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.