SENATRAN: Boleto da Infração

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

With annotations declaring idempotentHint=true and destructiveHint=false, the description adds useful context by revealing the browser-based flow, the two persistence modes (permanent via config vs. session-only), and that no-args returns a login link. This meaningfully extends the annotations' minimal data—though it could add a bit more about what the response contains or token 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?

The description is compact and every clause adds information, but it's written as a single meandering run-on with colons and 'Or' to stitch together three distinct flows (config, session token, no-arg). Better structural separation (e.g., bullet points or separate sentences) would improve scannability. Not bloated, but not elegantly 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 tool with one optional parameter, no output schema, and modest annotations, the description covers the key behavioral aspects: the two authentication modes and the side-effect-free no-arg call. The scope is simple, so the description needn't be verbose to be complete. Gaps like undefined return format keep it from a 5, but it's adequate for an agent to use 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?

Schema coverage is 0% and the schema only lists `token` as an untyped string with no description. The prose description compensates by explaining that `token` should be a JWT pasted after the user logs in, and that omitting it triggers the link-returning flow. However, the token parameter semantics aren't fully documented (e.g., no format validation details, no real example), so it's minimally acceptable but not exemplary compensation.

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 centers on authentication/login ('log in in the browser, copy the access token') and distinguishes itself from siblings like show_version and toolkit_info by being the auth tool. The 'MCP.AI for IDE agents' phrase and run-on structure add slight ambiguity, but the verb+resource (log in/authenticate with token) is clear enough to prevent confusion with siblings like 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 gives explicit options: best practice (config header for permanent connection), session-only (pass token), and no-args to receive the link. It explains when each usage mode applies. However, it never names alternative tools from the sibling list (like connect) or states when NOT to use this tool, so it misses the explicit exclusion criteria that would earn full marks.

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

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds specifics about the two return states and URLs, providing behavioral detail beyond the annotations without contradicting 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, front-loaded with the core purpose, and efficiently explains the two possible outcomes without any redundant wording.

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 are no parameters and no output schema, the description adequately explains the return values for the two main states. It could be more explicit about the 'pending' array contents when not all providers are connected, but the current coverage is sufficient for a simple status-check 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 parameters and schema coverage is trivially 100%. The baseline for 0 parameters is 4, and since there are no parameters to explain, the description does not need to add further 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 clearly states the tool returns connection status and URLs, and differentiates the two possible outcomes (authenticated vs. missing credentials). This distinguishes it from sibling tools like authenticate which likely handles authentication.

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 what the tool does (checking connection status) but does not explicitly mention when to use it vs. alternatives or when not to use it. The context is sufficient for an agent to infer usage, but lacks explicit 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 are minimal, so the description carries the transparency burden. It discloses one-off execution without installation, credential/payment failure behaviors with connect/checkout links and retry flow, owner/admin requirements for writes, and installed_in_toolkit vs installed_in_workspace flags. No contradiction with 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?

Though long, the description is dense and front-loaded: purpose, core flow, key invoke behavior, permissions, and prompt library follow in logical order. Every sentence contributes a distinct fact rather than restating the schema or title, and there is no tautological 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 14-action tool with no output schema, the description covers the main flows well: capability search, describe/select/invoke, install vs invoke, billing, permissions, and the prompt library. Notable gaps remain: the 'resume' action is never mentioned, and return shapes for search/describe/list_tools are not described beyond links.

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 prose must compensate. It adds meaning for core parameters like action, mcp_id, tool_id, and several prompt_* fields through the workflow narrative. However, many of the 23 parameters—immediate, tier_slug, conversation, report_context, request_details, cancel_reason, prompt_targets—are never explained, leaving advanced paths under-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 opens with a precise identity: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' naming the resource and its dual role as catalog and execution layer. It also spells out the search→describe→invoke core flow and the separate prompt library, making the tool clearly distinct from sibling tools like show_version, toolkit_info, and authenticate.

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

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

It gives explicit when-to-use guidance: 'Use install only to make an MCP PERMANENT in the active toolkit' versus 'prefer invoke for a single/occasional use,' and explains request_mcp is for when nothing fits. It also maps each action to its job, e.g. list_tools shows what is callable right now and subscribe/cancel handle per-MCP billing.

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 provide idempotentHint and destructiveHint, so the description need not repeat those. It adds that the conversation array should be included for reproduction, which gives some behavioral context. However, it does not explain what happens after the report is submitted (e.g., whether it creates a ticket or sends a message), leaving some opacity. The description is not contradictory to 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 no wasted words. It front-loads the purpose and then provides the key parameter guidance. Every word contributes to the tool's operation.

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 low complexity (3 params, no output schema), the description should adequately explain the tool's input and expected behavior. It covers the primary purpose and the conversation parameter but omits the context parameter and does not describe what happens after reporting (e.g., acknowledgment, ticket creation). The description is not fully complete for an agent to understand the full workflow.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions including the conversation array and implicitly refers to the message (the bug text) but does not explain the 'context' parameter at all. Additionally, it says to include the conversation array, suggesting it is required, though the schema marks it optional with a default of '[]', which could mislead the agent. The description adds some value but leaves gaps and introduces 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 clearly states the tool's purpose: to report a bug, missing feature, or send feedback. The verb 'Report' is specific, the resource is 'bug' (or feedback), and it is distinct from sibling tools like authenticate, connect, or show_version.

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

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

The description implies when to use the tool (when you have a bug or feedback) but does not explicitly mention when not to use it or provide alternatives. It gives a usage tip about including the conversation array but lacks specific guidance on choosing this over other 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 mark it as read-only, non-destructive, and idempotent. The description adds valuable behavioral details: it does not require platform credentials, it is a paid consult (prepaid credit), and the data is not confidential. It also clarifies data controller responsibilities (LGPD). This goes beyond the annotations and helps the agent understand implications like cost and data 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?

The description is a single paragraph, relatively short, and front-loaded with the tool's purpose. It includes essential metadata (official source, no credentials, payment model, LGPD responsibility) without excessive fluff. However, it could benefit from a bulleted structure for readability, though it is still concise.

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

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

Given that there are 8 parameters and no output schema, the description leaves much to be inferred. It explains the nature of the query (official, safe, paid) but does not explain what inputs are needed or what to expect in return. Since the tool has many parameters ordered without explanation, the description is insufficient for a complete understanding. A score of 3 reflects that it covers the 'what' and 'why' but not the 'how'.

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 none of the 8 parameters. It does not mention what 'chave_infracao', 'placa', 'obter_desconto', 'login_cpf', 'login_senha', 'pkcs12_cert', 'pkcs12_pass', or 'cnpj' mean. Given the tool has multiple parameters, the description should have at least explained the key ones. This is a critical gap, as the user cannot understand which parameters are required for what 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 identifies the tool as a query for Brazilian traffic fine billets (Boleto da Infração) from the official SENATRAN source. The verb 'consultar' (query) and resource 'Boleto da Infração' are specificтно named. It is easily distinguished from the generic sibling tools (authenticate, connect, etc.).

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 indirect usage context—official source, no platform credentials needed, pay-per-query, and LGPD compliance—but does not explicitly state when to use this tool over alternatives or exclude cases (e.g., if the fine is already paid). No comparison to other tools is provided, so it only implicitly indicates its 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the specific scope (both MCP platform and adapter versions), which is beyond the schema and useful context for the agent.

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?

Description is a single, front-loaded sentence that states exactly what the tool does. No fluff, no repetition of the tool name, and every word adds value.

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

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

For a zero-parameter, read-only version query tool with solid annotation coverage and no output schema, the description is complete. It clearly specifies what information is returned (platform and adapter versions), and no further detail is necessary for the agent to invoke 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?

Tool has no parameters, so the baseline is 4 as per instructions. The description does not need to elaborate on parameters since none exist, and no additional meaning 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 function ('Show the current MCP platform and adapter versions') with a specific verb and resource. It distinguishes itself from siblings like toolkit_info by specifying it focuses on MCP platform/adapter versions rather than general toolkit info.

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

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

The intended use case is evident: check compatibility or version details. While it doesn't explicitly list when not to use it or name alternatives, its unique scope (platform and adapter versions) implicitly separates it from sibling tools. No exclusions are needed for such a simple read-only tool.

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 behavioral context beyond those flags by specifying exactly what state is returned (e.g., connection status, accounts, tool counts). This enriches the agent's understanding without contradicting the annotations. A small deduction for not mentioning any side effects (though readOnlyHint implies none), which is minor given the annotations cover 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 a single, well-structured sentence that front-loads the action and result. Every word adds value, and the colon-delimited list improves readability. It's concise without losing specificity, earning a perfect score.

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 no parameters and no output schema, the description fully covers what a caller needs to understand the return value. It enumerates every major aspect of the state (installed MCPs, status, accounts, catalog tool counts), making the tool self-contained. There is no missing information for a tool of this simplicity.

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?

There are zero parameters, so the schema is trivially 100% covered. The description correctly avoids inventing parameters. Baseline for 0 params is 4, and no description details are needed. The description doesn't conflict with the empty schema, so a 4 is appropriate.

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 clearly identifies the resource ('current toolkit state') followed by an enumerated list of the exact contents (installed MCPs, connection status, connected accounts, catalog tool counts). It distinguishes this tool from siblings like 'show_version' by focusing on the aggregated toolkit state rather than version info, so it earns full marks for purpose clarity.

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 diagnostic/inspection tool but provides no explicit guidance on when to choose it over alternatives like 'show_version' or 'marketplace'. There are no exclusion criteria or alternative mentions. It barely meets the threshold for 'implied usage' (3) but offers no proactive context.

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