catalog

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the burden is lower. The description adds meaningful context: it returns a 'full catalog card', includes the connector URL, and frames the purpose as 'your agent connects to consult them', which goes beyond the 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 a single sentence that front-loads the core purpose and adds no filler. Every phrase contributes value: what is returned, how it is identified, and what the connector URL enables.

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 one-parameter read-only lookup with an existing output schema and thorough annotations, the description is sufficient. It tells the agent what the tool does, what the key input is, and what the returned card includes. No critical operational detail 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?

Schema coverage is 100% and the parameter is already described as 'An id returned by search.' The description adds extra meaning by clarifying that the id is 'their slug', which is not present in the schema and helps the agent understand the value format.

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 specific verb plus resource: 'Full catalog card for one expert by id (their slug)'. It clearly differentiates from the sibling 'search' by narrowing to a single item and explicitly including the MCP connector URL.

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 context is clear: use this after obtaining an expert id via search, since the schema notes 'An id returned by search.' It implies this tool is for retrieving one full expert record, but it does not explicitly name search as the alternative or state 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.

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so 'Read-only' merely restates structured data and earns no extra credit. The description does add behavioral scope ('published' experts only) and return-shape guidance (ids to pass to fetch), but omits ranking, result limits, or pagination.

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?

Three short sentences, front-loaded with purpose, then the downstream usage, then the safety note. No filler and nothing that could be trimmed without losing information.

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?

A single-parameter search tool with an output schema and rich annotations needs only purpose, scope (published only), and workflow placement — all of which are present. Return-value details are correctly deferred to the 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 is 100%, so the baseline is 3, but the description goes beyond the schema's generic 'What kind of judgment you are looking for' by enumerating the query facets (domain, decision types, free wording), which genuinely guides how to phrase the query.

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?

Specific verb+resource ('Find published experts') with the searchable facets named (domain, decision types, wording). It also implicitly distinguishes itself from its only sibling by stating it returns ids 'for fetch', so an agent can tell search from fetch immediately.

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?

'Returns result ids for fetch' establishes the search-then-fetch workflow, telling the agent this is the entry point and fetch is the follow-up. There is no explicit statement of when NOT to use it or of alternative query strategies, but for a two-tool workflow the routing is clear.

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