Post by dong evan on Peerlist

dong evan

Shipped an open awesome-list: 60 curated, real-world Claude Fable 5 cases — each logged with input, process, output (time/tokens/cost), and an evidence tag (Demo / Tutorial / Evaluation / Integration). Principle: concrete evidence over hype.

What's in it:

→ Coding: screenshot → working GitHub clone (~10 min, ~$4.07) → Agents: infra outage diagnosed from pod logs + Cloud SQL → fix PR in minutes → The "Relay" pattern: plan/review with the expensive model, build with cheaper ones → Honest limits: same sim cost $6 on GPT-5.5/Codex vs $360.55 on Fable 5/Cursor — a 60x gap → Copy-paste prompts (DEVICE HARDENING, /goal design audit, Repo Audit) + a curl quickstart

Built it because model evaluation is drowning in demos and starving for reproducible evidence. Multilingual READMEs (Korean included).

Repo: https://github.com/EvoLinkAI/awesome-claude-fable-5

To reproduce a case and test the model directly: https://evolink.ai/claude-fable-5?utm_source=community&utm_medium=peerlist&utm_campaign=awesome_claude_fable_5

(All case figures are creator-reported and curated with sources, not independently re-verified.)

GitHub - EvoLinkAI/awesome-claude-fable-5: Curated Claude Fable 5 use cases, tutorials, integrations, demos, and benchmark evidence with source links and multilingual README files.

github.com

GitHub - EvoLinkAI/awesome-claude-fable-5: Curated Claude Fable 5 use cases, tutorials, integrations, demos, and benchmark evidence with source links and multilingual README files.

TL;DR by

This repository showcases real-world Claude Fable 5 use cases, tutorials, integrations, and benchmark evidence. It features concrete workflows, prompts, and demos from public sources, highlighting coding, automation, creative tasks, and practical limitations. API access via Evolink is also provided.