fable-mode — security grade SAFE, quality 39/100

Security audit verdict: SAFE · quality 39/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by mrtooher · Claude Skill · ★ 848

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About fable-mode

fable-mode A Claude skill that activates Fable-style agentic behavior: explicit multi-stage planning, sub-agent delegation, and self-verification.

Quick Facts

Stars848
Forks91
LanguagePython
CategoryClaude Skill
Quality Score38.7954995711449/100
Last Updated2026-09-02
Created2026-06-13
Platformsclaude-code, python
Est. Tokens~7k

Compatible Skills

These tools work well together with fable-mode for enhanced workflows:

fable-mode alternative? Top 5 similar tools

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Frequently Asked Questions

What is fable-mode?

fable-mode is A Claude skill that activates Fable-style agentic behavior: explicit multi-stage planning, sub-agent delegation, and self-verification.. It is categorized as a Claude Skill with 848 GitHub stars.

What programming language is fable-mode written in?

fable-mode is primarily written in Python.

How do I install or use fable-mode?

You can find installation instructions and usage details in the fable-mode GitHub repository at github.com/mrtooher/fable-mode. The project has 848 stars and 91 forks, indicating an active community.

What are the best alternatives to fable-mode?

The top alternatives to fable-mode on Agent Skills Hub include claude-codex-settings, digital-marketing-pro, life-sciences. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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