catalog

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

Annotations already cover read-only, idempotent, and non-destructive behavior; the description adds useful context that the returned catalog card includes the MCP connector URL, and clarifies that the id is actually the expert's slug. No contradiction with annotations.

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 one compact sentence that front-loads the core purpose, specifies the key output feature, and notes read-only behavior. Every phrase earns its place with no fluff or repetition of obvious schema details.

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 simple single-parameter, read-only fetch tool with an output schema and strong annotations, the description provides all necessary semantics: what the tool returns, what the id means, and the special connector URL. Nothing essential is missing.

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 already documents the single required parameter, so the baseline is high. The description adds meaningful nuance by explaining that 'id' is the expert's slug, and the schema's note that it comes from search complements that. Coverage is 100%, and the description strengthens the meaning beyond the raw schema.

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 a clear verb, 'Full catalog card for one expert by id', and distinguishes the tool from the sibling 'search' by focusing on a single record retrieved by identifier. The added detail about including the MCP connector URL gives a precise, non-redundant purpose.

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 implies the tool is for retrieving a single expert once its id/slug is known, but it never explicitly says 'use this when you have an id from search' or contrasts it with the sibling 'search'. The usage is clear enough by context, but exclusions or alternative-selection guidance are absent.

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

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds the important behavioral detail that the tool returns result ids (not full entity details), which shapes caller expectations. It restates 'Read-only,' matching the annotations without contradiction.

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 three concise sentences with no filler. The 'Read-only.' fragment duplicates the annotation, a minor redundancy, but the rest is tightly packed and front-loaded with the core purpose.

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 single-parameter search tool with an output schema, the description covers the purpose, query semantics, and the relationship to the fetch sibling. It does not detail result limits or pagination, but those are less critical given the simplicity and the presence of an output schema.

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 for the single 'query' parameter is 100%, but the description enriches it by specifying the kinds of accepted queries: domain, decision types, or wording. This gives the agent better guidance on what to put in the query than the schema's generic description alone.

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 uses a clear verb and resource: 'Find published experts' in the Avva expert catalog. It also distinguishes the tool from its sibling by stating it returns result ids for fetch, making the tool's scope unmistakable.

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 implies the intended workflow: search to find result ids, then fetch to retrieve full details. While it does not explicitly say 'use this when you need to locate experts' or exclude fetch, the phrase 'Returns result ids for fetch' provides clear contextual guidance.

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