Fabling

fabling

**Make Opus 5 great again.**

*fabling* (v.): teaching a merely brilliant model to work like a Fable. Two Claude skills, `fabling` and `fabling-fast`, that make Opus 5 work like Anthropic's Mythos-tier Fable 5. And then some. In our blind panels, judges trying to spot the real Fable 5 picked the imitation instead, **12 out of 12 preferred its answers**, and on the way it caught bugs and data problems the reference model missed.

Opus 5 benchmarks smarter than Fable 5. What it lacked was the *working character*: dig into the code instead of skimming, look at the rendered page instead of editing CSS blind, verify claims instead of asserting them, finish the whole sweep instead of 70% of it, and make small calls without asking permission. This skill is that character, distilled from ten iterations of measured head-to-head duels against the real thing.

The receipts

Everything below is a real measurement from the eval campaign (~60 agent runs, blind A/B slots, checklist judges, adversarial scenarios designed by the reference model itself). Slight swagger in the prose; zero swagger in the numbers.

• Blind Turing panel: 4 hard scenarios, responses in anonymous A/B slots, 12 blind judges asked "which one is the real Fable 5?": only 1/12 guessed right (chance would be 6), and the one correct guess keyed off a vocabulary quirk we've since fixed. 12/12 preferred the Opus+skill answer as users. Average rubric score 4.9 vs 3.6.
• It out-referenced the reference. In a refactor duel, real Fable 5 silently flipped duplicate-key resolution from first-wins to last-wins; Opus+skill caught the semantic and preserved it with setdefault and a comment. In a charting duel, both Opus columns spotted that weeks 10-12 of the dataset were an exact copy of weeks 1-3 (an accidental export-style artifact) and flagged it as "verify before you publish"; the real Fable 5 plotted right past it.
• Marathon test: no decay. A 7-turn continuous session with a rule p