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fablize — run Opus like Fable
A Claude Code plugin that makes Opus (or any Claude model) see a task through to the end — with evidence and verification — as procedure, not as luck.
Why
When Fable 5 shipped, I ran a controlled comparison of Fable 5 and Opus 4.8 (an A/B set of 19 runs plus 26 real working sessions, ~1,500 tool calls). The finding:
- On closed, answer-bearing work (code, logic, builds), the two models were effectively tied.
- The gap appeared only on open-ended work, and its nature was "following an implication one step further."
- That depth is model capability — it could not be transferred by instructions or a harness. An injection experiment confirmed it: Opus could not reproduce the defects Fable found on its own.
- But the procedure of good work — actually running what you build, seeing it through, investigating systematically — does transfer.
fablize applies only the procedures whose effect was verified. It does not raise the model's ceiling; it makes the model reach its own ceiling.
What transfers and what doesn't
| Trait | Transferable? | Reason |
|---|---|---|
| Verification grounding (run & observe the artifact) | ✅ shipped | A procedure Opus skipped "not because it can't, but because it didn't." Injecting it raised render-verification behavior measurably. |
| Multi-story completion + evidence gate | ✅ shipped | A procedure — decompose, checkpoint, refuse completion without proof. |
| Systematic investigation (reproduce → hypotheses → causal chain) | ✅ shipped | A procedure — on par with what the strong model already does. |
| Early-stop prevention | ✅ shipped | A deterministic hook — catches "I'll do X" without doing it. |
| Out-of-spec defect discovery | ❌ not possible | Capability. Injection was refuted — the model finds it, or it doesn't. |
| Open-ended creative detail | ❌ not possible | Capability. Shows only where there is no fixed answer. |
| Self-driven propagation depth | ❌ not possible | Capability. Directed propagation transfers; self-started depth does not. |
The non-transferable rows are the model's job (or a human's), not a harness's. When you hit them, fablize tells you to escalate instead of pretending.
What's included (verified only)
- Verification grounding — render/executable artifacts (HTML, SVG, games, charts) are run and observed before completion.
- Multi-story verification gate —
goals.pydecomposes work and refuses a groundless "done." - Investigation protocol — reproduce, compete hypotheses, trace the full causal chain.
- Early-stop hook — blocks promising-without-doing.
- Per-task router — injects only the matching verified discipline.
Negligible or unverified ideas (style mimicry, broad reasoning injection, a silent-recovery guard, a review-recall scan) are not shipped. They stay in personal development until a controlled experiment confirms their effect.
Install
/plugin marketplace add fivetaku/fablize
/plugin install fablize
The per-task router (a UserPromptSubmit hook) registers automatically.
For always-on operation (the rules resident in context), run once:
bash ${CLAUDE_PLUGIN_ROOT}/setup/setup.sh # choose local (recommended) or global
Uninstall: bash ${CLAUDE_PLUGIN_ROOT}/setup/uninstall.sh
If fablize helps, a ⭐ on the repo means a lot — setup asks once (a single opt-in question); it never stars without your explicit "yes".
How it behaves
- Trigger with
/fablizeor phrases like "see it through", or automatically when installed always-on. - 2+ stories → decompose + verification gate. Debugging → investigation protocol. Render artifact → verification grounding. Hard task → adaptive thinking plus an
/effort xhighsuggestion. - At the capability ceiling, escalate to a stronger model or a human.
Honest limits
- It cannot raise model capability. Open-ended creative quality and self-driven discovery are out of reach — that is a model-choice decision, not a harness one.
- The effect numbers come from a small, single-family (Claude) self-measurement (the 19-run A/B set). The direction is solid; the decimals are not asserted.
- The early-stop hook can misfire on a declarative offer ("I'll write the report if you want") — phrasing offers as questions avoids it.
License
MIT — see LICENSE.