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

No annotations are provided, so the description bears the full behavioral burden, yet it only explains what a 'proof' is conceptually. It says nothing about return shape, ordering, pagination, or count limits for what is evidently a list endpoint.

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?

A single compact sentence with no filler, and the defining qualifier ('have a published proof') is placed first. It is efficient, though it lacks an explicit action verb to front-load.

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 zero-parameter list tool with no output schema and no annotations, the description covers the domain concept but omits whether a list is returned, how items are ordered, and whether results are paginated. Adequate but with clear gaps against the tool's actual shape.

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 tool takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. No parameter-level gaps exist to compensate for.

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 defines the domain concept ('skills that have a published proof') but never states the operative verb — it reads as a definition rather than 'returns/lists skills'. An agent can infer it is a listing operation from the name, but the sentence itself doesn't assert what the tool does, and it doesn't distinguish itself from search_skills or get_skill.

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?

There is no when-to-use guidance and no mention of the siblings (search_skills could plausibly surface the same set). Nothing tells the agent when to choose this over get_proof or get_skill, so selection must be inferred entirely from the name.

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