Sahir619/fable-method resource

Health v2 · maintenance only

Flags: young

Adoption not part of the score

2253 stars · 322 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A distilled set of agent skills (think/act/prove/grow) capturing the working methodology of Claude Fable 5, packaged as a Claude Code plugin any model can run. It includes an adversarial evaluation harness with fifteen rounds and 260+ agent runs that validates the skills with blind LLM judges.

Use cases

• make a mid-tier LLM coding agent follow a disciplined think/act/prove workflow
• evaluate whether an agent surfaces spec-vs-test conflicts instead of silently fixing code
• verify agent work by diffing and executing rather than trusting reports
• install agent skills as a Claude Code plugin
• generate new domain adapters for agent workflows
• study committed transcripts of adversarial agent eval runs

When to choose

• you want structured, threshold-based agent instructions rather than vague 'be careful' prompts
• you use Claude Code and want a plugin enforcing verification-first agent behavior
• you need an eval harness that judges agents by observation, not self-reported output

When to avoid

• you need a general-purpose agent framework with tool integrations rather than a methodology
• you don't use Claude Code or compatible skill-running models
• you want production agent infrastructure rather than skills and evals

Facets

learning-resource · maturity active

agent-framework prompt-engineering testing llm-inference artificial-intelligence large-language-models developer-tools tutorials python cli cross-platform claude-code agent-skills claude-plugin evaluation coding-agent workflow-methodology llm-judging ai-agents

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markdown · JSON · MCP: product_card(name="Sahir619/fable-method")