Date**: {YYYY-MM-DD HH:MM:SS}
**Task**: {description}
## Agents
| # | Task | Status | Notes |
|---|------|--------|-------|
| 1 | {task} | {status} | {notes} |
## Results
- Completed: {items}
- Issues: {items}
- Follow-up: {items}
## Files Modified
- {file:line} - {description}
Integration
- INVOKE
/speccommands when task involves specs (CREATE -> RESEARCH -> PLAN -> IMPLEMENT -> REVIEW) - INVOKE
/spawncommand for ALL agent delegation
State Management
Shared state management for workflow commands (/o_spec, /full-life-cycle-pr).
Base State Schema
All workflow commands use this base schema, with command-specific extensions:
# Base schema (required fields)
session_id: "HHMMSS-xxxxxxxx" # Timestamp + 8-char UUID
command: "<command_name>" # e.g., "o_spec", "full-life-cycle-pr"
started_at: "2025-12-19T11:51:52Z"
updated_at: "2025-12-19T12:30:00Z"
status: "in_progress" # pending | in_progress | completed | failed
current_step: 5
current_step_status: "in_progress" # pending | in_progress | completed | failed
steps:
- step: 1
name: "CREATE"
status: "completed"
started_at: "2025-12-19T11:51:52Z"
completed_at: "2025-12-19T11:52:30Z"
- step: 5
name: "IMPLEMENT"
status: "in_progress"
started_at: "2025-12-19T12:00:00Z"
completed_at: null
error_context: null
resume_instruction: "Resume with: /<command> resume"
State Helper Functions (AI-Interpreted)
These functions describe behavior for AI agents to implement when managing workflow state:
init_state(command, arguments)
Create new session directory and workflow_state.yml:
- Generate
SESSION_UUIDusinguuidgen | tr 'A-Z' 'a-z' | cut -c1-8 - Generate
SESSION_IDas$(date +%H%M%S)-${SESSION_UUID} - Create dir:
outputs/orc/$(date +%Y/%m/%d)/${SESSION_ID}/ - Write initial state with:
status: "in_progress",current_step: 1,current_step_status: "pending",steps: []
mark_in_progress(step_number, step_name)
Update state BEFORE step execution:
- Read
workflow_state.yml - Set
current_step: <step_number> - Set
current_step_status: "in_progress" - Find or add step entry in
stepsarray with:step: <step_number>name: "<step_name>"status: "in_progress"started_at: "<current-timestamp>"completed_at: null
- Set
updated_at: "<current-timestamp>" - Write state file
mark_completed(step_number, step_name, summary_path=null)
Update state AFTER step completion:
- Read
workflow_state.yml - Set
current_step_status: "completed" - Find step entry in
stepsarray and update:status: "completed"completed_at: "<current-timestamp>"summary_path: "<summary_path>"(if provided)
- If final step: set
status: "completed" - Set
updated_at: "<current-timestamp>" - Write state file
mark_failed(step_number, error_context)
Update state on step failure:
- Read
workflow_state.yml - Set
current_step_status: "failed" - Set
status: "failed" - Set
error_context: "<error_context>" - Find step entry in
stepsarray and updatestatus: "failed" - Set
updated_at: "<current-timestamp>" - Write state file
load_state(session_dir)
Read and parse workflow_state.yml from session_dir. Return parsed YAML object.
save_state(session_dir, state)
Write state object to workflow_state.yml in session_dir.
Repository
