agent-methodology

Use when shipping or handing off code — treat docs as a first-class deliverable — present-tense, diagrammed-as-code, verified against reality, reader-tested.

Use when making a load-bearing or security-relevant claim, or reusing inherited or unfamiliar code — treat recalled facts and unread code as unverified until re-grounded against the live source, and disposition every dangerous surface rather than eyeballing it.

Use when containing untrusted or agent-generated execution, sandboxing a worker with write/exec tools, or judging whether a guard is actually a security boundary.

Use when building automation that edits, tests, or deploys itself — an agent that regenerates its own code, a self-updating pipeline, any loop that modifies the thing running it.

Use when an LLM or agent emits decisions or claims and you need to turn fuzzy output into a verifiable, regression-protected signal.

Use when the human's request rests on a premise you can check, contradicts evidence or a recorded principle, or proposes a direction you have not independently weighed — weigh the strongest alternative before taking a stance, challenge once with evidence before complying; their decision still wins.

Use when a live result contradicts the hoped-for story or a metric could be gamed — state what really works and never fake a green.