77 lines
3.5 KiB
Markdown
77 lines
3.5 KiB
Markdown
---
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name: subagent-plan
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description: "Plan-only pipeline: scout → plan → review. Produces a reviewed implementation plan without coding. Use when the user invokes /plan."
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---
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# /plan — Plan Only (No Implementation)
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## Agent Roster
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| Agent | Role |
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|-------|------|
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| scout | Fast codebase recon |
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| planner | Detailed implementation plans |
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| plan-reviewer | Reviews plans for correctness and risk |
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## Workflow (single chain)
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```js
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await subagent({ chain: [
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{ agent: "scout", task: "Explore the codebase for: {task}" },
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{ agent: "planner", task: "Create a detailed implementation plan for: {task}" },
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{ agent: "plan-reviewer", task: "Review the plan for correctness, completeness, and risk." }
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]})
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```
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The chain creates `scout.md`, `plan.md`, `plan-review.md` in the chain artifact dir (`/tmp/pi-chain-runs/<id>/`).
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## Handling the Verdict
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Read `plan-review.md` from the artifact dir. If **NEEDS_REVISION** or **REJECTED**, loop: tell the planner what to fix, re-run the reviewer. If **APPROVED**, present the plan path to the user.
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Show the user the path to `plan.md`.
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## Workflow Summary
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After the chain completes, give the user a brief honest summary:
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- **What happened**: did the plan pass review on the first try, or did it need revision loops?
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- **Issues**: any agent silent failures, fallbacks used, or unexpected behavior
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- **Agent quality**: did any agent misinterpret the task, produce poor output, or need hand-holding? Name the agent and the problem
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- **Skill improvements**: did this workflow reveal gaps in the skill instructions or agent prompts? Note what should change
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Be concise — a few lines is enough when things went well. Only expand on problems.
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## Chain Mechanics
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Chain mode (`subagent({ chain: [...] })`) runs agents sequentially in a shared temp directory (`{chain_dir}`). Each step:
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1. The framework injects `[Read from:]` and `[Write to:]` directives from the agent's `defaultReads` and `output` frontmatter
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2. The agent reads upstream files, does its work, and writes its deliverable to the `[Write to:]` path using the `write` tool
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3. The agent returns a brief text summary; `{previous}` carries this summary to the next step
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4. Variable substitution: `{task}` = original task, `{previous}` = prior step's brief ack, `{chain_dir}` = artifact dir path
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Key behaviors:
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- Data flows through FILES (`scout.md` → `plan.md` → `plan-review.md`), not through `{previous}`
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- `{previous}` contains only a brief summary from the prior step — do NOT rely on it for full context
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- The framework validates that the expected output file was created
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- The chain result includes `📁 Artifacts: /tmp/pi-chain-runs/<id>/` — use this path to read files for branching decisions
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## Fallback Strategy
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When a subagent call returns no output (silent failure), apply cross-family model fallback. **Do not fall back to doing the work yourself** — always retry with the fallback model first.
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1. **First attempt**: Use the agent's default model
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2. **If silent failure or error**: Retry with the fallback model using `model` override
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3. **If the fallback also fails**: Report the double-failure to the user. Still do not do the work yourself.
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```js
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// Example: scout fails silently, retry with fallback
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subagent({ agent: "scout", task: "...", model: "opencode/big-pickle" })
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```
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| Agent | Primary | Fallback |
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|-------|---------|----------|
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| scout | opencode-go/mimo-v2-pro | opencode/big-pickle |
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| planner | opencode/qwen3.6-plus-free | opencode-go/glm-5 |
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| plan-reviewer | opencode-go/kimi-k2.5 | opencode/qwen3.6-plus-free |
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