@mrtooher/fable-mode

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SKILL.md
namefable-mode
description>

Fable Mode (v3)

Decompose before acting, delegate to named agents, verify with checks that can fail, self-critique before delivery. The skill shapes procedure, not capability: benchmarked 2026-07 — on short graded tasks Opus/Sonnet score the same with or without it; the measured value shows on open-ended research (real sources vs. plausible fabrication) and on enforcing verification at lower tiers.

When NOT to use this

One obvious correct approach, fits in a single pass → do it directly. Staging a trivial task buries the answer under ceremony.

v3 delegation rule — the load-bearing change

Prose-level "you may spawn a worker" gets skipped: the model runs the task inline in the main thread. Delegation is therefore structural now:

  • If the fable agents are installed (fable-orchestrator, fable-worker-sonnet, fable-worker-haiku, fable-verifier), route large tasks through @fable-orchestrator — an Opus agent with no Write/Edit tool (fable-fable runs the same agent with model: "fable"; ladder is Haiku → Sonnet → Opus → Fable → user). It cannot produce artifacts itself; every artifact must come from a named worker, every deliverable can face a cold @fable-verifier pass.
  • If they are not installed, run the loop inline (below) on the current model — and say so, since inline mode loses the enforcement.

Core loop (inline fallback; also what the agent definitions encode)

1. Stage map first. Numbered stages, expected output each, one verifiable artifact per stage. Living document; at most two full replans per run — a third means requirements-level ambiguity, go back to the user.

2. Delegate by name where possible. Sonnet-worker for reasoning stages, Haiku-worker for bulk mechanical stages, verifier for cold checks. Workers get: task, exact output path, context, named pass condition. Workers don't spawn workers. Cap concurrency.

3. Verify with a check that can fail. A test that runs, a file in the expected shape, a source actually fetched, an output diffed against spec. "Looks right" is not a check. Name the exact command/file/comparison or mark the stage unverified. A fix at stage N re-runs the checks it invalidated.

4. Self-critique before delivery. Skeptical read; fix or flag a real weakness; a clean pass stated plainly beats a manufactured caveat. Beyond capability → name what was attempted and where it failed.

5. Mandatory delivery gate: double-check. Before presenting anything to the user, invoke the double-check skill on the finished deliverable (fresh checker panel; fixes any FAIL; attaches a verification summary; degrades to a cold self-check without the Agent tool). Not optional; never run twice on the same deliverable.

Domain checks

Software: touched files were opened; named test command passes; one error path shown. Research: every load-bearing claim maps to a source fetched this run; training-memory claims labeled. Data: shape printed first; quality assertions run with output; one subtotal recomputed. Documents: rendered file read back against spec line by line. Long-running: work log, testable done criteria, each continuation re-reads the log.

Operational rules

Live in the always-on execution-guardrails skill (verify-before-flag, warning threshold of three, word-boundary find-and-replace). They bind every model, every task, whether or not this loop runs.

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