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

With no annotations provided, the description fully discloses the tool's behavior: it returns per-fact statuses (valid, changed, unknown), and meaningfully clarifies the critical caveat that 'unknown' is not confirmation of unchanged. This is a behavioral trait that an agent must know to interpret results correctly, and the description delivers it clearly.

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?

Well-structured: the critical call-to-action is front-loaded in caps, followed by a concise definition of the return statuses, a crucial caveat about 'unknown', and an efficiency tip. Every sentence carries operational value; no filler.

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?

Given the tool's simplicity (single parameter, but with complex semantics around the 'unknown' status), the description is complete. It explains the return values (valid/changed/unknown), the interpretation pitfall, the batching limit, and points to how to obtain valid subject keys. The absence of an output schema is adequately compensated by the description's explanation of return value meanings.

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?

With 0% schema description coverage, the description partially compensates by explaining the 'facts' parameter's purpose (batch of assertions) and the expected outcome semantics. It does not detail individual fields like subjectKey or aspect, but the 'subjectKey' reference to check_coverage provides useful cross-tool guidance, and the overall parameter meaning is clear enough for the agent to construct a valid call.

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 clearly states the tool's purpose: batch-checking cached assertions against current observed state, with a specific verb ('verify') and resource (cached facts). It explicitly distinguishes itself from sibling tools like check_coverage and what_changed_since by focusing on fact verification rather than coverage or change detection.

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 gives explicit when-to-use guidance ('CALL THIS BEFORE ACTING ON ANYTHING YOU REMEMBER'), and explains the key semantic distinction of 'unknown' vs 'unchanged'. It also provides usage efficiency advice (batch up to 100 facts) and sets expectations about speed ('Cheap and fast').

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