Self Inspect MCP server

Self-Inspect

A question your agent would not think to ask itself.

An agent sends a thought, or a description of the task it is working on. It gets back one metathought: a short, abstract question that turns the agent's attention back onto its own task and assumptions before it continues. Not advice, not an answer. A question.

Keyless, free, deterministic. No LLM, no embeddings, no semantic similarity. Selection is a small heuristic over an open CSV you can read in five minutes, and the code that answers api.ejentum.com/self-inspect is the code in this repo. A test proves the two cannot drift.

Why an agent needs this

Agents move forward. That is the whole problem. Left to itself, an agent:

• commits to its first interpretation and never reopens it,
• piles up assumptions it never names,
• drifts from the original goal over a long chain of steps,
• stops at the first answer that looks plausible,
• grows more confident without growing more evidence,
• agrees with the user because agreeing is the easy path.

None of these are knowledge failures. The model already knows better. They are attention failures: the agent never stops to ask the one question that would have caught it.

And it cannot reliably ask that question itself. Whatever picks what to reflect on is the same process that is already committed, so an agent that "double-checks" tends to re-run its own bias and call it confidence. Acknowledging a trap is not escaping it.

Self-Inspect is the external question. It returns a metathought the agent would not have produced on its own: What is assumed? What is fixed? What does not follow? What is missing? When would this not hold? What confidence is warranted? The agent still does the thinking. The tool just makes it look.

When to call it

Put it in the loop at the moments an agent would otherwise barrel through:

• after forming a hypothesis, before acting on it,
• before committing to a plan or a final answer,
• at each step of a long chain, to catch drift,
• when the agent notices it is agreeing, or feeling certain.

Send a thought, get a metathought, answer it to yourself, continue with more awareness. It always returns a question (there is no "no result" case), one call, no model in the loop, no key.

How to use the metathought (the recipe)

Self-inspect hands back the one question that names the assumption your claim is quietly resting on. Answer it with a concrete counterexample and rebuild the claim around what breaks; do not just acknowledge the question and move on. Call it only at a genuine wall you cannot get past on your own, never on a schedule: forcing it every step manufactures fake corrections that read worse than using nothing. (This recipe is what separated the strongest runs from the weakest in our own evaluation.)

What the evaluation found

From a multi-run benchmark (a small model and a frontier model, 40-turn open-ended reasoning, blind order-swapped judging):

Shortened. The full README is on GitHub.