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

With no annotations available, the description must disclose behavioral traits. It only states that it runs an aggregate query, which is an action but does not mention side effects, authentication needs, rate limits, or what the response contains. There is no mention of output format or potential limitations, leaving the agent with minimal behavioral insight.

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, compact sentence that front-loads the key purpose ('aggregate query'). It is concise and free of fluff, but it sacrifices essential detail. Structure is adequate for a short definition, though the brevity reduces overall value.

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?

This is a complex tool with 7 parameters, no output schema, and no annotations. The description provides almost no context for how to construct an aggregate query (e.g., how group_by interacts with select, what where filtering supports, or what the returned data looks like). It is far from complete for an agent to call it 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 only 14% (only 'select' has a description). The tool description does not compensate for the lack of explanation for portal_url, dataset, group_by, order_by, where, and limit. No parameter semantics are added beyond what the schema barely provides, so an agent cannot understand the role of most parameters.

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 a specific action ('Run an OpenDataSoft Explore v2.1 aggregate query') on a resource ('any dataset'). The term 'aggregate' distinguishes it from the sibling tool query_records, which likely handles plain queries, but it does not explicitly name that alternative. It is specific enough to understand the tool's function.

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?

There is no guidance on when to use this tool versus alternatives like query_records or inspect_dataset. It only states that it runs aggregate queries, which implies a use case but provides no exclusions, prerequisites, or context to help an agent decide between siblings.

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?

No annotations are provided, so the description must carry the full behavioral burden. It only states that it compares expected fields to the schema, but does not disclose whether the operation is read-only, what happens on mismatches, whether it raises errors, or what the return value looks like. This lack of detail is insufficient for safe invocation.

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, tightly woven sentence with no filler. It front-loads the core action and stays within one line, which is ideal for quick parsing by an agent. No unnecessary words or redundant 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?

Given that there are no annotations, no output schema, and only one documented parameter, the description is far too sparse. It does not explain the expected result (e.g., a boolean, a list of differences, an error), how the comparison is performed, or any prerequisites like dataset existence. An agent would need to inspect sibling tools or guess to use this 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?

The schema description coverage is only 33% (only expected_fields has a description). The tool description does not compensate by explaining portal_url or dataset parameters. It adds no parameter-level detail beyond what is already minimal in the schema, leaving the agent to guess the purpose and format of two key arguments.

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 ('Compare expected field names against the current OpenDataSoft dataset schema'), specifying the verb and resource. It is easy to understand what the tool does, but it does not explicitly distinguish itself from sibling tools like inspect_dataset, which also deals with dataset schema. Thus a 4 is appropriate.

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 provides no guidance on when to use this tool versus alternatives such as inspect_dataset or query_records. There is no mention of context, constraints, or exclusions. The only hint is the word 'expected' implying a validation use case, but this is not explicit.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure, but it states only the action and selection method. It omits any information about side effects, return format, error handling, or whether the operation is safe (read-only), which is especially important for a tool with no 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, tight sentence with no filler and the action is front-loaded. It is appropriately sized for a two-parameter tool, though brevity comes at the cost of missing behavioral 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?

Given no annotations and no output schema, the description is too sparse. It fails to explain the max_chars parameter, the nature of the excerpt, or error behavior. An agent would need to assume critical details, making it incomplete for reliable 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 50% (only source_key has a description). The tool description repeats the selection method already in the schema but adds no detail for max_chars, which lacks schema documentation. The description does not compensate for the missing parameter semantics.

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 ('fetch') and clearly identifies the resource ('short text excerpt from a curated source') and the selection method ('by index or title keyword'). This is distinct from sibling tools that list sources or query records, making 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 provides no guidance on when to use this tool versus siblings like opendatasoft_universal_query_records or inspect_dataset. It does not mention exclusions or alternatives, leaving the agent to infer the appropriate context.

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?

No annotations are provided, so the description carries the full burden. While 'list' implies a non-destructive read, the description does not disclose whether authentication is required, response format, or any limitations. It adds minimal behavioral context beyond the verb.

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, front-loaded sentence that succinctly states the tool's purpose with no filler. It is highly concise and well-structured.

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 has no output schema, so the description should clarify what the returned 'sources' look like. It only says 'list curated sources' without specifying the format or content, leaving some ambiguity. However, given the low complexity, it is mostly adequate, but not fully complete.

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 the schema is trivial. The baseline for 0 params is 4, and the description does not need to explain parameters. It adds no extra parameter information, which is appropriate since none exist.

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 a specific action ('List') and resource ('curated sources'). It is distinct from sibling tools like search_catalog or fetch_source_excerpt, though it doesn't explicitly differentiate. Not a tautology, but could be more precise about the scope of 'curated sources'.

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 provides no guidance on when to use this tool versus alternatives like opendatasoft_universal_search_catalog or fetch_source_excerpt. It only states its function without any context or exclusions, leaving the agent to infer its usage.

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?

With no annotations provided, the description must carry the full burden of behavioral disclosure. It indicates a read-only connectivity check but does not state what happens on failure, whether it returns a boolean or detailed status, or any side effects. The single sentence lacks the necessary detail for an agent to anticipate behavior beyond the basic purpose.

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 concise—a single sentence with no waste—and front-loads the action. However, it is too terse to cover essential behavioral and parameter semantics, suggesting brevity at the expense of completeness. It is not inappropriately long, but it under-specifies.

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 health-check tool with no output schema and no annotations, the description is incomplete. An agent cannot know what result to expect (e.g., status code, boolean, error details) or how to interpret the check outcome. The description leaves critical context undefined, making it insufficient for reliable 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?

The schema covers only the 'dataset' parameter with a description; 'portal_url' has no description and is required. The tool description mentions 'portal' but doesn't clarify the expected format or meaning of portal_url beyond being a URI. Since schema coverage is 50%, the description should compensate for the undocumented parameter, but it doesn't, leaving ambiguity.

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 ('check') and resource ('portal and optional dataset'), and specifies the context (reachability through Explore v2.1). It clearly distinguishes itself from sibling tools that fetch data or query records, though it doesn't explicitly name an alternative. The purpose is 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 implies usage as a health check before other operations, but does not explicitly state when to use this tool versus alternatives like opendatasoft_universal_query_records or opendatasoft_universal_inspect_dataset. There is no guidance on exclusions or prerequisites. The context is clear but lacks explicit 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?

With no annotations, the description carries the full burden of behavioral disclosure. It implies a read-only inspection but does not explicitly state so, nor mention any side effects, permissions, limitations, or output format. This is a significant gap for an inspection tool.

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, which is appropriately brief, but it is under-specified rather than concise in an effective way. It does not waste words, but it also does not earn its place by conveying necessary information. A balanced description would be longer but more informative.

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 tool with only two parameters and no output schema, the description should at least explain what the inspection returns and how it differs from similar tools. It is incomplete, offering no context about the dataset schema structure, possible error cases, or usage scenarios.

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 description coverage is 0%, so the description must compensate by explaining the parameters. It fails to clarify what 'dataset' and 'portal_url' refer to, their expected formats, or how they interact. The description adds no meaning beyond the parameter names themselves.

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 inspects a dataset schema on an OpenDataSoft portal. The verb 'inspect' and resource 'dataset schema' are specific, but it does not distinguish itself from the sibling 'check_schema', which might serve a similar 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?

No guidance is provided on when to use this tool versus alternatives like 'check_schema' or 'get_sources'. The description does not mention any context in which this tool is preferred, nor any exclusions or prerequisites.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description merely says 'Query records,' implying a read operation, but it does not explicitly state that it is non-destructive or disclose any limitations (e.g., pagination, rate limits, authentication requirements). It fails to add context beyond the obvious.

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, concise sentence with no wasted words and is front-loaded with the primary action. However, it is under-specified, which makes it too terse to be genuinely useful. It achieves brevity but at the cost of necessary detail.

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 no annotations, no output schema, and zero parameter documentation, the description is severely incomplete. An agent lacks critical information about parameter syntax, expected response format, request examples, or edge cases. This is a query tool that needs much more context to be callable 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?

With 0% schema description coverage, the description is the only source of parameter meaning, but it explains none of the six parameters. The agent has no idea what 'where', 'select', 'order_by', 'limit', 'dataset', or 'portal_url' do beyond inferred naming. This is a critical gap for a query tool.

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 a specific verb (Query) and resource (records from any OpenDataSoft Explore v2.1 dataset). It implies a read-only operation and distinguishes from siblings like aggregate_records (aggregation) and search_catalog (catalog search). However, it could be more explicit about the exact scope (e.g., filtering, selecting, sorting) and how it differs from other query-like siblings.

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?

There is no guidance on when to use this tool versus alternatives. Given siblings such as aggregate_records and search_catalog, the description does not mention scenarios where one might prefer this tool, nor does it note any exclusions or prerequisites. An agent must infer usage from the name alone.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only says it searches a catalog; it does not mention pagination, limit behavior, return format, authentication requirements, or any side effects. For a tool with no annotations, this is a severe gap. The description is essentially a one-line purpose statement with zero behavioral information.

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, succinct sentence with no wasted words. It is front-loaded with the main action ('Search any OpenDataSoft Explore v2.1 catalog') and is appropriately brief for a tool with a simple purpose. However, it is so truncated that it lacks structural detail, so it earns a 4 for conciseness rather than a 5.

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 has three parameters, no output schema, and no annotations. The description does not explain what the search returns (e.g., dataset summaries, metadata), how results are ordered, or any constraints beyond what the schema specifies. An agent would not know what to expect from the response or how to interpret results. This is incomplete for a tool that likely returns a complex list of catalog entries.

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 67% (two of three parameters have descriptions: 'query' and 'portal_url'; 'limit' has no description but has default/min/max). The tool description adds no additional parameter details beyond what the schema already provides. With coverage above 50%, the baseline is 3, and the description does not augment or clarify parameter semantics further.

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's purpose: to search any OpenDataSoft Explore v2.1 catalog. The verb is specific ('Search') and the resource is a catalog, which distinguishes it from the sibling tools that target sources, datasets, or records (e.g., opendatasoft_universal_inspect_dataset, opendatasoft_universal_query_records). However, it does not explicitly contrast with these siblings, so it earns a 4 rather than a 5.

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 searching a catalog but provides no guidance on when to use it versus alternatives. It gives a clear context (search a catalog) but lacks any exclusions or comparisons to sibling tools. This qualifies as 'implied usage' with no explicit when/when-not guidance.

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