F360 Finanças

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

The description adds useful behavior beyond the annotations: config header yields a permanent connection, while passing a token yields a session-only login, and no args returns a link. It does not fully spell out side effects or success/failure return values, but annotations already cover idempotency and non-destructiveness.

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 dense and front-loaded, with no fluff, but the long single sentence with parenthetical clauses and multiple alternatives could be structured into clearer separate instructions. Still, every part adds necessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter auth tool with no output schema, it covers the no-arg return (the link), the token-paste path, and the persistent-config alternative. It doesn't state the response on a token success/failure, but the invocation guidance is sufficient for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description carries the full burden for the optional `token` parameter. It explains that token is a JWT/access token pasted by the user and how to pass it, compensating well for the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as MCP.AI authentication for IDE agents, with a concrete browser-login + access-token flow and two invocation paths (no args for a link, token for login). This specific verb+resource is unambiguous and easily distinguished from the unrelated calculo_* sibling 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?

It explicitly differentiates the persistent config-header approach ('best... permanent, non-expiring') from the session-only paste/login path, and states exactly when to call with no args versus with { token }. This gives the agent clear selection criteria for both setup and invocation.

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

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

Annotations already establish this is read-only, idempotent, and non-destructive. The description adds useful behavioral detail beyond that by specifying the two main response states: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing. This helps an agent predict what to expect.

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-loads the core purpose, and then adds only the essential conditional details. Every sentence contributes meaningful information, and there is no waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only status tool with no output schema, the description is complete enough. It tells the agent what information will be returned, what the success condition looks like, and what happens when credentials are missing. The low complexity means no additional guidance is required.

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 description does not need to explain any input semantics. The baseline of 4 applies because there is no parameter burden at all.

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: returning connection status and URLs. It distinguishes connect from its sibling authenticate by framing it as a status/read operation rather than an action, and the conditional output descriptions reinforce this.

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 makes clear that this is the tool to call when checking connection state or getting URLs. It does not explicitly mention alternatives like authenticate, but the context strongly implies connect is for status checking rather than initiating authentication, so usage is clear without being fully 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 indicate read-only, idempotent, non-destructive. Description adds bulk execution capability, enhancing transparency 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?

Two concise sentences that directly convey purpose and bulk support without extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers core functionality and bulk use, but missing explanation for 'account' parameter and return value details. Adequate for a simple tool but not fully 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 has 0% description coverage. Description explains 'id' and mentions 'ids' for bulk, but does not cover 'account' parameter, leaving it undocumented.

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?

Clearly states that the tool downloads the result of an already generated report using the id from f360_relatorio_* tools. Distinguishes from others like f360_obter_danfe and f360_obter_xml.

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?

Explicitly instructs to use the id from f360_relatorio_* tools, providing clear context for when to invoke this tool. Lacks explicit exclusions or alternatives but is effective.

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, so the description adds value by specifying the returned fields (id, label) and the scope ('conectadas a este install'). No contradictions 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 a single, front-loaded sentence with no wasted words. It efficiently conveys the core purpose and output fields.

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 rich annotations, the description covers the basic purpose. However, it lacks explanation of the optional 'account' parameter (e.g., whether it filters or specifies a specific account), and there is no output schema to detail return structure. Given siblings are similar, a bit more context would help.

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 parameter 'account' with 0% description coverage. The description does not mention the parameter or explain its purpose. Since schema coverage is low, the description should compensate, but it does not add meaning beyond the parameter name.

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 accounts/companies connected to this install and returns id and label. It uses a specific verb ('lista') and resource ('contas/empresas'), distinguishing it from sibling list tools for other entities.

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 (listing connected F360 accounts) but provides no explicit guidance on when to use it vs. alternatives or any prerequisites. The purpose is clear, but no exclusions or trade-offs 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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which fully disclose the tool's non-destructive, read-only nature. The description adds no behavioral context beyond what the annotations provide, such as output format or pagination behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (one short sentence) but at the expense of informativeness. It merely restates the tool name, wasting an opportunity to provide useful guidance.

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 is a list operation with one optional parameter and no output schema, the description should explain what product classifications are, what the account parameter does, and what the output looks like. It provides none of this, making it inadequate for confident agent 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 single optional parameter 'account' is undocumented in both the description and the input schema (schema coverage 0%). The description fails to explain its purpose or expected format, forcing the agent to assume its meaning.

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 repeats the tool's name with a verb and resource ('lista as classificações de produtos'), but it offers no clarification on what 'classificações de produtos' means or how it differs from sibling list tools like f360_listar_pessoas or f360_listar_planos_contas. This makes the purpose vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent to guess.

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 complements annotations (readOnlyHint=true, destructiveHint=false) by stating that the tool is paginated via the 'pagina' parameter. It does not mention limits or default ordering, but adds useful behavioral 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?

The description is a single, well-structured sentence with a clear list of filters. It is front-loaded with the main action and contains 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?

The tool has 8 parameters and no output schema. The description covers all important filter parameters and pagination, which is adequate for a list tool. It lacks details on response format or prerequisites, but given the tool's simplicity, it is reasonably 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 coverage, the description adds significant meaning for most parameters: it specifies ISO format for date filters, provides examples for 'registro' and 'tipo', and explains comma separation for 'empresas'. However, the 'account' parameter is not mentioned in the description.

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 starts with 'Lista notas fiscais' (Lists tax invoices), clearly stating the verb and resource. It also mentions pagination and lists filters, which distinguishes it from sibling tools like f360_listar_pessoas.

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 explicitly state when to use this tool versus alternatives. It implies usage through the name and filter list but lacks guidance on when not to use it or what other tools might 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 indicate read-only and idempotent behavior. The description adds useful context about pagination and filtering, going beyond what annotations provide. No contradictions.

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 fully front-loaded with purpose and key details. No waste.

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 pagination and filtering but omits explanation for the 'account' parameter and does not describe the output format or return structure. Given no output schema, 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%. The description explains 'pagina' and 'definicao' (with valid values), but 'account' is not mentioned at all, leaving it ambiguous.

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 people (clients/suppliers) with pagination and filtering. It uses specific verbs and resources, but doesn't explicitly differentiate from sibling tools like 'f360_obter_pessoa' (which gets a single person).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains pagination and filtering options, implying when to use them, but provides no explicit guidance on when to use this tool versus alternatives or when not to use it.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds no behavioral details beyond what the annotations provide, such as side effects, authentication needs, or output format. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence but is too brief and uninformative. It does not earn its place because it adds no value beyond the tool name. True conciseness would include essential details without wasting 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?

With one optional parameter, no output schema, and no parameter descriptions, the description should at least explain the parameter's purpose and the structure of the listing. The current description is incomplete for an agent to use the tool effectively.

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 parameter 'account' with 0% description coverage, and the tool description does not mention or explain this parameter. The agent has no information about what 'account' means or how to use it, requiring guesswork.

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 'Lista os planos de contas (ListarPlanosContas)' essentially restates the tool name, providing no additional clarity on what the tool does beyond the name itself. It fails to distinguish the tool from siblings like 'f360_list_accounts' or 'f360_obter_plano_contas'.

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 offers no guidance on when to use this tool versus alternatives, nor does it specify any prerequisites or exclusions. The agent is left without context to decide whether to use this tool over similar listing/getting 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, so the description adds value by noting bulk support (accepts multiple IDs). However, it does not explain output format, size limits, or error scenarios, which would further enhance 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 extremely concise: two short sentences with no fluff. It front-loads the core purpose and then adds the bulk support detail. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (get DANFE by ID/batch) and the description covers the main action and bulk capability. However, it fails to mention what the tool returns (e.g., PDF, URL) or any authentication prerequisites, which is missing given 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?

With 0% schema description coverage, the description partially explains the 'ids' parameter for batched execution but does not clarify the 'id' parameter (likely the note ID) or the 'account' parameter. It adds minimal semantic value beyond the parameter names.

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 obtains the DANFE (a tax document) of a note by ID, with specific verb 'Obtém' and resource 'DANFE'. It also mentions bulk support via 'ids', distinguishing it from siblings like 'f360_obter_xml' which gets XML data.

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 retrieving DANFE documents and supports batched execution, but lacks explicit guidance on when to use it versus alternatives (e.g., f360_obter_xml for XML). No prerequisites or exclusions are stated.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that the tool supports batched execution via the 'ids' parameter, which is valuable behavioral context beyond the annotations. However, it does not disclose other traits like rate limits or output behavior.

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: two sentences. The first states the core purpose, and the second adds bulk support. No unnecessary words, well front-loaded.

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 3 parameters, no output schema, and low schema coverage, the description should provide more context (e.g., return format, details on 'account' parameter). It only covers the basics of fetching by ID and batch, leaving the agent underinformed.

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 explains 'id' implicitly and 'ids' as for batch, but the 'account' parameter is entirely unmentioned. The description adds minimal meaning beyond the schema's structural constraints.

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 action: 'Detalha uma pessoa por id' (details a person by ID) and highlights bulk support with 'ids'. This distinguishes it from sibling tools like f360_listar_pessoas, which lists people without a specific ID, and other obter_* tools for different entities.

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 when you have a person's ID(s) but provides no explicit guidance on when to use this tool versus alternatives. There is no mention of prerequisites, context, or when not to use it, leaving the agent without decision support.

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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that it supports batched execution (ids parameter), but does not disclose any other behaviors like permission requirements or response format. Since annotations cover most behavioral aspects, a 3 is appropriate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise—two sentences that front-load the main action and mention bulk support. 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?

With three parameters, no output schema, and a sibling list tool, the description should provide more context, such as return format, parameter interplay, or typical use cases. It falls short, leaving the agent potentially unable to infer correct usage.

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 'account' parameter at all. While 'id' and 'ids' are implied by the text, their meanings and relationship (e.g., whether ids overrides id) are unclear. The description adds minimal value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool details a chart of accounts by ID ('Detalha um plano de contas por id'), which matches the tool name. It distinguishes from the sibling list tool (f360_listar_planos_contas) by indicating this is a get/detail operation. However, it could be more explicit about what a 'plano de contas' is.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like f360_listar_planos_contas. It only mentions bulk support, but does not specify when batched execution is appropriate or needed.

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 tool is clearly a safe read operation. The description adds the detail that it performs 'ObterXML' (get XML) and supports batch, which is consistent but does not reveal additional constraints like authentication or data format. Given the annotation coverage, the description adds moderate value.

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 with no wasted words. The bulk support note is front-loaded. Every sentence earns its place, and the structure is optimal for quick parsing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and strong annotations, the description is adequate but not complete. It does not mention the return format (expected XML string) or any response structure. Since there is no output schema, the description could provide more context, making it a 3.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the burden. It explains 'id' (primary identifier) and 'ids' (for bulk), but does not mention the 'account' parameter. This partial explanation helps but leaves a gap. Baseline for 0% coverage is lower, but the description compensates somewhat.

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 retrieves XML of a note by ID, with bulk support. This distinguishes it from siblings like f360_obter_danfe (which likely gets DANFE PDF) and other unrelated tools. The purpose is specific and well-defined.

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 when XML of a note is needed, especially hinting at bulk execution via 'accepts ids for batched execution.' However, it does not explicitly state when not to use it or provide alternatives (e.g., f360_obter_danfe for PDFs). The guidance is present but incomplete.

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 annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds that the tool may return an ID and requires a subsequent download. It also explains its role in reconciliation. 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?

Two sentences convey the core purpose and usage flow efficiently. Some detail could be structured better, but it is front-loaded with key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters and no output schema, the description explains the purpose and a multi-step flow (generate then download). However, it omits parameter details, error handling, and response format, leaving gaps for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description only mentions 'por período' covering the required date parameters. It does not explain the optional parameters (account, cnpj_empresas, tipo_conciliacao) leaving significant gaps 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 it generates a card reconciliation report by period ('Gera o relatório de CONCILIAÇÃO DE CARTÕES ... por período'). It distinguishes from sibling report tools like f360_relatorio_contabil and f360_relatorio_transferencias. The verb 'gera' and resource are specific.

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 explains the tool is the basis of reconciliation and pairs with Bank MCP, providing context. It instructs to download the result using f360_baixar_relatorio. However, it does not explicitly state when not to use or alternatives.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true. Description adds that it returns an id and should be used with download sibling, but does not discuss potential side effects, rate limits, or error handling.

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, directly to the point, no unnecessary words. Front-loaded with 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?

Provides essential flow (generate then download) but lacks explanation of non-obvious parameters and return value details. For a 7-param tool, more context on filters is 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?

Only describes data_inicio and data_fim with format, leaving 5 other parameters (contas, account, cnpj_empresas, modelo_contabil, modelo_relatorio) unexplained. With low schema description coverage (0%), the description fails to compensate adequately.

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?

Description clearly states it generates accounting/management reports and specifies period via dates. It differentiates from the sibling f360_baixar_relatorio by noting the output is an id for download.

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 indirect guidance by mentioning that the report id can be downloaded with f360_baixar_relatorio, but no explicit when-to-use vs alternative report tools (e.g., f360_relatorio_conciliacao_cartoes).

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 and idempotent behavior. The description adds value by stating that the tool may return an id, implying an asynchronous or deferred download pattern. No contradictions 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 extremely concise with two sentences. The first sentence immediately states the purpose and scope, and the second covers the return behavior and next steps. 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?

Given the tool has 4 parameters, no output schema, and moderate complexity, the description covers the core function and return behavior. However, it lacks details on parameter formats, required vs optional fields, and the structure of the report. Additional context would be needed for robust 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?

With 0% schema description coverage, the description should explain all parameters. It only briefly implies that data_inicio and data_fim define the period, but does not clarify account or cnpj_empresas. Two of four parameters are left completely unexplained.

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 generates a report of transfers between accounts by period, using a specific verb and resource. It also distinguishes from the sibling tool f360_baixar_relatorio by mentioning the return of an id.

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 partial guidance by noting that an id can be returned and should be used with f360_baixar_relatorio. However, it does not differentiate this tool from other report generation tools (e.g., f360_relatorio_conciliacao_cartoes), leaving the agent to infer when to use this specific one.

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 discloses important behaviors: invoke runs an MCP even when it is not installed, does a one-off run without adding the MCP to the toolkit, returns a connect link when credentials are needed, returns a checkout/top-up link when payment is needed, and requires workspace owner/admin for write operations. The description enriches the 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 front-loaded with identity and the core flow, and nearly every sentence carries useful guidance. However, it is one dense, wall-of-text paragraph with mixed language ("pontualmente") and heavy inline emphasis, which makes the many action alternatives hard to scan and 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?

For a complex 23-parameter, 14-action facade with no output schema, the description is remarkably complete: it covers the core flow, one-off invoke semantics, auth/credential/payment behavior, permission requirements, installed flags, the prompt library, and most action outcomes. The main gaps are the resume action and return-shape details for a few actions, but the overall guidance is sufficient for correct invocation 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 does a lot of compensating work: it maps action values such as search, describe, invoke, install, list_tools, publish_prompt, and explains tool_id, arguments, and prompt-related intent. However, several parameters and enum actions remain unexplained, including resume, limit, immediate, tier_slug, cancel_reason, report_context, conversation, request_name, and request_details, leaving agents under-specified for those paths.

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 in-platform catalog of MCPs/tools and the way to run them. It states the core discovery→describe→invoke flow, distinguishes the prompt-library subdomain from the MCP flow, and makes it clear this is a marketplace orchestrator rather than one of the sibling calculator/authenticate 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 gives explicit when-to-use guidance: use install only to make an MCP permanent, prefer invoke for one-off use, use list_tools to see what is callable now, use subscribe/cancel for billing, and use request_mcp when nothing fits. It also explains what to do when invoke returns a connect link or checkout link, including retry behavior.

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 carry the safety profile with idempotentHint=true and destructiveHint=false. The description adds that conversation data is needed for reproduction, which is useful context. However, it does not disclose what happens after submission, such as whether a ticket is created or whether the report is asynchronous, though the annotations lower the burden.

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 consists of two tight sentences: the first states the purpose, the second gives the key usage instruction. There is no filler, repetition, or irrelevant detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple three-parameter reporting tool with annotations already covering idempotency and destructiveness, the description is mostly sufficient. The main gaps are the unexplained `context` parameter and the absence of any indication of what the response or outcome will be, though no output schema is 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 for undocumented parameters. It only clarifies the `conversation` parameter via 'conversation array with recent messages,' leaving the required `message` and optional `context` undefined. The agent must guess at their intended content.

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 the verb 'Report' and explicitly enumerates three targets: 'bug, missing feature, or send feedback'. This makes the tool's purpose unmistakable and easily distinguishable from the sibling calculo_* and authentication tools, which serve entirely different functions.

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 establishes a clear context: use when a user reports a problem or wants to provide feedback. It also adds practical guidance to 'Include the conversation array with recent messages for reproduction.' It does not name alternatives, but none of the sibling tools overlap with bug reporting, so exclusions are unnecessary.

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 and idempotentHint=true, so the agent knows this is a safe, non-mutating call. The description adds little beyond that—it names the output as versions but doesn't specify the format (e.g., semver strings, JSON object) or whether the output is human-readable. Since the annotations carry the safety profile, a 3 is appropriate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 9 words, front-loading the action ('Show') and the object ('version'). There is zero waste, and it fully conveys the tool's purpose within its scope. This is a model of conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, read-only, idempotent tool with no output schema, the description is nearly complete. An agent can confidently invoke it without additional context. The only minor gap is that the return format is unspecified, but since there is no output schema, a brief note on the output structure (e.g., 'returns a plain-text summary') would elevate completeness. Still, the description is sufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema coverage is 100% (no properties). The description doesn't need to explain parameters. The baseline for zero-parameter tools is 4, and the description is consistent with that—it correctly implies that no input is required.

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: 'Show the current MCP platform and adapter versions.' This is a specific verb-resource pair that distinguishes it from sibling tools, which are all calculation or authentication tools. It could be slightly more explicit about what 'show' returns (e.g., a text summary vs. structured data), but the resource is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies that this tool is for checking version information, which makes sense in contexts where an agent needs to confirm platform/adapter versions before proceeding. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention whether version information is needed for authentication or compatibility checks. Given the sibling tools are all calculations, the usage context is reasonably clear, but not explicitly delineated.

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

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

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to restate safety. It adds value by detailing what kind of state is returned, including connection status and account bindings, which helps the agent understand the tool's informational scope.

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?

A single tightly packed sentence with the main action front-loaded, followed by a colon-delimited list of return contents. Every phrase earns its place with no repetition 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?

For a zero-parameter, read-only introspection tool, the description fully covers what the agent needs to know before calling: what information it will receive. No output schema exists, but the description essentially provides a light output contract by enumerating the returned components.

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 is empty with zero parameters, and schema description coverage is 100%, so the description has no parameter burden. Per calibration, zero-parameter tools receive a baseline of 4; the description's output-focused content is more than sufficient.

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 ('Returns') and resource ('current toolkit state'), then enumerates exactly what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This is specific enough to distinguish it from computational siblings like calculo_* and action tools like authenticate or connect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly conveys that this is the tool to call when an agent needs an overview or snapshot of the toolkit's current state. It does not explicitly list exclusion criteria or name alternatives such as show_version, but the context is clear enough for routine selection.

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