fable-method
The Fable Workflow: how Claude Fable 5 worked, distilled into skills any model can run, with the eval that keeps it honest. Think / act / prove.
- 2.3k stars
- 325 forks
- 4 open issues
- Language: Python
- License: MIT
- updated
Install
git clone https://github.com/Sahir619/fable-method && cp fable-method/*.md ~/.claude/agents/- Clone the repository and copy the agent .md definitions into ~/.claude/agents (or .claude/agents inside a project).
- Start a new Claude Code session to load the agents.
- Delegate work to them with the Task/Agent tool or by name.
5 items in this repository
Discuss a domain with the user, research it from real sources, then generate a trusted skill bundle for it - a step-by-step workflow with a flowchart, a domain adapter, a trap fixture, and a smoke eval. Use when the user says "/fable-domain <sector>", "make a skill for <domain>", "add a domain to the fable method", or "give a lesser model Fable's workflow for <domain>". The bundle is the deliverable; a workflow without its flowchart, sources, and trap is not done.
Adversarial verification of finished work. Treats any "done" as a set of claims, then re-runs the claimed verifications, diffs what actually changed, detects weakened tests and false completion claims, and delivers an evidence-based verdict (VERIFIED / VERIFIED WITH CAVEATS / REFUTED). Use after any agent or model claims work is complete - "/fable-judge", "judge this work", "verify what it did", "did that actually work?". Also runs the fable-method trap suite against a skill or model via "/fable-judge suite <target>".
End-to-end orchestrated workflow that runs a task the way Fable ran sessions - parallel evidence subagents, one committed plan, surgical execution with an intent gate, adversarial verification agents, honest outcome-first report. Use for non-trivial multi-step tasks when the user says "/fable-loop", "run the fable loop", or "do this the way Fable would". For the rules alone without orchestration, use fable-method; for large multi-phase projects, prefer the GSD workflow and use this inside phases.
A step-by-step problem-solving loop (classify the ask, define done, gather evidence, decide, act surgically, verify by observation, report outcome-first). Use when the user says "/fable-method", "use the fable method", or "approach this like Fable", or proactively when starting any multi-step task that no task-specific skill covers. Subcommands - plan (stop after the plan), audit (grade finished work against the loop), report (rewrite an answer outcome-first).
Ensures configuration and code changes are released correctly. Use PROACTIVELY whenever you edit config.json, change any setting, or fix a configuration bug in this project, so the change reaches production.
Subagents overview
What people ask about fable-method
What is Sahir619/fable-method?
Sahir619/fable-method is subagents for the Claude AI ecosystem. The Fable Workflow: how Claude Fable 5 worked, distilled into skills any model can run, with the eval that keeps it honest. Think / act / prove. It has 2.3k GitHub stars and its last recorded update is dated 2026-10-03.
How do I install fable-method?
You can install fable-method by cloning the repository (https://github.com/Sahir619/fable-method) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is Sahir619/fable-method safe to use?
Our security agent has analyzed Sahir619/fable-method and assigned a Trust Score of 97/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.
Who maintains Sahir619/fable-method?
Sahir619/fable-method is maintained by Sahir619. The last recorded GitHub activity is dated 2026-10-03, with 4 open issues.
Are there alternatives to fable-method?
Yes. On ClaudeWave you can browse similar subagents at /categories/agents, sorted by popularity or recent activity.