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. It only says 'Return', which implies a read operation, but does not explicitly state that it is read-only, nor does it disclose error behavior, authentication needs, rate limits, or side effects. This is a minimal gap for a GET-like tool but still below the bar.

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 short and front-loaded with the primary purpose, followed by a structured args line. No wording is wasted, though the 'Args' block partially overlaps with the input schema. Overall it is appropriately sized.

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 tool with an output schema, the core mechanics are covered: what it returns and what the parameter means. However, the absence of explicit usage guidance, behavioral safety disclosure, and error handling leaves the description only minimally viable for an agent to confidently use it in a broader workflow.

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 0%, but the description compensates with 'dataset_id: Dataset id or slug'. This adds crucial semantic meaning beyond the raw schema's 'type: string' by clarifying that both a dataset ID and a human-readable slug are accepted.

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 ('Return') and resource ('dataset metadata and resources') and explicitly scopes the operation to one dataset. The distinction from the sibling datagouv_search_datasets is apparent: this retrieves one known dataset rather than discovering many.

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 the tool by indicating it returns a single dataset and requires a dataset_id or slug. However, it does not explicitly state when not to use it, mention prerequisites like knowing the ID, or recommend datagouv_search_datasets for finding datasets.

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 behavioral burden. It adds useful search-scope details and a page_size guard ('keep reasonably small, e.g. ≤ 100'), but it does not disclose authentication needs, rate limits, result ordering, or whether search is fuzzy/exact.

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 main purpose is front-loaded in one line, followed by compact and complete Args entries. Every sentence earns its place, and there is no repetition of schema defaults or irrelevant 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?

For a simple 3-parameter search tool with an output schema, the core calling contract (free-text query, pagination, size limit) is fully covered. The main missing context is explicit differentiation from sibling toolsarkan otherwise minor gap given the output schema covers return shape.

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 0%, but the description compensates fully for all three parameters: query is labeled 'free-text search', page is '1-based', and page_size gets explicit sizing guidance. This adds real meaning beyond the raw schema property 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 states 'Search datasets' and specifically lists the searchable fields (title, description, organization), making the tool's action and resource clear. This clearly differentiates it from the sibling datagouv_get_dataset, which is a direct fetch rather than a search.

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 implies this is the dataset discovery/search tool, but it never explicitly says when to use it versus datagouv_get_dataset or the geo/insee search siblings. No alternatives, exclusions, or routing conditions are stated.

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 burden of behavioral disclosure. It usefully explains the code format and the Corsica 2A/2B edge case, but it does not describe behavior for invalid or not-found codes, or any other runtime traits. This is moderate but incomplete.

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 compact: one sentence states the core purpose, and the second sentence explains the parameter format. There is no filler or repetition.

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 get-by-code tool with an output schema, the description is nearly complete. It could additionally mention using geo_search_communes when a code is not known, but that is a minor enhancement rather than a critical gap.

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 only defines 'code' as a required string, while the description adds substantial meaning: it is an INSEE commune code, exactly 5 characters, with a specific note about Corsica. This fully compensates for the 0% schema description coverage.

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 ('Return') with a precise resource ('one commune') and identifier ('INSEE municipality code'). This clearly distinguishes it from sibling tools like geo_search_communes, which search, and geo_get_departement, which targets a different geographic entity.

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 usage context is clear: call this tool when you have a specific INSEE commune code and need the corresponding commune. It does not explicitly name alternatives or exclusions, so it falls just short of a 5, but the get-by-code framing leaves little ambiguity.

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 description adds the conditional behavior 'including its region when available,' which is useful context beyond the schema. With no annotations, it does not disclose error handling for unknown codes or explicitly confirm it is read-only, but for a simple getter this is a modest gap.

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 very short, front-loads the core behavior, and contains no filler. The Args section efficiently communicates the parameter meaning and examples.

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 one-parameter getter with an output schema, the description covers what is returned, how to specify the department, and the region condition. It lacks a note about unknown-code behavior, but the tool's simplicity and output schema reduce the need.

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 only declares code as a string, so the description's 'Official department code' with examples '13, 75, 2A' adds essential formatting and domain meaning. It compensates well for the 0% schema coverage on the single parameter.

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 resource: 'Return one department by code' and mentions the region inclusion. It implies a distinct exact-code lookup compared to sibling search tools, but it does not explicitly name or contrast itself with geo_search_departements.

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 'by code' clearly implies this tool is for callers who already have an official department code. However, it gives no explicit guidance about when to prefer a search sibling or when this tool should not be used.

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?

There are no annotations, so the description carries the full burden. It does disclose the core behavior: the tool retrieves and returns one region by code, and it adds that the code is an 'Official region code.' It does not mention what happens for unknown or malformed codes, or any other edge behavior, but for a simple read-style getter the disclosed behavior is adequate though incomplete.

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, front-loaded with the core action, and includes only the one parameter explanation that matters. There is no filler or repetition of the tool name beyond the docstring-style parameter label.

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 lookup with an output schema, the description is nearly complete: it states what is returned, by what key, and gives an example. The main missing context is routing guidance toward the sibling search tool and clarifying not-found behavior, but these are minor for a simple getter.

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 input schema only declares that code is a string with no description, so the description adds meaningful value by calling it an official region code and giving the concrete example '11' for Île-de-France. With only one parameter and a degenerate schema, this is strong compensation for the 0% schema coverage.

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 and resource combination: 'Return one region by code.' It is clearly distinguished from sibling geo_search_regions, which implies searching multiple regions, because this tool fetches a single region by an official code. For a simple getter this is exactly the level of specificity an agent needs.

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 intended usage is implied rather than explicit: it is appropriate when a region code is known and exactly one region is wanted. However, the description does not mention the alternative geo_search_regions or state when not to use this tool, so the agent must infer the decision boundary.

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 full responsibility for behavioral disclosure. It does add valuable context: the upstream API can return large slices, hence the bounded-query requirement, and explains the boost_population ranking effect. However, it does not mention authentication, rate limits, or whether this is a read-only operation (trivially implied by 'search'). Some behavioral aspects like pagination or error handling are absent, though the output schema may cover returns.

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 compact and well-organized: a one-line purpose, a critical usage constraint, and then a clean Args list. Every sentence earns its place; the most important operational caveat (bounded query) is highlighted early. No redundancy or fluff.

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 description covers all parameters, their optionality, the mandatory filter requirement, and safe usage limits. Since an output schema exists, not describing the return format is acceptable. The only minor gap is lack of explicit differentiation from geo_get_commune, but the search semantics are clear. Overall, an agent can correctly call this tool with confidence.

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 description includes an explicit Args section that explains every parameter: nom (substring/fuzzy), code_postal (five-digit), code_departement (department code), boost_population (ranking by population), and limit (maximum results). It also states the interdependency constraint (at least one of the three filters). The input schema provides no descriptions of its own, so this description adds substantial meaning beyond types 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 'Search communes by name, postal code, and/or parent department' – a clear verb, resource, and search criteria. This immediately differentiates it from siblings like geo_search_departements or geo_search_regions, which target different geographies. 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 clearly states a required precondition ('At least one of nom, code_postal, or code_departement must be non-empty') and gives guidance on limit ('keep small, e.g. ≤ 50'). It does not explicitly contrast with geo_get_commune (which likely retrieves by ID), but the search-oriented purpose is implied clearly enough from the name and context. No misleading exclusions.

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 behavioral burden. It discloses fuzzy-search behavior, optional name filtering, and that limit defaults to cover all mainland and overseas departments. It does not mention read-only status or edge cases, but the key behaviors are transparent.

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 and front-loaded with the primary purpose stated first, followed by a compact Args section. Every sentence adds value with no filler.

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 two-parameter search tool with no required parameters and an existing output schema, the description covers purpose, parameter behavior, and default behavior. The agent has enough to call the tool correctly without missing guidance.

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 0%, so the description fully compensates. It explains nom as a name filter and limit as a row cap, adding meaning beyond the raw schema types 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 states a specific verb and resource: 'List all departments or fuzzy-search them by name.' This clearly distinguishes it from sibling tools like geo_get_departement, which targets a single department by code, and geo_search_communes, which targets communes.

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 clear context for when to use it: when listing all departments or fuzzy-search by name, and explains nom set vs omitted. However, it does not explicitly mention alternatives or exclusions relative to sibling tools like geo_get_departement.

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 burden of behavioral disclosure. It explains the fuzzy-search behavior, the all-regions default when 'nom' is omitted, and the row cap with a useful real-world sizing detail about France's region count.

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 compact, front-loaded with the main purpose, and uses brief bullet-style argument explanations. Every sentence adds useful information without unnecessary 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?

For a low-complexity search/list tool with only two optional parameters and an output schema, the description covers the key behavior and edge cases. It does not mention pagination or exact-match alternatives, but those are not essential for correct invocation here.

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 0%, so parameter documentation in the description is essential. It adds meaningful semantics: 'nom' filters by name when set and returns everything when omitted, and 'limit' caps results.

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 clear verbs 'List' and 'fuzzy-search' with a clear resource ('regions'), making it clear this tool is for listing all regions or searching by name. It also distinguishes itself from sibling tools targeting different geographic objects such as communes and departements.

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 clear parameter-level guidance: set 'nom to filter by name, omit it to return all regions, and use 'limit' to cap rows. However, it does not explicitly contrast this tool with siblings like 'geo_get_region' or explain when to prefer this search tool over exact-lookup alternatives.

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 burden. It discloses that a valid portal API key is required, which is useful. However, it doesn't describe the return format, error behavior, or rate limits. The description adds some behavioral context but not comprehensive detail.

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 compact and front-loaded. The first sentence states the core purpose, the second gives usage context, and the third covers the parameter. Every sentence earns its place with no 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 single-parameter lookup tool with an output schema present, the description covers the key aspects: what it returns, when to use it, the parameter format, and the auth requirement. It doesn't mention error cases or response structure, but the output schema likely covers the return shape. Minor gap: no explicit mention of what happens for invalid SIRETs.

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 0%, so the description must compensate. It does: it explains the siret parameter is a 14-digit SIRET with spaces optional, and explains the SIREN+NIC composition. This adds meaning beyond the bare schema type string.

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 an establishment for a 14-digit SIRET, and distinguishes it from the sibling insee_get_unite_legale by explaining that SIRET includes SIREN plus NIC. This is a specific verb+resource with enough detail to differentiate it from related tools.

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 explains when to use this tool (for a specific branch or address) and implicitly contrasts it with the SIREN-based sibling. It doesn't explicitly name the alternative or state when not to use it, but the SIRET vs SIREN distinction provides clear 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. It discloses a meaningful operational requirement ('Requires a valid portal API key') and sketches what is returned (status, denomination, activity codes). Yet it stays silent on failure behavior (e.g., unknown SIREN), rate limits, and whether the response is a raw records envelope. Decent but not exhaustive for an unannotated 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?

Compact and well-ordered: the purpose is front-loaded in the first line, followed by a single usage sentence and an Args block. No filler, 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?

Low complexity (one required parameter) with an output schema present, so return-value detail is not needed. The description covers the data returned, the parameter format, and the auth requirement. Housekeeping details like error semantics and rate limits are the only gaps, which are minor for a simple lookup tool.

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 0%, so the description must compensate, and it does: 'Nine-digit SIREN (spaces optional)' documents the expected format and normalizability beyond the bare string type in the schema. This is genuinely added value for the only parameter.

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 resource: 'Return the legal unit (unité légale) for one 9-digit SIREN.' It implicitly differentiates itself from sibling insee_get_etablissement by keying on SIREN vs. SIRET, and the use case 'resolve a company identifier to its official INSEE record' sharpens the intent. It doesn't explicitly name the sibling, but the purpose is 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?

'Use this to resolve a company identifier to its official INSEE record' gives a clear when-to-use context. However, there is no mention of the natural alternative insee_get_etablissement, no exclusions, and no guidance on when NOT to use this tool. The when-to is present, but the when-not-to is 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?

No annotations are present, so the description carries the full behavioral burden. It explicitly discloses that mutations are possible, which is important, and mentions using an API token in the hosted explorer. However, it does not explain authentication requirements for actual execution, rate limits, error behavior, or side effects beyond the word 'mutation'.

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 well structured and appropriately sized: it front-loads the purpose, provides the documentation link, gives discovery guidance, and then clearly documents both parameters. Every sentence contributes useful information without 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?

Given the tool's simplicity, the presence of an output schema, and only two parameters, the description covers the essential aspects: what the tool does, how to discover the GraphQL schema, and how to supply parameters. It could be more explicit about authentication for API calls, but the mention of an API token in the explorer partially addresses this.

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 0%, so the description must compensate. It does so by explaining that 'query' is a GraphQL document and that 'variables' is optional and should be omitted or an empty dict when unused. This adds meaningful semantic guidance beyond the bare schema types.

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 executes a GraphQL query or mutation against the Radio France Open API, naming the specific resource and action. This differentiates it from the sibling tools, which target unrelated data sources and APIs.

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 clear context by linking to the upstream API documentation and directing users to use introspection or the hosted explorer to discover fields and types. It does not explicitly contrast with alternatives, but there are no similar GraphQL siblings, so the context is sufficient.

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