HiveCloud CT-e / MDF-e

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

Annotations already mark the tool as idempotent and non-destructive; the description adds meaningful context that the config-based token is permanent/non-expiring while a pasted token is session-only. It also clarifies that calling with no args returns a link, which goes beyond the structured annotations and does not contradict them.

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 and front-loaded with the tool's purpose. It uses 'Best:' and 'Or' to structure two usage paths cleanly. Minor jargon like 'MCP.AI' and 'Cursor, etc.' adds context without being overly verbose.

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 both call patterns and the permanent/session distinction, but it does not state what the tool returns when called with a token (e.g., success message or validation error). Since there is no output schema and no structured return information, this is a meaningful gap for an agent relying on the description to handle the tool's response.

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 an optional 'token' string with 0% coverage, but the description compensates by explaining 'token' is a JWT used for session-only login and that omitting it returns a login link. This gives the agent clear semantics 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 clearly states the tool authenticates to MCP.AI by logging in and obtaining an access token, with concrete steps for browser login and token handling. It names the resource (authentication for MCP.AI) and the verb (log in), but it does not explicitly differentiate from the sibling tool 'connect', which may serve a similar role.

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 gives explicit usage modes: adding the token to server config for a permanent connection, or calling with a token for a session-only login, and calling with no arguments to get the login link. This provides clear context for when to use each invocation, though it does not state when to prefer this tool over alternatives like 'connect'.

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 non-destructive behavior. The description adds valuable context beyond annotations: it discloses the two possible output states (connected vs. missing credentials) and what fields are returned in each case.

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, front-loaded with the core purpose, and every clause adds meaningful information about the tool's behavior. No wasted words.

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 zero-parameter status check with strong annotations, the description covers both the happy path and the missing-credentials state adequately. It does not fully specify the exact shape of the 'pending' field or URL properties, but no output schema exists and the description provides enough for an agent to invoke and interpret results.

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 and schema coverage is trivially 100%. Per the rubric, a zero-parameter tool gets a baseline of 4, and the description appropriately does not need to explain 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 ('Returns') and resource ('connection status and URLs'), clearly stating what the tool does. It also distinguishes itself from sibling tools by focusing on status rather than performing authentication actions.

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 connection status check by describing the conditional outputs, but it does not explicitly state when to use this tool versus alternatives like 'authenticate'. No exclusions or alternative recommendations are provided.

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 indicate readOnlyHint=false, and the description adds the operation's effect and the allow_writes prerequisite. It does not disclose partial failure behavior, idempotency implications, return values, or reversibility, so it adds only limited behavioral context beyond 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 focused sentence that front-loads the action, states the target resource, and includes the key prerequisite. There is no filler; every word contributes to understanding the tool.

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 the core action and a critical authorization condition, which is sufficient for a simple operation. However, it lacks information about expected outcomes, error conditions, or how processing multiple IDs behaves, leaving some operational ambiguity for a mutation tool with no 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 0%, so the description needs to compensate. It clarifies that the required 'ids' parameter refers to CT-e IDs and supports one or more IDs, but it does not explain the optional 'account' or 'empresa_id' fields. This adds meaningful detail for only one of three 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 uses the specific verb 'Averba' and explains it as 'registra o seguro de carga' for 'um ou mais CT-e (por id)'. This makes the tool's purpose clear and differentiates it from sibling CT-e operations such as cancelar, emitir, and excluir.

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 states the permission requirement 'Exige allow_writes' and implies the use case of registering cargo insurance on CT-e documents. However, it does not explicitly say when to prefer this tool over alternatives or provide any when-not-to-use guidance.

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 mark destructiveHint=true and readOnlyHint=false. The description adds 'Irreversible' and 'Requires allow_writes', which are more specific than the hints. However, it does not disclose other side effects (e.g., impact on related documents) or what happens on success/failure. With annotations providing the safety profile, the added value is moderate.

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 'ATO FISCAL REAL', and every word adds value. No fluff 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 destructive fiscal operation with no output schema, the description gives critical warnings (irreversibility, require allow_writes) but misses important context: return values, prerequisites (e.g., authorized CT-e), and parameter meanings beyond ids. It is adequate but not comprehensive.

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 only implicitly covers 'ids' (CT-e IDs) but leaves 'account' and 'empresa_id' completely unexplained. Given all three parameters are required contextually, the lack of clarification for two parameters is a significant 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 the action: cancels one or more CT-e by ID with SEFAZ, and distinguishes it from other CT-e operations like averaging or emission. The verb 'cancels' and resource 'CT-e' are specific, and the phrase 'ATO FISCAL REAL' emphasizes its fiscal nature.

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 mentions 'Irreversible' and 'Requires allow_writes', which imply caution and permission prerequisites. However, it does not explicitly state when to use this versus alternative tools like hivecloud_cte_excluir, or what conditions must be met (e.g., CT-e must be authorized). The guidance is clear but could be more 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?

The description adds valuable behavioral information beyond annotations: it genuinely calls out that this is a *real fiscal act* and that `allow_writes` is required. It also discloses bulk execution support. It does not mention irreversibility or post-issuance effects, but the annotation level provides a baseline and the description meaningfully enhances it.

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 essential real-fiscal-act warning, and presents the intended use plus bulk support in just two paragraphs. There is no redundancy or 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?

Considering the tool has six parameters, no output schema, and no parameter descriptions, the description covers the core purpose, the special object field semantics, the required permission, and bulk alternatives. It does not explain error behavior or fully specify every parameter, but it is enough for a competent agent to select and invoke the tool correctly in most cases.

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 partially compensates by explaining `correcoes` as an object containing only correction fields with examples, and by clarifying `cte_ids` and `empresa_ids` for bulk execution. It leaves `account` largely unexplained and `cte_id`/`empresa_id` implied rather than explicit, but the most important parameter is well-defined.

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 verb and resource: it emits a correction letter (CC-e) for an authorized CT-e. The action is specific and immediately distinguishable from sibling CT-e operations like canceling, averaging, or enumerating CT-e.

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 specifying the CT-e must be authorized and that `allow_writes` is required. It also explains batch usage via `cte_ids` and `empresa_ids`. It does not explicitly name alternatives or exclusions, but the conditions are clear enough.

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?

Beyond the annotations, the description adds substantial behavioral detail: it creates a draft, stays in 'digitação' for review, does not transmit, requires allow_writes, and uses the last authorized CT-e as a base. It also explains that it fills load, values, and parties, and describes bulk execution semantics.

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-structured: the first sentence states the purpose, the second explains the data import and defaults, the third clarifies the non-transmission behavior, and the fourth gives the prerequisite and bulk capability. 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?

Given the tool's complexity (13 params, no output schema), the description provides a solid overview of behavior, state, prerequisites, and bulk support. It doesn't explain what the function returns (e.g., draft ID) or distinguish singular vs. plural parameters like template_cte_id vs. template_cte_ids, which keeps it from a 5.

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 schema_description_coverage at 0%, the description must compensate, and it partially does by naming nfe_chaves, template_cte_ids, and empresa_ids, and explaining that values are auto-filled from the NF-e and last CT-e. However, many parameters (tomador, cfop_codigo, cfop_natureza, responsavel_frete, produto_predominante, observacao, account, etc.) remain unexplained, leaving a significant 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 the tool's specific function: 'Cria um RASCUNHO de CT-e a partir de uma ou mais chaves de NF-e' — creates a draft CT-e from NF-e keys. It explicitly notes that it does NOT transmit to SEFAZ, distinguishing it from siblings like hivecloud_cte_emitir.

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 gives clear context: use this to create a draft for review, not to transmit. It also states a prerequisite ('Exige allow_writes na conexão') and mentions bulk support. However, it doesn't explicitly name an alternative such as 'use hivecloud_cte_emitir to transmit,' so it falls just short of a 5.

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/idempotent/non-destructive behavior, and the description adds matching context by saying 'não altera o documento' and noting the returned URL is temporary. It also clarifies that one or more CT-e can be processed in a single call, which is useful beyond the schema.

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 concise sentences lead with the main action, then add scope, output, and side-effect information. No filler or redundant restatement of the tool name.

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 purpose, applicable state ('autorizados'), output, and side-effect safety, which is enough for a low-complexity read-only tool without an output schema. The main gap is incomplete parameter semantics for account/empresa_id, but the core invocation path is clear.

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 schema description coverage at 0%, the description must compensate for undocumented parameters. It only clarifies that 'ids' refers to one or more authorized CT-e; 'account' and 'empresa_id' receive no explanation, leaving meaningful ambiguity for a 3-parameter 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 uses a specific verb ('Gera o PDF do DACTE') and clearly identifies the resource ('um ou mais CT-e autorizados') and the output (temporary download URL). This distinguishes it from sibling tools like hivecloud_cte_xml or hivecloud_cte_emitir.

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 states the target condition ('CT-e autorizados') and compares the behavior to the issuer's 'Imprimir DACTe' button, giving users a clear mental model of when to invoke it. It does not explicitly name alternative tools or list exclusion cases, so it falls short of a 5.

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 note 'ATO FISCAL REAL' and the requirement of allow_writes, which goes beyond the annotations that only indicate readOnlyHint=false. It gives context about the real-world impact and connection prerequisites, but does not detail failure modes or rate limits.

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, two sentences, and front-loaded with the critical 'ATO FISCAL REAL' label. Every word adds value 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?

The tool performs a real fiscal action, and while the description covers the main function and a key prerequisite, it lacks details about expected outcomes, return values, or error handling. With no output schema, it could benefit from more context on post-transmission behavior.

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 has 3 parameters with 0% coverage in the description. The description only mentions 'by id' implying the ids array, but does not explain the account or empresa_id parameters. With no schema descriptions, this is a significant 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 the tool transmits one or more CT-e to SEFAZ by id, using a specific verb and resource. It distinguishes from sibling tools like cancelar, averbar, etc., by specifying the action and the prerequisite that documents must already exist.

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 states it operates on already created/drafted documents, giving a clear when-to-use condition, and mentions the require of enable write permission. It doesn't explicitly contrast with alternatives, but the sibling context makes the intended usage clear.

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 flag destructiveHint=true, but the description adds valuable behavioral context: the operation is irreversible and requires the 'allow_writes' flag. This goes beyond the structured data by clarifying permission prerequisites and non-reversibility.

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 extremely concise, using a single sentence to state the action, scope, irreversibility, and permission requirement. Every word adds value with no 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?

For a simple delete operation, the description covers the essential context (irreversibility, permission). However, it omits details about response behavior, error conditions, or whether it's a hard delete, which would be useful but not critical given the tool's straightforward nature.

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% and the description offers no parameter explanations. While parameter names like 'ids' and 'account' are self-explanatory, the description fails to compensate for the lack of schema descriptions, even though the 'por id' phrase hints at 'ids' usage.

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 ('Exclui' - deletes) and the resource (CT-e), specifying they are drafts/rejected ones selected by ID. This distinguishes it from sibling operations like cancellation, making the 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 clear usage context by specifying the tool applies to drafts/rejected CT-e and warns it is irreversible, requiring the 'allow_writes' permission. While it doesn't explicitly compare to siblings like 'hivecloud_cte_cancelar', the scope is well-defined.

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 and destructiveHint=false, and the description reinforces this with 'não altera o documento'. It adds valuable behavioral context beyond annotations: output is a zip containing XML, and the download URL is temporary. No mention of authentication or file expiration details, but for a read-only export this is sufficient.

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, front-loaded with the action and outcome, and every sentence adds value. The analogy to the button and the safety note are both useful without 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 read-only export, the description covers the main behavior and return value (temporary download URL). However, with three parameters and no output schema, it leaves the account and empresa_id parameters unexplained, so the context is only partially 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?

Schema description coverage is 0%, and the description does not explain the parameters. It only hints that the tool handles 'um ou mais CT-e', which partially clarifies that the 'ids' array contains CT-e identifiers, but it does not mention 'account' or 'empresa_id' or how they should be used.

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 ('Exporta'), the resource ('XML de um ou mais CT-e'), and the output (zip and temporary download URL). It also distinguishes itself from siblings like hivecloud_mdfe_xml (MDF-e) and hivecloud_cte_dacte (DACTE PDF) by specifying CT-e XML and download link.

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?

Usage is implied: one should use this tool when needing the raw XML of CT-e documents. It provides a concrete analogy ('Mesma ação do botão Exportar XML do emissor') but does not explicitly state exclusions or alternatives such as hivecloud_get_cte or hivecloud_list_ctes.

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 safe-read behavior is known. The description adds the bulk execution trait and clarifies the single-item scope via 'específico pelo id,' which is useful context. However, it does not disclose batch limits, response format, or error modes, making the added transparency moderate but not rich.

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 the purpose front-loaded and the bulk support note immediately after. Every sentence provides distinct information, and there is no redundant or filler content. It is appropriately concise for a simple retrieval tool.

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, idempotent nature and no output schema, the description is minimally viable but omits important context. It does not explain what 'detalha' includes, how batches are returned, or what the 'account' and 'empresa_id' parameters are for. The bulk feature and 5-parameter complexity warrant more detail than this short description provides.

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 has 0% description coverage, so the description must compensate. It mentions 'id', 'ids', and 'empresa_ids' but omits 'account' and 'empresa_id' entirely, and does not clarify parameter relationships or precedence (e.g., whether id and ids are mutually exclusive). For a 5-parameter tool with no other documentation, this partial explanation is insufficient.

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: 'Detalha um CT-e específico pelo id' (details a specific CT-e by id), providing a specific verb, resource, and scope. It distinguishes from list tools (hivecloud_list_ctes) and mutating tools (hivecloud_cte_emitir, cancelar) by indicating a read/detail operation. However, it does not explicitly differentiate from hivecloud_cte_xml, which also retrieves a CT-e, and no alternative tools are named.

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 only usage guidance is the bulk support line: 'accepts ids, empresa_ids for batched execution.' This indicates when to use the array parameters, but there is no explicit statement about when to use this tool versus alternativas like hivecloud_list_ctes or hivecloud_cte_xml, nor any exclusions or preconditions. The context is implied rather than 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?

Annotations already cover read-only and idempotent behavior, and the description adds value by clarifying the returned fields (e.g., vehicle data, drivers) and the tenancy requirement. It also notes bulk execution capability. This goes beyond the annotations, providing useful behavioral context 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 exceptionally concise: two sentences in the first paragraph and one in the second. Every sentence serves a purpose: the first list fields and differentiates from listing, the second covers the prerequisite and bulk support. No fluff, front-loaded, and well organized.

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 get-by-id tool, the description provides a complete picture: it lists the output fields, notes the prerequisite, and explains bulk behavior. Combined with annotations that establish safety, this is sufficient. Without an output schema, listing the fields is helpful, though it could also mention response format, but it's not critical 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?

With 0% schema description coverage, the description must explain all parameters. It does clarify 'id' as the main identifier and mentions 'ids' and 'empresa_ids' for bulk, but it does not explain 'account' or 'empresa_id' at all. This partial explanation leaves ambiguity for some parameters, so it is only minimally adequate.

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 explicitly states the tool details an MDF-e by id and enumerates the exact fields returned, such as vehicle plate, drivers, CIOT, linked documents, UFs, value/weight, and status. It distinguishes itself from the listing tool by noting that the listing does not contain these detailed fields, and it mentions bulk support, making its purpose 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 usage context by noting that listing lacks the detailed fields, so this tool is for when you need that detail. It also states a prerequisite (mdfe_tenant_id in the connection) and explains bulk support. However, it does not explicitly name alternative tools like hivecloud_list_mdfes, though the implication is clear enough.

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, covering safety traits. The description adds the behavioral detail that accounts are composed of user+environment and are specific to this installation, which provides context 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?

One concise sentence delivers the purpose and a key definition, with no redundancy or filler. It is front-loaded and easy to parse.

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 with rich annotations, but the description does not explain the optional 'account' parameter or describe the output format, and there is no output schema. The description is adequate for basic understanding but leaves the parameter semantics ambiguous.

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 has 0% coverage for the single optional 'account' parameter, and the description does not explain its purpose or expected values. The description only defines what an account is, but does not clarify how the parameter filters or influences the result, which is a gap for the agent.

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 lists HiveCloud accounts connected to the installation, with a specific definition of an account as user+environment. This distinguishes it from sibling tools that handle CTE, MDFE, NFe, etc., and clearly indicates the resource and action.

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 listing accounts but does not explicitly state when to use it versus alternatives, nor does it mention exclusions or prerequisites. There is no guidance on when another tool (like hivecloud_list_empresas) would be more 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile with a low bar. The description adds value by disclosing the return fields (número, série, UF inicial/final, valor do frete, remetente/destinatário, status, datas, status de averbação) and the bulk execution behavior. This is useful context beyond the annotations, especially with no output schema.

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 reasonably efficient (~50 words), front-loads the core purpose and return values, then appends the bulk note. The minor structural issue is the language mixing (Portuguese main body with English bulk sentence), which could cause slight processing inconsistency, but it's not overly verbose.

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 7-parameter tool with no output schema and 0% schema coverage, the description covers return values (compensating for missing output schema), main behavior, and bulk mode. However, it leaves gaps around parameter semantics (account/empresa_id roles, date formats), pagination defaults, and any filtering caveats. It's adequate for selecting the tool but insufficient for fully 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 0%, so the description must compensate. It partially does: 'filtro por data de emissão' implies data_inicial/data_final as a date range, 'paginado' implies pageNumber/pageSize, and 'Bulk support: accepts empresa_ids' clarifies that param. However, 'account' and 'empresa_id' are unexplained, their relationship to 'empresa_ids' is unclear, and no date format or pagination defaults are specified.

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 ('Lista os CT-e') and resource (Conhecimento de Transporte eletrônico), and specifies scope (da empresa, paginado, com filtro por data de emissão). This clearly distinguishes it from siblings like hivecloud_get_cte (singular fetch), hivecloud_list_mdfes, and hivecloud_list_dces, which target different document types or granularity.

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?

Usage context is implied: it's a paginated list operation with date filtering, and the bulk support note ('accepts empresa_ids for batched execution') gives some guidance. However, there is no explicit when/when-not guidance contrasting with alternatives (e.g., when to use get_cte for a single document vs this list tool), and no mention of default pagination values or authentication 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?

Annotations already declare read-only, idempotent, non-destructive behavior, and the description adds pagination and bulk execution context. However, it does not disclose return-shape expectations, pagination defaults, or how parameters like account and empresa_id influence results.

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, front-loaded, and immediately identifies the resource and behavior. The bulk-support notice is useful and concise, with minimal 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 read-only list tool, the description is minimally viable, but the lack of output schema increases the burden on the description. It provides no details on response format, default pagination, or the relationship between singular and plural empresa parameters, so the agent is left guessing at meaningful behavior.

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%, and the description only compensates for two of the five parameters: empresa_ids (batch support) and pagination via 'paginated'. The meaning of account, single empresa_id, pageNumber, and pageSize are left unstated, and relationships/requirements among the parameters are unclear.

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 ('Lista') and the resource (DC-e / Declaração de Conteúdo Eletrônica), with company scoping and pagination noted. This distinguishes it from sibling tools such as hivecloud_list_ctes and hivecloud_list_mdfes.

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: use this tool to list DC-e records from the company, with pagination and bulk execution via empresa_ids. No explicit guidance is given about when to prefer this over alternatives or which parameter combination to use.

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 and idempotentHint=true. The description adds value by specifying the return fields (id, nome, cnpj) and its role in the workflow, 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?

Two concise sentences, front-loaded with the action and key information, zero 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?

For a simple list operation with no output schema, the description covers the essential purpose, return fields, and integration with other tools. However, it omits any explanation of the 'account' parameter, which would have made it 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 only parameter 'account' is optional and completely undocumented. With 0% schema description coverage, the description was expected to explain it but does not, leaving the agent uncertain about its 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 clearly states it lists issuing companies with id, name, and cnpj, and explicitly connects the id to the empresa_id used in other tools. This is specific and distinguishes it from sibling tools like hivecloud_mdfe_empresas.

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?

Clearly indicates the tool is a prerequisite for other tools ('passo de seleção da empresa'), which implies when to use it. However, it doesn't explicitly state when not to use it or mention alternatives, but the purpose is clear enough.

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, destructiveHint=false, which covers safety. The description adds that it is paginated and supports bulk execution via empresa_ids, which is useful behavioral context beyond the schema. However, it does not describe return format, filtering, or other behavioral traits like ordering or default page size.

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 main purpose. The bulk support note is concise and adds value. No wasted words, though it could be slightly more structured with parameter clarification.

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 there is no output schema and five parameters with no description coverage, the description is incomplete. It doesn't explain the pagination parameters (pageSize, pageNumber) or the account parameter. It also doesn't clarify the difference between empresa_id and empresa_ids, or provide any guidance on how these are used. For a list operation with bulk support, more context is needed.

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%, meaning the description provides no parameter details. The description mentions 'empresa_ids' for bulk support, which adds some meaning, but other parameters (account, pageSize, empresa_id, pageNumber) are left undocumented in the description, and the schema only provides types, not semantic meaning. The description should have compensated for the low coverage but only partially does.

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 verb ('Lista') and the resource ('inutilizações de numeração de CT-e da empresa'), and mentions pagination. It distinguishes itself from siblings by specifying the CT-e domain, though it doesn't explicitly differentiate from other list tools like hivecloud_list_ctes or hivecloud_list_dces, but the specific resource name is 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 does not provide guidance on when to use this tool versus alternatives. It only mentions pagination and bulk support, but no context about typical use cases or when not to use it. No alternatives are mentioned.

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 indicate read-only, idempotent, non-destructive, which the description reinforces by stating it lists (read operation). The description adds behavioral details: pagination, listing of specific fields, and tenant id requirement on the connection, which go beyond the annotations. No contradiction is present.

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 extremely concise, containing only two sentences. The first sentence states the main purpose and output fields; the second adds a critical prerequisite and bulk capability. No extraneous information or filler. Every sentence is purposeful, achieving high clarity without verbosity.

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?

Despite simple annotations, the tool has 7 parameters with no schema coverage and no output schema. The description does not provide enough information for the agent to understand all input semantics (e.g., pageSize, data_inicial, data_final), the pagination mechanics, or the shape of the response. It lists some output fields but not how to control pagination or filter by dates/company. This is inadequate for operational use.

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 explain all 7 parameters. It only mentions `empresa_ids` for bulk support and implies pagination (pageSize, pageNumber, data_inicio/fim) but does not describe each parameter's meaning, format, or purpose. This critical gap severely reduces an agent's ability to correctly invoke the 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 it lists MDF-e (Manifesto Eletrônico de Documentos Fiscais) of the company with pagination, and specific fields (number, series, emission date, status, loading/unloading UF, CIOT). It distinguishes itself from sibling tools like hivecloud_list_ctes or hivecloud_list_dces by explicitly naming MDF-e. The verb 'List' and resource 'MDF-e' are specific and 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?

It provides essential context: requires mdfe_tenant_id on the connection, which is distinct from CT-e, and accepts empresa_ids for batched execution. However, it does not explicitly say 'use this instead of X' or mention when not to use it. The context implies usage only for MDF-e, but excludes mention of alternatives beyond noting the distinct tenant requirement.

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?

Além das annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false), a descrição adiciona comportamento relevante: paginação, exigência de tenant e execução em lote. Não há contradição com annotations. Faltam detalhes sobre formato de resposta ou limites, mas o contexto adicional é valioso.

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?

Duas frases curtas, sem redundância, com a informação essencial na primeira frase e o detalhe de bulk na segunda. Front-loaded e eficiente.

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?

Para uma listagem simples com annotations de segurança e 5 parâmetros opcionais, a descrição cobre propósito, paginação, autenticação e bulk. Faltam especificações como default de paginação e semântica precisa de account/empresa_id, mas é suficiente para invocação básica.

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?

O schema tem 0% de descrições e a descrição compensa parcialmente: explica empresa_ids (lote) e implica pageSize/pageNumber via 'paginado'. Porém, parâmetros como account e empresa_id não são esclarecidos, deixando ambiguidade sobre o papel de cada um.

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?

A descrição especifica a ação (Lista), o recurso (motoristas/condutores cadastrados), os campos retornados (nome, cpf, cnh) e o contexto (usados no MDF-e, paginado). Isso distingue claramente o tool de irmãos como hivecloud_list_veiculos e hivecloud_list_mdfes.

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?

A descrição informa o requisito de mdfe_tenant_id na conexão e menciona suporte a bulk via empresa_ids, o que dá contexto de uso. Porém, não explicita quando usar esta ferramenta em vez de alternativas (ex.: list_veiculos, list_empresas) nem fornece exclusões ou cenários de não-uso.

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. The description adds useful behavioral context beyond that: pagination, the mdfe_tenant_id connection requirement, and bulk execution via empresa_ids. No contradiction exists.

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 paragraphs with the core purpose and output fields front-loaded. Every sentence adds value: pagination, tenant requirement, and bulk support. There is 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?

For a simple list tool, the description covers the resource, key returned fields, pagination, the connection requirement, and bulk support. Since there is no output schema, it does briefly indicate return contents, though it omits pagination response details, defaults, or limits. Overall it is adequate for tool selection and 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 has 0% property descriptions, so the description must compensate. It adds pagination semantics (pageSize/pageNumber) and explains that empresa_ids enables batch execution. However, it does not clarify account, empresa_id, or how singular and plural empresa parameters relate, leaving some parameter 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 opens with a specific verb ('Lista') and clearly identifies the resource: registered vehicles ('veículos cadastrados') used in MDF-e, including key fields (placa, motorista, reboque, tara). This clearly distinguishes it from sibling list tools like hivecloud_list_motoristas or hivecloud_list_empresas.

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 states the tool is for listing vehicles used in MDF-e, that it is paginated, and that it requires mdfe_tenant_id on the connection. It does not explicitly list alternatives or exclusions, but the context is sufficient for choosing this tool among the sibling list tools.

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 indicate destructiveHint=true and readOnlyHint=false, so the description reinforces that. It adds value by stating 'Irreversível' and 'ATO FISCAL REAL', making the consequence explicit. 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 two sentences with zero filler. It's front-loaded with the action and immediately conveys critical constraints.

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 complexity (irreversible fiscal action), the description covers essential aspects: what it does, irreversibility, and prerequisites. It lacks detail on return values or error handling, but since there's no output schema and the action is straightforward, this is acceptable.

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 with only 3 parameters where only 'ids' is required, the description explicitly mentions that 'ids' is used to select MDF-e(s). It clarifies that 'account' and 'empresa_id' are likely context identifiers, though not detailed. The description adds meaning about the primary 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 clearly states the tool's purpose: cancels one or more MDF-e (by id) with SEFAZ. The verb 'cancela' is specific, the resource (MDF-e) is named, and it distinguishes from siblings like emitir, encerrar, excluir.

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 gives clear context: it's an irreversible fiscal act, requires allow_writes and mdfe_tenant_id, and targets MDF-e. However, it doesn't explicitly contrast with alternative tools like hivecloud_mdfe_encerrar or hivecloud_mdfe_excluir beyond listing the purpose.

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. The description adds meaningful context beyond those annotations: the PDF link is temporary, the action matches the print button, and the document is not altered. It also calls out the mdfe_tenant_id connection requirement.

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 short sentences with no filler. The main action is front-loaded, and the temporary-URL behavior, non-mutating nature, and connection requirement each earn their 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?

The tool is relatively simple and the description covers core purpose, return value, and a key prerequisite. However, with no output schema and two unexplained optional parameters, the overall context is not fully complete for an agent deciding how to invoke it.

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 for all parameter meaning. It clarifies that ids refer to one or more MDF-e, but it does not explain the optional account and empresa_id parameters at all. This leaves agent invocation uncertain for the optional fields.

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: it generates the DAMDFE PDF for one or more MDF-e and returns a temporary download URL. It also clarifies the tool is equivalent to the issuer's print button, which helps distinguish it from siblings like mdfe_xml, mdfe_cancelar, and mdfe_emitir.

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 gives useful context: use this when you need the printed DAMDFE PDF, it does not change the document, and it requires mdfe_tenant_id in the connection. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a full 5.

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 indicate a write operation (readOnlyHint=false) and non-idempotent behavior. The description adds 'ATO FISCAL REAL' to convey the legal gravity and mentions required permissions, providing context beyond the annotations. However, it does not detail potential side effects or what happens after transmission, so it stops short of 5.

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 information ('ATO FISCAL REAL') and clearly states the action and requirements. Every word earns its place, with no fluff or repetition of 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?

Given that this is a fiscal transmission (write operation, non-idempotent, no output schema), the description is quite brief. It covers the action and prerequisites but omits any mention of return values, error behavior, or post-transmission status. Annotations help, but for a tool with real fiscal consequences, more context would be expected.

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 only clarifies the 'ids' parameter via 'por id', but leaves 'account' and 'empresa_id' unexplained. For a tool with three parameters, this is insufficient, as the agent must infer the meaning of these fields from context or external knowledge.

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 function: transmitting one or more MDF-e to SEFAZ by id. It uses a specific verb ('transmite') and resource ('MDF-e'), and the addition of 'ATO FISCAL REAL' emphasizes the real fiscal nature. This distinguishes it from sibling tools like hivecloud_mdfe_cancelar or hivecloud_mdfe_encerrar.

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 use: it is for sending MDF-e to SEFAZ and explicitly states prerequisites ('allow_writes + mdfe_tenant_id'). While it does not name alternative tools or explicitly say 'use when...', the purpose and requirements imply when it should be used, which is sufficient for a 4.

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, so the safety profile is covered. The description adds valuable behavioral context beyond annotations by noting the connection requirement (mdfe_tenant_id) and the MDF-e-specific isolation from CT-e data.

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 core purpose. Every sentence adds value: purpose, distinction from CT-e, result id semantics, and connection requirement. 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 simple list tool with one optional parameter, the description explains purpose, result id, and connection requirement, but leaves the 'account' parameter unexplained. Since there is no output schema, a bit more detail about the optional parameter would make it 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 input schema has one optional string parameter, 'account', but schema description coverage is 0% and the description does not explain this parameter at all. The mention of 'id' refers to the returned company identifier, not the input parameter, so the description fails to add any meaning to 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 uses a specific verb ('Lista') and clearly identifies the resource ('empresas emitentes do ambiente de MDF-e'). It also distinguishes this from CT-e companies by explicitly noting MDF-e has its own environment and companies, which separates it from sibling tools like hivecloud_list_empresas.

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: this tool is for MDF-e companies, not CT-e companies, and requires mdfe_tenant_id in the connection. It does not explicitly name an alternative tool for CT-e companies, but the exclusion is stated clearly enough.

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 are minimal (readOnlyHint=false, no other hints). The description adds 'ATO FISCAL REAL' implying legal/fiscal significance and requires 'allow_writes' which hints at authorization. It does not, however, disclose side effects (e.g., irreversibility, impact on subsequent operations). Given the lack of annotations, the description carries some burden but provides only partial transparency.

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 exceptionally concise: one line, two sentences at most. The key information (action, target, timing, and requirement) is delivered upfront without repetition or fluff. Every word adds value, and the 'ATO FISCAL REAL' prefix immediately signals importance.

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 lack of an output schema and sparse annotations, this tool description leaves significant gaps. It does not explain the effect of closing an MDF-e, whether it is reversible, what responses to expect, or how the parameters interact. For a write operation with legal implications, more context is needed (e.g., confirmation, error handling, consequences). The description is too brief for a tool with these characteristics.

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 has three parameters: ids, account, empresa_id, but the description only mentions 'por id' which maps to 'ids'. It does not clarify the purpose or format of 'account' or 'empresa_id', and schema coverage is 0%. The description adds minimal value beyond what the schema already shows, and for an unannotated schema, it should explain the parameters more thoroughly.

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: 'encerra um ou mais MDF-e (por id) após o fim da viagem' (closes one or more MDF-e by id after the trip ends). The verb is specific ('encerra') and the resource is clear (MDF-e). It also emphasizes 'ATO FISCAL REAL' which sets it apart from mere utility. While it doesn't explicitly contrast with siblings like 'cancelar' or 'emitir', the phrase 'após o fim da viagem' provides a distinct context, making it distinguishable.

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 gives explicit context: 'após o fim da viagem' (after the end of the trip) indicates when to use it. It also states a prerequisite: 'Exige allow_writes + mdfe_tenant_id', which is essential for invocation. However, it does not mention when not to use it or suggest alternatives, so it falls short of a 5.

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 and destructiveHint=false, and the description reinforces 'Não altera o documento'. It adds useful behavioral context beyond annotations: the download URL is temporary, and the connection requires mdfe_tenant_id. 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 two sentences, front-loaded with the main action and result, followed by two important caveats. Every word earns its place; no fluff or verbosity.

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 explains the main return value (temporary URL) and safety characteristics, which is adequate for a simple read tool. However, it omits details about optional parameters (account, empresa_id) and does not specify the URL's lifetime or zip structure. With no output schema, there are some completeness gaps.

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 implies 'ids' are MDF-e IDs via 'um ou mais MDF-e', but it does not explain 'account' or 'empresa_id', nor the exact format or constraints of 'ids'. With zero schema-level descriptions, this is a significant 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 the tool exports XML of one or more MDF-e as a zip and returns a temporary download URL. This specific verb+resource+result distinguishes it from sibling tools such as hivecloud_mdfe_damdfe (PDF) and hivecloud_cte_xml (CT-e).

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 this tool: to obtain XML download URLs without altering the document. It also notes a prerequisite (mdfe_tenant_id in the connection), but does not explicitly name alternatives or say when not to use it. This is clear context without 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?

Annotations already mark the operation read-only and idempotent. The description adds meaningful behavioral context by warning that the query counts against the NF-e query quota and by disclosing bulk execution via empresa_ids. 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 compact and front-loaded: it states the operation, lists returned data, gives usage context, notes quota impact, and mentions bulk support in a few sentences. 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?

For a read-only lookup with annotations, the description covers purpose, key input, returned fields, prerequisite context, quota, and bulk behavior. The main gap is incomplete parameter semantics for account and empresa_id, but overall it is sufficiently complete for selection and 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 description explains the key chave parameter (44-digit access key) and clarifies that empresa_ids enables batched execution, which the schema does not convey. However, account and empresa_id are left unexplained, and with 0% schema description coverage the description should compensate more fully.

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 consults NF-e data by 44-digit access key and enumerates the returned fields (sender, recipient, load value, weights, volumes, predominant product). It also positions the tool as the step before CT-e creation, distinguishing it from CT-e-related 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?

The phrase 'É o passo antes de criar o CT-e' gives clear contextual guidance on when to use this lookup. It does not explicitly name alternatives or when-not-to-use conditions, so it stops short of a 5.

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 valuable behavioral context beyond the annotations: it mentions that the tool consolidates multiple companies in one call, resolves everything server-side, excludes canceled trips by default, and requires mdfe_tenant_id in the connection. The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which align with the description's read-only nature. No contradiction found.

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, dense paragraph that packs a lot of information efficiently. It front-loads the core purpose and then adds details on filters, consolidation, and server-side processing. While it is somewhat long, every sentence adds value and there is no 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?

Given the tool's complexity (8 parameters, no output schema, no parameter descriptions), the description covers the essential aspects: what the report contains, how filters work, the multi-company consolidation, the optional billing, and the exclusion of canceled trips. It could be more complete by explaining the date format and the account parameter, but it is largely sufficient for an agent to use 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?

The schema has 0% description coverage, so the description must compensate. It explains the purpose of key parameters: placa and motorista as filters, empresa_ids for consolidating multiple companies (omitted = all), incluir_cancelados and incluir_faturamento as optional flags. However, it does not explain the format of data_inicial/data_final or the account parameter, which are left to the schema's basic type definitions.

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: it generates a consolidated travel report (MDF-e) by period, with counts by month, rankings by plate and driver, and optional billing totals. It distinguishes itself from sibling tools like hivecloud_list_mdfes and hivecloud_get_mdfe by specifying the consolidated, analytical nature of the report.

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 on when to use the tool (for consolidated reports and answering questions like 'how many loads did plate X do in the quarter and how much did it bill'), and mentions that canceled trips are excluded by default. However, it does not explicitly state when not to use it or name alternative tools for simpler queries.

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, covering safety. The description adds the bulk support feature (accepting 'empresa_ids') and restates the operational purpose. It does not describe return format or edge cases, but adds meaningful context about batched execution 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 highly concise: two sentences with no fluff. The first sentence clearly states the purpose, and the second adds the bulk support detail. Every word contributes value, and the structure is 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?

The tool is simple, and annotations cover safety. The description explains the purpose and bulk capability, but does not document the parameters (account, empresa_id) or the expected output format, especially given there is no output schema. For a read-only status check, the description is adequate but incomplete—missing parameter explanations and response 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 0%, and the description only mentions 'empresa_ids' for bulk execution. It does not explain the 'account' or 'empresa_id' parameters, leaving most of the schema meaning unexplained. The description adds minimal value over the bare schema, failing to compensate for the low 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 clearly states that this tool checks the status of the SEFAZ service for a company (whether the Treasury server is in operation). It uses a specific verb ('status') and resource ('SEFAZ service'), and is completely distinct from sibling tools that perform actions like emit, cancel, or list documents.

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 for checking service status but does not explicitly state when to use it (e.g., before issuing a document) or when not to use it. It does not mention alternatives or exclusions, though no sibling tool serves the same purpose. The guidance is implicit rather than 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?

The description goes well beyond the annotations. It discloses that invoke runs one-off without installing, requires a connect link for credentials, returns a checkout link for insufficient wallet balance, and that writes require owner/admin. It also explains installed_in_toolkit vs workspace flags. This adds significant behavioral context beyond the sparse annotations (readOnlyHint false, destructiveHint false), enriching the agent's understanding of side effects and prerequisites.

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 dense paragraph but well-organized: starts with overarching purpose, walks through the core flow, contrasts invoke vs install, then quickly covers remaining actions and the prompt library. It's information-dense with no fluff, but the wall-of-text format could be improved with bullet points or section breaks for readability. Still, it's fairly concise given the breadth of functionality.

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 23 parameters, no output schema, and no schema descriptions, the description covers the primary workflows (search, describe, invoke, install), the one-off vs permanent distinction, auth/payment handling, and the prompt library. It does not explain every action (e.g., resume, list_tools details) but provides enough to use the tool effectively. It's a very good, near-complete overview for a complex umbrella 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?

With 0% schema description coverage and 23 parameters, the description carries the full burden. It explains the core action parameter (action enum with meanings), and key parameters like mcp_id, tool_id, arguments, prompt_slug, prompt_vars, and the flow connecting them. It does not detail every parameter (e.g., cancel_reason, prompt_targets), but given the tool's complexity, the description covers the critical ones and gives a mental model for the rest. This is strong but not exhaustive, earning a 4.

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 identifies the tool as the official mcp.ai marketplace, the catalog of every MCP/tool and the way to run them. It names specific actions (search, describe, invoke, install) and distinguishes itself from sibling tools (which are individual hivecloud tools) by being the umbrella gateway. The purpose is unambiguous and distinct.

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?

Provides explicit guidance on when to use each action: search to discover, describe to get profiles, invoke for one-off runs (even without installation), install only for permanence. It explicitly contrasts invoke vs install and lists alternatives for different intents (subscribe/cancel, report_bug, request_mcp). Clear when-to-use and when-not guidance is present.

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 useful behavioral context by telling the agent to include the recent conversation for reproduction. Annotations already indicate idempotent and non-destructive behavior, and the description does not contradict them, but it does not explain the result of submitting the report or what side effects occur beyond sending feedback.

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?

Both sentences earn their place: one states the core purpose, and the other gives the single critical reproduction instruction. There is no fluff or redundant restatement of the tool name.

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 is generally adequate for a simple side-effect tool with annotations, but it leaves parameter-format ambiguity unresolved and does not explain what happens after reporting. Given the minimal schema and no output schema, a bit more detail would make this 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?

With 0% schema description coverage, the description carries the burden of explaining parameters. It clarifies that 'conversation' should contain recent messages, but it does not explain the required 'message' field or the 'context' field, and it calls conversation an 'array' while the schema types it as a 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's purpose with specific verbs: 'Report a bug, missing feature, or send feedback.' It is distinct from the sibling tools, which focus on CTE/MDFE operations, authentication, and system information.

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 gives clear intended contexts: bug reports, missing features, and general feedback. It does not explicitly list when not to use it, but the naming and wording make the appropriate situations obvious relative to the unrelated sibling tools.

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 and idempotentHint=true, covering safety. The description adds the specific types of versions (platform and adapter) but does not disclose any additional behavior like error conditions or output format. This is acceptable for a simple query 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, concise sentence that conveys exactly what the tool does with no unnecessary words.

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 no-parameter, read-only version tool, the description fully specifies its behavior. No output schema is needed, and the provided annotations and description cover all necessary information.

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 trivially complete. The description adds no parameter details because none exist. Baseline 4 applies for zero-parameter tools.

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 shows the current MCP platform and adapter versions, using a specific verb and resource. It is distinct from sibling tools, which are primarily action-oriented or domain-specific, making the 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?

No explicit when-to-use guidance is given, but the purpose is trivial: it is the tool for checking versions. No alternatives or exclusions are mentioned, so it relies on user inference.

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 context on the return contents (installed MCPs, status, accounts, catalog tool counts) beyond the readOnlyHint and idempotentHint annotations. It clarifies this is a read-only state report, which aligns with annotations and provides behavioral clarity 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 a single, front-loaded sentence that efficiently enumerates the key information: what it returns and its scope. No verbose or redundant phrases, and it directly states the tool's purpose and contents.

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 no parameters and a straightforward state-reporting purpose, the description covers the essential return contents. The presence of sibling tools like 'show_version' adds context, but the description sufficiently clarifies its role. It could mention that it returns connection status details, but overall it's complete for a low-complexity 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?

The tool has zero parametersause the schema is empty, making parameter semantics trivial. The baseline of 4 is appropriate as there is no parameter burden, and the description focuses on the output rather than inputs.

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 returns the current toolkit state, listing specific items like installed MCPs, connection status, accounts, and catalog tool counts. This distinguishes it from siblings like 'show_version' and 'hivecloud_sefaz_status', though it doesn't explicitly highlight its status-reporting role versus other info 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 implies this is for checking overall state, which is appropriate for a no-parameter info tool. It does not explicitly state when to use it versus alternatives like 'hivecloud_list_accounts' or 'hivecloud_nfe_info', but the context of a toolkit overview gives reasonable guidance.

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