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

With no annotations, the description carries the behavioral disclosure burden. It supplies a precise verification condition and states that floats are refused, which is meaningful behavioral information. However, it does not say what the tool returns on success or failure, whether it only checks consistency, or what side effects or errors may occur.

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 very short and front-loads the essential mathematical relation. Each sentence adds information: the algorithm identifier, the verification equation, and a type constraint. The cryptic 'QC-007' prefix and the terse 'Floats refused' are compact but not fully self-explanatory.

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 tool with no annotations, no output schema, and three undocumented parameters, this description is incomplete. The formula is useful, but an agent still lacks guidance on input format, return value, error behavior, and how verification outcome is communicated. It is a minimally viable core spec rather than a complete callable contract.

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?

The schema provides no parameter descriptions and coverage is 0%, so the description must compensate. It does relate hidden, queries, and answers through the formula, clarifying that hidden and query_i are bitwise operands and answers is a list of parity bits. Yet it does not explain string encoding, bit order, optionality, or how queries are represented, leaving important format details unresolved.

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 name plus 'Bernstein-Vazirani' and the explicit formula 'answers[i] = popcount(hidden AND query_i) mod 2' identify the algorithm and the core relation being verified. It distinguishes this from the many other verify_* siblings by algorithm name and mathematical condition, though it never states the verb 'verify' directly in the description.

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 no guidance about when to choose this tool over the many sibling verification tools, nor any prerequisites, exclusions, or context for use. The algorithm name implies a domain, but there is no explicit 'use this for Bernstein-Vazirani verification' or statement of when not to use it.

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