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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: the tool returns a pointer (URL) plus index size rather than the ranking itself, and the underlying index is public — which prevents an agent from assuming this call delivers ranking results.

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?

Two tight sentences, front-loaded with the verb and resource, followed by the return payload and the public-index note. Nothing is padded and nothing repeats the title verbatim.

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, and the description compensates by naming the return values (URL and index size). Minor gaps remain — nothing on what happens for an unmatched skill name or whether matching is fuzzy — but for a one-parameter lookup the core is covered.

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 100% schema description coverage on a single required parameter, the schema already explains that 'query' is a skill name or category with an example. The description's phrasing ('skill or category') restates rather than extends that meaning, so baseline 3 applies.

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 names a specific verb ('look up') and resource ('an AI agent skill or category') along with the data source (SkillAssay, outcome-based ranking). It also states what the call yields — the SkillAssay URL plus current index size — so an agent knows exactly what this tool does without opening the schema.

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?

Usage is implied by the statement that the index is public at skillassay.com, suggesting a two-step 'get URL, then query the site' workflow. There is no explicit when-to-use or when-not guidance, but the sibling tools (list_ventures, network_stats, solar_prefeasibility, say_hello) are unrelated, so there is no genuine alternative to route to.

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