fable-method

Guides AI agents through a structured evidence-based problem-solving loop with verification gates.

Updated Jun 25, 2026
One-click install
npx skills add https://github.com/ismaelsoilet/ismaelsoilet-landing --skill fable-method-ismaelsoilet
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fable-method
Source: https://github.com/ismaelsoilet/ismaelsoilet-landing/tree/main/.agents/skills/fable-method
Command: npx skills add https://github.com/ismaelsoilet/ismaelsoilet-landing --skill fable-method-ismaelsoilet

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? AI agents often fake rigor: they invent APIs from memory, skip verification, take unauthorized actions, or report guesses as facts. This Skill replaces free-styling with a structured loop that forces evidence gathering, observed verification, and honest reporting on every non-trivial task. ## Core Features & Use Cases - Structured problem-solving loop: Classify the ask, define done, gather evidence, decide, act surgically, verify by observation, and report outcome-first. - Safety gates: Authorization gate blocks irreversible actions without explicit user approval; intent and recall gates prevent edits based on memory or misunderstood specs. - Domain adapters: Pre-built adapters for marketing, research, data analysis, business ops, finance, legal, design, and devops define what counts as evidence in each field. - Use Case: Ask the agent to fix a failing test or audit completed work; it will read the actual code and spec, make the smallest correct change, run the full suite, search for twin defects, and report only verified claims. ## Quick Start Ask the agent to use the fable method to diagnose why your dashboard is slow and recommend a fix without changing any files.

Frequently Asked Questions about fable-method

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I make an AI agent verify its work instead of guessing?▼

Use a structured loop that requires observed verification: the agent must run the named check, confirm the surrounding system still works, and search for twin defects before reporting done. Claims that cannot be verified must be labeled as caveats, never passed as facts.

How to prevent AI agents from taking unauthorized actions like deploying or pushing?▼

Apply an authorization gate: before any irreversible or outward-facing action, the agent must quote the user's exact words authorizing it. Documentation or task completion never counts as authorization; without a quote, the action is deferred as a pending step.

What is the difference between fable-method plan, audit, and report modes?▼

Plan mode runs classification through evidence gathering and stops with a recommended plan for approval. Audit grades completed work against each loop step, marking steps followed, skipped, or faked. Report rewrites a pending answer outcome-first with honest caveats.

Does this problem-solving method work for non-coding tasks?▼

Yes, domain adapters adapt the loop for marketing, research, data analysis, business operations, finance, legal compliance, design, and devops. Each adapter defines binding minimum evidence sets, authority orders, and fraud tables specific to that field.

When should the full problem-solving loop be skipped?▼

Skip the loop only for trivial tasks: one file, under ten changed lines, no new behavior, and no searching required. Make the change, run the one obvious check, and report in one or two sentences. Anything uncertain gets the full loop.