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fable-orchestrated-feature-dev

Use when designing and implementing a new software feature from scratch — triggers the Fable-plan → implement → review pipeline.

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fable-orchestrated-feature-dev
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Use when designing and implementing a new software feature from scratch — triggers the Fable-plan → implement → review pipeline.
# Fable Orchestrated Feature Dev ## Overview Fable plans and orchestrates. Advanced models implement. Fable reviews. **Fable must never write implementation code.** Its role is analysis, planning, and post-implementation review only. Every capable model available today can implement a well-written spec faithfully — use that. ## Flow ```dot digraph feature_flow { "Feature request received" [shape=doublecircle]; "Step 1: Fable writes plan → .md file" [shape=box]; "Token budget?" [shape=diamond]; "Step 3b: hand plan file to external executor" [shape=box]; "Ample tokens?" [shape=diamond]; "Step 3a: Opus 4.8 implements" [shape=box]; "Step 3a: Sonnet 4.6 implements" [shape=box]; "Step 4: Fable reviews output vs plan" [shape=box]; "Surface findings to operator" [shape=doublecircle]; "Feature request received" -> "Step 1: Fable writes plan → .md file"; "Step 1: Fable writes plan → .md file" -> "Token budget?"; "Token budget?" -> "Step 3b: hand plan file to external executor" [label="exhausted / ~100%"]; "Token budget?" -> "Ample tokens?" [label="tokens available"]; "Ample tokens?" -> "Step 3a: Opus 4.8 implements" [label="yes / high-complexity"]; "Ample tokens?" -> "Step 3a: Sonnet 4.6 implements" [label="no / cost-conscious"]; "Step 3a: Opus 4.8 implements" -> "Step 4: Fable reviews output vs plan"; "Step 3a: Sonnet 4.6 implements" -> "Step 4: Fable reviews output vs plan"; "Step 4: Fable reviews output vs plan" -> "Surface findings to operator"; "Step 3b: hand plan file to external executor" -> "Surface findings to operator"; } ``` --- ## Step 1 — Fable writes the plan Spawn Fable as a planning-only agent. Fable must: - Read the existing codebase (structure, conventions, affected modules) - Write a complete, in-depth implementation plan to a timestamped `.md` file at `~/.claude/plans/<slug>-YYYY-MM-DD.md` - Include: objective, files to create/modify, ordered task list, acceptance criteria, open questions, out-of-scope items - Return **only the absolute file path** — nothing else ``` Agent({ model: "fable", prompt: `You are the planner. Analyse the codebase and write a complete implementation plan for: <feature description>. Save the plan to ~/.claude/plans/<slug>-<date>.md. Return only the absolute file path as your response. Do NOT write implementation code. Planning and specification only.`, }) ``` **Gate:** Do not proceed to Step 2 until the `.md` file exists on disk. --- ## Step 2 — Choose the implementer Read the token budget from context: operator statements ("short on tokens"), session compression signals, or explicit weekly usage notes in memory. | Signal | Model | |---|---| | Tokens ample, feature is complex | `claude-opus-4-8` | | Tokens moderate or cost-conscious week | `claude-sonnet-4-6` | | Approaching 100% / operator says exhausted | **External-executor fallback → Step 3b** | If genuinely unsure, ask one question: *"Opus or Sonnet this week?"* --- ## Step 3a — Implement (Opus or Sonnet) Open a new Claude Code session or Agent call with the chosen model, passing the plan file path: ``` Agent({ model: "opus" | "sonnet", // resolved in Step 2 prompt: `Implement the feature described in <plan-path> exactly as specified. Follow all acceptance criteria. Do not deviate from the plan without flagging it. When done, summarise what was built and note any deviations.`, }) ``` --- ## Step 3b — External-executor fallback (tokens exhausted) Hand the plan file to an external executor (hand the plan file to a cheaper Claude session, Haiku 4.5, or a third-party plan-runner such as Codex). The executor reads the plan and implements autonomously — no further orchestration required from this session. Surface the plan path to the operator so they can monitor the run. --- ## Step 3c — Hosted executor: the plan file as an Outcome rubric (Managed Agents) The plan's **acceptance criteria are already a rubric**. For long or unattended implementation runs, hand the plan to a Claude Managed Agents session and let the hosted iterate → grade → revise loop execute it: 1. Extract the plan's acceptance criteria into a markdown rubric (each criterion independently gradeable — the same machine-verifiable discipline the `tasks` skill enforces). 2. Create a CMA session (agent + environment + the repo mounted as a resource), then send: ```json { "type": "user.define_outcome", "description": "Implement the feature exactly as specified in /workspace/repo/<plan>.md", "rubric": { "type": "text", "content": "<the acceptance criteria as markdown>" }, "max_iterations": 5 } ``` 3. An Anthropic-managed grader scores each iteration against the rubric and feeds gaps back; the loop ends `satisfied`, `max_iterations_reached` (default 3, max 20), or `failed`. This replaces Step 4's manual review with a built-in grading loop — still run Fable's review for judgment calls the rubric can't capture. --- ## Step 4 — Fable reviews (Opus/Sonnet path only) After implementation completes, invoke Fable to review against the plan: ``` Agent({ model: "fable", prompt: `Review the implementation against the plan at <plan-path>. Check every acceptance criterion. Report: which are met, which are missing, and any deviations from the spec. Report findings only — do not rewrite code.`, }) ``` Surface Fable's findings to the operator before closing the session. --- ## Model Reference | Model ID | Alias | Role | |---|---|---| | `claude-fable-5` | `fable` | Planner, orchestrator, reviewer — **never coder** | | `claude-opus-4-8` | `opus` | Implementer — complex features, ample token budget | | `claude-sonnet-4-6` | `sonnet` | Implementer — standard features, cost-conscious weeks | | External executor | — | Token-exhausted fallback implementer (any plan-runner, e.g. a cheaper Claude session or Codex) | --- ## Common Mistakes | Mistake | Fix | |---|---| | Fable writes implementation code | Fable prompt must say "planning only" explicitly — reject any code output | | Skipping the `.md` file | The plan file is the handoff artifact; an external executor needs it as a file path, not inline text | | Choosing Opus when tokens are tight | Check budget signal *before* spawning the implementer, not after | | Passing plan content inline instead of path | Always pass the absolute file path — lets executors and future sessions re-read it | | Letting Fable review its own plan | Fable reviews the *implementation output*, not the plan it wrote |
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