| 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