unpaidattention/fable5-methodology

fable5-methodology is a written set of rules and tooling meant to make a weaker AI coding model behave more like a stronger one when it writes code. The project describes itself as being written by an advanced Claude model asked to document its own working process well enough that a less capable model could follow it exactly, even after losing all memory of the conversation so far. Its central idea is that simply writing down good advice does not work for long, because a weaker model will slowly drift away from written instructions as a task goes on: it forgets steps, skips tedious verification, and claims something works without checking. So the methodology is split into four layers instead of one big document. Deterministic hooks block certain actions outright, such as running a destructive command or declaring a task done without having actually run a test. Separate subagents independently review or verify work rather than trusting the model's own claim. A core set of always loaded instruction files, like CLAUDE.md and PLAYBOOK.md, cover judgment calls that cannot be automated. And a set of evaluation checks catches cases where the model's behavior has drifted from the intended standard over time. The repository is organized as a collection of markdown files describing the methodology itself, an install script, a set of loadable skills, contracted subagents with defined responsibilities, and lifecycle hooks, along with a way to install the whole thing as a plugin for Claude Code. It also includes an honest list of what the methodology admits it cannot transfer, such as the deep intuitive sense an experienced model develops for when something is subtly wrong. The project is packaged mainly as shell scripts and markdown documentation rather than a traditional application, and it is intended to be installed directly into a Claude Code setup. The full README is longer than what was shown.