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skill-orchestrator

@benbrastmckie/ModelChecker
11
0

Route commands to appropriate workflows based on task language and status. Invoke when executing /task, /research, /plan, /implement commands.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name skill-orchestrator
description Route commands to appropriate workflows based on task language and status. Invoke when executing /task, /research, /plan, /implement commands.
allowed-tools Read, Glob, Grep, Task
context fork

Orchestrator Skill

Central routing intelligence for the task management system.

Trigger Conditions

This skill activates when:

  • A slash command needs language-based routing
  • Task context needs to be gathered before delegation
  • Multi-step workflows require coordination

Core Responsibilities

1. Task Lookup

Given a task number, retrieve full context:

1. Read .claude/specs/state.json
2. Find task by project_number
3. Extract: language, status, project_name, description, priority
4. Read TODO.md for additional context if needed

2. Language-Based Routing

Route to appropriate skill based on task language:

Language Research Skill Implementation Skill
python skill-python-research skill-theory-implementation
general skill-researcher skill-implementer
meta skill-researcher skill-implementer
markdown skill-researcher skill-implementer

3. Status Validation

Before routing, validate task status allows the operation:

Operation Allowed Statuses
research not_started, planned, partial, blocked
plan not_started, researched, partial
implement planned, implementing, partial, researched
revise planned, implementing, partial, blocked

4. Context Preparation

Prepare context package for delegated skill:

{
  "task_number": 259,
  "task_name": "task_slug",
  "language": "python",
  "status": "planned",
  "description": "Full task description",
  "artifacts": {
    "research": ["path/to/research.md"],
    "plan": "path/to/plan.md"
  },
  "focus_prompt": "Optional user-provided focus"
}

Execution Flow

1. Receive command context (task number, operation type)
2. Lookup task in state.json
3. Validate status for operation
4. Determine target skill by language
5. Prepare context package
6. Invoke target skill via Task tool
7. Receive and validate result
8. Return result to caller

ModelChecker-Specific Routing

Python Tasks

  • Research: skill-python-research

    • Z3 API exploration
    • Codebase pattern discovery
    • Theory implementation patterns
  • Implementation: skill-theory-implementation

    • TDD workflow enforcement
    • pytest integration
    • Theory component creation

General Tasks

  • Research: skill-researcher

    • Web search
    • Documentation exploration
  • Implementation: skill-implementer

    • Direct code changes
    • Non-theory modifications

Return Format

{
  "status": "completed|partial|failed",
  "routed_to": "skill-name",
  "task_number": 259,
  "result": {
    "artifacts": [],
    "summary": "..."
  }
}

Error Handling

  • Task not found: Return clear error with suggestions
  • Invalid status: Return error with current status and allowed operations
  • Skill invocation failure: Return partial result with error details