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

With no annotations at all, the description carries the full burden, yet it only discloses the returned fields (name, category, description). It says nothing about pagination, result ordering, catalogue size, or that the call is read-only beyond the verb "List" — meaningful gaps for a list tool with a filterable catalogue.

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 front-loaded sentence with the returned shape in parentheses and the filtering options trailing it — no wasted words, nothing buried.

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?

There is no output schema, so stating the returned fields is valuable, and read-only listing needs little safety context. But the unexplained `proven` parameter and the absence of any hint about result volume or ordering leave the definition only minimally sufficient.

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 coverage is 67% and the description reinforces the two filter parameters (category, model family), but it completely omits the third parameter `proven`, whose semantics (works-on-5-models, 365-day window) are subtle even in the schema. Baseline 3 fits given a moderate coverage level with one notable omission.

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?

States a specific verb and resource ("List all skills") plus the fields returned, which cleanly separates it from get_skill. However it never names the sibling it competes with (search_skills), so the differentiation is only implicit from the verb.

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?

"Optionally filtered by category and/or AI model family" implies when the filters apply, but there is no statement of when to use this versus search_skills or list_categories, and no note that omitting the filters returns the full catalogue.

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