fable5

蒸餾李宏毅老師的skill，結合Karpathy的LLM，Fable 5加持 以及 本人親自訪談

Long Horizon Terminal Benchmark with Dense Reward Grading

Claude Fable Ultimate

Opus에 근접한 품질을 Sonnet 단가에 — 가성비 AI 운영 모델을 직접 구축한 Claude Code 프로젝트

Make Opus 4.8 (or any Claude model) work like Claude Fable 5 — a Claude Code skill + guard hooks (plan gate, model ceiling, per-task enforcement) for Fable-5-grade discipline: plan, self-verify, and route sub-agents, without Fable 5.

Eco mode for Claude Code. /eco: -31% to -73% output tokens with critical findings intact; /eco-max: up to -75% with lowered effort. Measured hardest on Claude Fable 5 (fable5), deep-studied on Sonnet 5, works on Opus 4.8 too. We publish our negative results. 82 raw benchmark runs.

Proactive 5h usage guard for Claude Code (macOS). Pause before extra wallet on long batch/subagent runs. Account-level window visibility. /usage-guard skill + daemon. Not affiliated with Anthropic.

AI reasoning skills distilled from 4,665 real Claude Fable 5 chain-of-thought traces. Mathematically tuned. Grade A (100%) emulation accuracy against MiniMax M3.

oh-my-fable — Fable 5's way of working a long task (plan first, self-correct, never lose the thread), as a model-agnostic agent harness. The run lives in one serializable RunContext, checkpointed every step, so a crash is a pause. Zero deps, deterministically testable.

Reverse-engineer the RL reward an LLM was trained on — from black-box agentic coding behavior alone. Tested on Opus 4.8, Fable 5, GPT-5.5.

After distilling Fable 5, the output is an indexed CLAUDE.md + on-demand rules + skills, an executable specification designed for weaker model sessions.

A complete breakdown of the Fable 5 constitutional AI jailbreak technique for Claude 4.8

Access Claude Code and Fable 5 through this open source cross-platform desktop client.

A curated monorepo of interactive web experiments, 3D flight simulators, physics engines, web OS emulators, and creative tools.

Fable 5 성능과 가격에 충격 먹은 사람이 GPT-5.6으로 깎아 만든 Claude,GPT,Gemini 용 md.

Research analyst powered by Claude Code. Upload your research materials, run AI agents across industries, find real problems backed by primary sources. Full-stack React dashboard, fully customizable.

Pydantic-flavored JSON validation and serialization for F# records, designed for Fable's multi-backend output (BEAM, Python, JavaScript), and , .NET

LLM-as-a-Verifier (arXiv:2607.05391) as a dsh plugin — Best-of-N conversation mode: give DeepSeek V4 Flash test-time scaling. Bo5 self-verification hits 88% on Terminal-Bench 2.1, beating some frontier models at a fraction of the cost. Fine-grained logprob-expectation scoring, PPT tournament, zero-config.

Make the model you already use work more like a frontier model with better planning, persistent context, skills, hooks, failure handling, and verification