Grounding an agent's answers about its own environment: a small but useful pattern

Sharing a small firmware change that I think is a genuinely useful pattern for anyone building agents that need to answer questions about their own setup or environment.

The problem: an agent asked "what do you own," "where does this route," or "how does recovery work" can produce an answer that sounds confident but isn't actually grounded in anything verifiable. Without a real reference to check against, a plausible guess and a correct answer look identical from the outside.

The fix (PR #624): a bundled, project-specific self-knowledge reference covering hardware ownership, runtime routing, device-bridge behavior, board configuration, setup, observation, verification, and recovery boundaries. Routing, device settings, and recovery paths are related but not interchangeable, so the reference is scoped per-area rather than one generic description.

The part I think generalizes beyond this specific firmware: the Skill enforces that an acknowledgement is not proof of completion. Receiving or accepting a request is a real, loggable event, but it's not evidence that anything downstream actually finished. Verified completion needs its own evidence from whatever observation/verification path applies. A specific example of the same discipline: during frame-service recovery, stale images can't be used as evidence for what happened or whether recovery succeeded, a rule scoped precisely to that recovery path rather than generalized into a blanket image-workflow rule.

Validation was structural rather than behavioral: lint (zero issues), YAML frontmatter validation, focused skill-loader tests, git diff checks. That confirms the content is formatted and loadable, not that every future answer will be correct.

Full writeup: https://aidenai.io/blog/aiden-adds-a-self-knowledge-skill-for-clearer-agent-boundaries/

PR: https://github.com/AidenAI-IO/aiden-firmware/pull/624

Curious whether others here have run into the same "confident but ungrounded self-description" problem in agent systems, and if so, whether you went with a similar bundled-reference approach or something else entirely.