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

Annotations include readOnlyHint true and idempotentHint true, and the description does not contradict them. It adds useful behavioral context: the alignment algorithm for sentences, the handling of negation/antonym flips, and the explicit caveat about lexical limitations ('cannot follow a paraphrase...'). This exceeds the baseline for a read-only tool.

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 detailed yet well-structured, with a clear explanation, a concrete example, and a limitation note. It might be slightly long but each sentence earns its place; it's front-loaded with the core purpose and usage.

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 complexity, the description covers the main use case, limitations, and provides an example for clarity. The schema covers parameters and output schema exists, so completeness is good for an LLM agent to invoke correctly, though it could add a bit more about the verdict values ('contradicted', 'well_grounded') but these are implied.

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 100% and does not contradict: it describes the behavior and the strict parameter's meaning briefly, but the schema already defines all parameters. The description adds explanation about sentence alignment for 'strict' mode behavior, which is helpful, so it meets the baseline with slight bonus.

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 states the tool performs a 'lexical' hallucination check, explicitly verifying words, numbers, and polarity against a source. It distinguishes itself from sibling tools like semantic tests by emphasizing its fast, deterministic, and lexical nature, and even names the alternative (run_semantic_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?

It clearly explains when to use this tool: for quick, deterministic verification of factual alignment, and when not to use it: when entailment or deeper reasoning is needed ('For entailment use run_semantic_tests'). It also mentions limitations that guide appropriate usage.

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