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

Annotations indicate readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description aligns with these, adding the behavior of array fields counting each element and default sorting. It also mentions that the filter applies first, influencing results. This adds some value beyond annotations, but it doesn't disclose potential performance implications or edge cases like missing fields.

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 two sentences with high information density. It front-loads the core behavior, then covers edge cases (arrays) and optional filtering. No fluff; every sentence earns its place.

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 read-only aggregation tool with a well-documented filter schema, the description covers the essential aspects: what it does, how arrays are handled, and that filter applies first. It could mention the return format (e.g., array of {value, count}) since there is no output schema, but the absence is not critical for calling the tool correctly.

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 description coverage is 50%: the filter parameter is well-documented in the schema, but the field parameter has no description. The tool description does not add any details about the field parameter (e.g., type, syntax, examples). It implicitly clarifies that field is used for grouping, but the schema already does that. With only half the parameters covered, the description should compensate but doesn't significantly.

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 clearly states the action (group and count), the resource (records by a field), and the ordering (most common first). It also explains a key nuance: array fields count each element. It distinguishes itself from siblings like catalog_stats by focusing on counting per value rather than aggregate statistics, though it doesn't explicitly name an alternative.

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 when to use this tool: when you want a frequency distribution of field values. It mentions an optional filter but does not specify alternatives or when not to use it. For example, it doesn't differentiate from catalog_values (which might return distinct values) or catalog_stats (aggregates). The usage guidance is clear but not exhaustive.

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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the return shape '{ found, record }', which is not in the annotations, and clarifies the key field. This adds useful behavioral context beyond what annotations provide.

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 two short sentences, front-loaded with the action and includes the return shape. Every word is necessary; no fluff or redundancy.

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 read tool with annotations covering safety and a schema documenting the required key, the description is mostly complete. It explains the return shape and key field. The only gap is the optional 'fields' parameter, which is not mentioned, but that is a minor omission for the core use case.

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 only 50%: the 'key' parameter has a description, but 'fields' has none. The tool description does not mention 'fields' at all, so an agent using this description alone would not know that field selection is possible. The description adds no meaning beyond the schema's existing key description, so it fails to compensate for the missing field documentation.

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 the verb 'Fetch' with a specific resource 'a single record' and identifies the key field ('id'), distinguishing it from siblings like catalog_query for multiple records or catalog_count_by for counting. This makes the tool's purpose unambiguous.

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 clearly states the intended use case: fetching one record by its key. It does not explicitly mention alternative tools or when not to use it, but the context is clear enough to infer. No exclusions are given, so a 4 is appropriate.

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 establish that this is a safe, read-only, idempotent operation, so the bar is lower. The description adds useful behavioral context by stating the exact return shape and by giving a concrete filter example, which reveals how records are matched and combined without hiding edge cases.

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 dense, front-loaded sentences with no filler. The return contract, prerequisite sibling tool, and a working example are packed into a compact definition that earns its length.

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?

Given the read-only annotations and no output schema, the description is nearly complete: it covers purpose, return values, a filter example, and a prerequisite. It does not spell out offset/limit pagination behavior beyond 'page through', but the schema defaults and constraints cover the mechanical details.

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 description coverage is only 50%, so the description carries some burden for parameters like limit, offset, and sort_dir. The filter example does add semantic value for filter and sort_by, but it does not compensate for the undocumented pagination and sorting-direction parameters, which remain dependent on schema names and defaults.

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 opens with a specific verb phrase — 'Filter, sort, and page through catalog records' — that names the resource and the operations precisely. The stated return shape also disambiguates it from the sibling tools like catalog_stats or catalog_get.

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?

It gives explicit guidance to 'Use catalog_schema first if you are unsure which fields exist', which tells the agent when to consult a sibling first. It does not explicitly exclude alternative tools like catalog_top or catalog_count_by, but the query/filter context is clear enough for a capable agent.

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 the operation safe via readOnlyHint, openWorldHint, idempotentHint, and non-destructiveHint. The description adds value by revealing that the schema is inferred from the records themselvesans, so its shape is data-dependent, and by detailing the returned content beyond what annotations express.

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 two tight sentences with no filler. It front-loads the concrete field inventory output before the usage directive, making the purpose immediately obvious.

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, read-only introspection tool, the description fully covers what the tool returns, when to call it, and how the schema is derived. Annotations cover side-effect safety, so no 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?

The tool has zero parameters, so parameter semantics are trivially satisfied; there is nothing for the description to elaborate. The baseline of 4 applies because no parameter documentation burden exists.

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 specific verb and output: 'field inventory inferred from the records themselves' and enumerates exactly what is included (type, coverage, numeric min/max, sample values). This clearly distinguishes it from siblings like catalog_stats or catalog_values, which serve different analytical purposes.

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 phrase 'Call this first when exploring an unfamiliar catalog' provides explicit when-to-use guidance and establishes the tool as the initial exploration step. It does not explicitly name sibling alternatives, but the sequencing instruction is clear enough for routing.

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 cover read-only, idempotent, non-destructive behavior. The description adds useful behavioral context beyond the schema: output includes cache age, and the refresh parameter can bypass the cache. This is consistent with the annotations and gives the agent a clearer operational picture.

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 with no filler. It front-loads the core output components and packs meaningful detail about optional numeric summaries into a compact, readable form.

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?

With only two optional parameters and no output schema, the description provides a reasonable high-level account of what is returned. It could be more precise about the meaning of 'source' or the exact response structure, but the essential call behavior and output scope are clear enough for an agent.

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 description coverage is only 50%, with numeric_fields having no schema-level description. The tool description compensates by explaining that numeric summaries (count/min/max/mean/median) are computed for the fields you name. The refresh parameter is already adequately described in the 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 clearly states the tool returns record count, source, cache age, and optional numeric summaries for named fields. It does not use an explicit verb but is specific about the resource and output. It does not explicitly differentiate it from siblings like catalog_count_by or catalog_values.

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 use case is implied: an agent would call this when it needs catalog totals, freshness, or numeric summaries for specified fields. However, there is no explicit guidance about when to choose this over sibling tools, nor any exclusions or alternative routing.

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 readOnly, non-destructive, idempotent behavior, so the description need not repeat safety. It adds useful ranking/filter semantics and a concrete example, though it does not explain edge cases like records missing the sort_by field.

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 sentences, with the core action first and a concrete example second. No filler or redundancy.

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?

The tool is simple enough and the schema covers filter syntax, limit bounds, and sort direction defaults. But there is no output schema and the description does not state the return shape (full records vs. projected fields), which is a notable gap for correct invocation.

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 description coverage is only 20%, so the description should compensate; the example meaningfully maps sort_by, sort_dir, and filter together. However, it does not clarify the fields parameter or how limit interacts with ranking, leaving a partial gap.

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 clearly states it ranks records by a numeric field with optional filtering, and the worked example (sort_by price, sort_dir asc, filter has features) demonstrates a concrete use. This distinguishes it from siblings like catalog_get, catalog_count_by, and catalog_values.

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 when to use it: when you need ordered/top-N records over a numeric field, optionally narrowed by a filter. The example gives a concrete scenario, but it does not explicitly name alternatives 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context: it returns occurrence counts, sorts most common first, and positions itself as reliable for vocabulary discovery. It doesn't mention pagination or what happens with high-cardinality fields, but the limit parameter with '0 = unlimited' partially covers that.

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 sentences with no wasted words. The first sentence states the core behavior (distinct values, counts, ordering), and the second adds the practical use case. Information is front-loaded and every word earns its place.

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 read-only, idempotent tool with two parameters and no output schema, the description is nearly complete. It explains what the tool returns (distinct values with counts, sorted) and when to use it. The only minor gap is not describing the output format structure (e.g., array of objects with value/count keys), but the description's clarity compensates for the missing 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 description coverage is 50%: 'field' has no description, while 'limit' has a description and default. The description clarifies that the tool returns distinct values with counts, which implies the 'field' parameter is the target field. It doesn't add detail about the 'limit' parameter beyond the schema, but the schema already documents it well. The description compensates for the undocumented 'field' parameter by explaining the tool's purpose.

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 specific verb ('catalog') and resource ('values of a field'), and clearly distinguishes itself from siblings by emphasizing occurrence counts and ordering. It also explains the practical use case (learning a categorical field's vocabulary before filtering), which makes the tool's purpose immediately clear.

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 when to use this tool: when you need distinct values with counts before filtering. It doesn't explicitly name alternatives or exclusions, but the phrase 'reliable way to learn a categorical field's vocabulary' provides clear context. Sibling names like catalog_top and catalog_count_by suggest related tools, but the description doesn't explicitly contrast them.

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