Agent skill

orchestrate

Use when orchestrating a Python development task via specialized agents. Activates on "build a Python CLI", "add a feature", "write tests", "refactor Python code", "debug Python", "code review", or any multi-agent Python workflow. Invoke as /orchestrate with a task description or alone to use conversation context.

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Install this agent skill to your Project

npx add-skill https://github.com/Jamie-BitFlight/claude_skills/tree/main/plugins/python3-development/skills/orchestrate

SKILL.md

Task

orchestrate in plugins/python3-development/skills/orchestrate/

If orchestrate is empty, derive the task from the conversation so far. If no task can be derived, ask the user to describe what they want built or changed before proceeding.

Step 1 — Read the orchestration guide (MANDATORY)

Read ../python3-development/references/python-development-orchestration.md.

Do not proceed to Step 2 until this file has been read. It contains agent selection criteria, workflow patterns, quality gates, and multi-agent chaining patterns you will need to fill in Step 2.

Step 2 — Route to track

mermaid
flowchart TD
    Q{"Does the task meet ANY of:<br>- user said 'add a feature', 'plan', or 'track'<br>- requires ≥ 2 agents in sequence<br>- spans multiple files/modules<br>- needs durable progress tracking across turns"}
    Q -->|"Yes"| SAM["SAM Track → Step 3A"]
    Q -->|"No — single focused task:<br>fix a bug, write tests for one file,<br>review code, one-shot refactor"| Direct["Direct Track → Step 3B"]

Then state aloud before the first Agent tool call:

text
Task: <one sentence>
Track: SAM | Direct
Workflow pattern: <TDD | Feature Addition | Refactoring | Debugging | Code Review>
Agent chain: <AGENT1> → <AGENT2> → ...

If you cannot fill in workflow pattern and agent chain from the guide read in Step 1, go back and read it.

Step 3A — SAM Track

mermaid
flowchart TD
    P1["Phase 1 — Plan<br>Skill: /dh:add-new-feature<br>Args: task description<br>Produces: ~/.dh/projects/{slug}/plan/P{NNN}-{slug}.yaml"]
    P1 --> P1Q{"add-new-feature result?"}
    P1Q -->|"BLOCKED — plan-validator gate failed"| P1Blocked["Surface blocker to user<br>Await clarification<br>STOP"]
    P1Q -->|"PASS — task file produced"| P2
    P2["Phase 2 — Execute<br>Skill: /dh:implement-feature<br>Args: path to task file<br>Loop: sam ready → start-task → SubagentStop hook marks COMPLETE<br>Repeat until no tasks remain"]
    P2 --> P3["Phase 3 — Quality gates<br>Auto-invoked by implement-feature<br>Skill: /dh:complete-implementation<br>Runs: code review → feature verification → integration check<br>→ doc drift → doc update → context refinement → commit"]
    P3 --> Done(["DONE — changes committed"])

Step 3B — Direct Track

Agent routing — delegate rather than implement:

  • Python code → subagent_type="python3-development:python-cli-architect"
  • Tests → subagent_type="python3-development:python-pytest-architect"
  • Code review → subagent_type="python3-development:code-reviewer"
  • Architecture design → subagent_type="python3-development:python-cli-design-spec"
  • Task breakdown → subagent_type="dh:swarm-task-planner"
  • Requirements → subagent_type="spec-analyst"
  • Stdlib-only script → Skill(skill: "python3-development:stdlib-scripting")

Each delegation must include:

  • Outcomes: what must be true when the agent is done
  • Constraints: user requirements, compatibility, scope boundaries
  • Known issues: error messages already in context (pass-through, not pre-gathered)
  • File paths: where to start looking — not what you found there

Do NOT read source files before delegating. Agents search and read files for themselves — pass file paths, not file contents. Pre-gathering wastes orchestrator context and duplicates work the agent will do anyway.

Track is DONE when all agents in the stated chain have returned their outputs.

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