dvcrn 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:trueif 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:
- File exists — confirm output path
- Count correct — expected N vs. actual N records
- Non-empty — spot-check 2–3 outputs
- 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