Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral detail beyond the schema by specifying the exact return payload for a direct match: verdict, positive control, honest bound, and anchor. It does not cover the no-match case, but that is a minor gap given the strong annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no filler, front-loads the core question, and packs the return contract into a readable list. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a three-parameter read-only tool, the description covers the key semantics: what is queried, what a direct match returns, and why an agent should call it. The lack of an output schema is partially compensated by listing the return components, though no-match behavior and the optional limit parameter are not explained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 67%, with claim and domain already described in the schema. The description reinforces that the claim is a plain-language hypothesis but does not add meaningful meaning beyond the schema, and the limit parameter remains undocumented by both.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific question and immediately names the resources being queried: the Null Museum and the Bitcoin-anchored hypothesis registry. It clearly distinguishes itself from siblings like run_controlled_test by framing this as a lookup that tells an agent whether a hypothesis has already been tested, not a tool that runs tests.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description conveys when to use the tool: before testing an Earth-science hypothesis, to avoid re-running a dead idea. It does not explicitly name alternative tools or state when not to use it, but the 'never re-runs a dead idea' phrasing provides practical usage context that is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.