What problem does it solve? Code samples in developer documentation silently rot: they stop compiling after API changes, leak credentials, break copy-paste, and drift out of sync across SDK languages, with nobody owning the fixes. This Skill defines the policy every published sample must meet and audits an existing corpus against it, returning a ranked fix queue. ## Core Features & Use Cases - Sample policy authoring: Produces a complete policy document covering the six decisions - coverage, anatomy, copy-paste and security safety, language parity, verification tiers, and ownership with freshness windows. - Corpus audit with ranked fix queue: Runs a mechanical census over every fenced code block (via scripts/sample-audit.py), applies ROT triage and rubric scoring on a stratified sample, then ranks findings by harm and a readers-times-severity-over-effort ratio. - Execution tiering and CI design: Classifies each sample as Run, Compile-only, or Illustrative, and designs the verification pipeline including single-sourcing from tested code, fixture teardown, and blocking gates. - Use Case: A docs team with 400 samples across five SDK languages runs the audit script, discovers leaked keys and untested quickstart samples, and receives a P0-first fix queue plus a parity matrix showing 71% cross-language coverage. ## Quick Start Ask the assistant to audit the code samples in your docs directory and produce a ranked fix queue with severity ratings.