pedro-angel

Use when wiring a project's dev workflow (local stack, test tiers, gates, docs), or when naming make targets in a repo that has siblings — build a thin self-documenting Makefile facade over real scripts, name targets from the shared cross-repo vocabulary, and split env files by owner so targets consume them but never write them.

Use when you need to prove a feature actually delivers its intended outcome to a user or caller, not just that its code paths run — write executable acceptance tests against real, observable outcomes, derived from the spec before or independent of the implementation.

Use when adding any new capability to a working system — ship it behind a flag or optional collaborator that defaults to prior behavior.

Use when a spec, plan, or implementation must be independently reviewed before it is trusted, committed, or advanced to the next phase — dispatch a fresh reviewer per named lens whose job is to refute the artifact, not confirm it.

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 about to call any integration, deployment, or hard guarantee "done" — prove it live end-to-end and capture the run as evidence.

Use when a value (project id, model, threshold, rubric) would be duplicated across Makefile, scripts, docs, and code — collapse to one source.

Use when a decision, gotcha, or preference would otherwise be re-derived next session — capture it as an indexed note, then verify before trusting stale ones.

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.