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Agent Conductor

Orchestrate coding sub-agents (Claude Code, Codex, Cursor, Gemini Code, or any CLI-based coding agent) for maximum throughput on implementation tasks. Use wh...

v1.0.0
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Description


name: agent-conductor description: "Orchestrate coding sub-agents (Claude Code, Codex, Cursor, Gemini Code, or any CLI-based coding agent) for maximum throughput on implementation tasks. Use when: (1) writing or modifying code files, (2) running scripts or data pipelines, (3) batch processing large datasets, (4) multi-stage workflows requiring parallel execution. Covers agent-agnostic dispatch templates, task decomposition, parallel coordination, and acceptance criteria. NOT for: simple file reads, config-only changes, or sending messages. Core principle — the orchestrator plans; the coding agents execute."

Agent Conductor 🎼

You conduct. Agents perform.

Route all implementation work — file changes, scripts, data processing — to coding sub-agents. The orchestrating session stays lean: it plans, decides, and validates. Agents do the execution.

Supported Agents

Agent-agnostic. Set your invoke command once:

Agent Invoke Command
Claude Code claude '<task>'
OpenAI Codex codex '<task>'
Cursor Agent cursor-agent '<task>'
Gemini Code gemini-code '<task>'
Any other your-agent-cmd '<task>'

Use AGENT_CMD as a placeholder in the examples below.

When to Dispatch

Dispatch when the task involves any of:

  • Writing or modifying files (even one line)
  • Running scripts or processing data
  • Execution time > 10 seconds
  • Batch operations over multiple items

If it produces file changes → dispatch it.

Dispatch Template

## Task: [name]

### Requirement
[One sentence: what to produce and where]

### Context
- Project: [name and purpose]
- Relevant files: [paths]
- Data format: [brief description of inputs/outputs]

### Acceptance Criteria
- [ ] Output file exists at [path]
- [ ] Contains [N] records / passes [specific check]
- [ ] No errors in [error field / log]

### Gotchas
- [Known pitfall 1]
- [Known pitfall 2]

### Environment
- Language/runtime: [python3 / node / go / etc.]
- Working directory: [path]
- Special config: [proxy, auth, env vars if needed]

When done, notify with:
[your completion notification command]

Execution Mechanism

Duration Mechanism
< 5 min Foreground: exec pty:true command:"AGENT_CMD '...'"
5–30 min Background: exec pty:true background:true timeout:1800 command:"AGENT_CMD '...'"
> 30 min Agent writes script → run in screen / tmux

Use pty:true if your platform requires it (needed for Claude Code; check other agents' docs).

Task Decomposition

Split large projects by stage, not by feature. Each stage must be independently verifiable.

Split when any of these apply:

  • Runtime > 30 minutes
  • More than one script needed
  • Batch > 100 items
  • Output of one step feeds the next
Stage 1: Prepare data  →  clean_data.csv        (< 2 min)
Stage 2: Process       →  results.json           (needs Stage 1)
Stage 3: Report        →  report.md              (needs Stage 2)

See references/patterns.md for parallel coordination, checkpoint/resume, and domain examples.

Acceptance Checklist

After any "done" signal, always verify:

  1. File exists — confirm output path
  2. Count correct — expected N vs. actual N records
  3. Non-empty — spot-check 2–3 outputs
  4. No silent errors — check error fields and null rates

A completion signal ≠ acceptance. Run the checklist.

Error Handling

Symptom Action
Timeout, no output Check process log → kill and re-dispatch with more context
File missing after "done" Read execution log → add context → re-dispatch
Partial completion Check progress.json → resume from checkpoint
Fails twice in a row Stop re-dispatching → debug in orchestrator session

What NOT to Dispatch

  • Simple reads → use read tools directly
  • Orchestrator config changes → orchestrator session only
  • Messages/notifications → use messaging tools directly
  • Design decisions → orchestrator decides first, agent implements

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Compatible Platforms

Pricing

Free

Related Configs