Prefeitura SP São Paulo: DSV Digital

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

The description discloses the tool's behavior: it returns a link when no token is provided, and accepts a token for session login. It also explains that the config method is permanent and non-expiring. Annotations indicate idempotentHint: true, which aligns with the tool's nature; the description adds context about security (token) and session vs permanent, which is not in annotations. However, it doesn't mention potential side effects like invalidating prior sessions, but that's a minor gap.

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

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

The description is concise and front-loaded with the tool's purpose, then explains usage. It's a single paragraph but well-structured with clear instructions. It could be slightly more structured (e.g., bullet points) but is not 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 tool is simple with one optional parameter and no output schema, so the description covers the essential aspects: login flow, token usage, and permanent vs session. It doesn't explain return format, but that's not critical for an authentication tool. It sufficiently covers context for an agent to invoke 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?

Parameter 'token' is not described in the schema (0% coverage), but the description explains its meaning: a JWT copied from browser after login. It distinguishes when to pass it vs. not, adding significant value beyond the schema. The description effectively compensates for the lack of schema descriptions.

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 authenticate with MCP.AI by logging in via browser and obtaining an access token. It distinguishes between two modes: permanent config-based login and session-only token pasting. This is specific and differentiates from siblings like 'connect' and '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 provides explicit usage scenarios: when to use the permanent config method (recommended) vs. session-only login, and explains how to call the tool (with no args to get the link, or with a token). It also mentions best practice (adding header to config), giving clear when-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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds behavioral context about the two possible return states (authenticated:true vs. connect_urls), which is useful. However, it does not describe the exact structure of the response beyond the mentioned fields, and there is no output schema to fill that gap.

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

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

The description is two sentences, front-loaded with the core purpose, and every sentence adds value. It efficiently covers the main behavior and the edge case of missing credentials without any 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 has no parameters, no output schema, and simple annotations, the description is fairly complete. It explains the two main states and what the user can expect. It could be slightly more complete by mentioning the exact fields returned (e.g., authenticated, pending, connect_url) but the description already names them. The lack of an output schema is compensated by the description's clarity.

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 parameter semantics. The baseline for 0 params is 4, and the description appropriately focuses on the output behavior instead. No additional parameter information is needed.

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 distinguishes between two states (all providers connected vs. missing credentials). It is specific about the resource (connection status) and the output (authenticated flag, pending array, connect URLs). It does not explicitly differentiate from siblings, but the purpose 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 implies when to use this tool (to check connection status and get URLs when credentials are missing) but does not explicitly state when not to use it or mention alternatives. Given the sibling tools like authenticate and toolkit_info, some guidance on when to use connect vs. those would improve the score.

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 sparse (readOnlyHint=false, openWorldHint=true), so the description carries the burden — and it delivers rich context: invoke runs one-off without installing or bloating the tool list, writes require workspace owner/admin, invoke returns connect/checkout links with a retry instruction, publish_prompt shares a login-free mcp.ai/p/<slug> link. This massively exceeds what annotations convey, with no contradiction (description's write semantics align with readOnlyHint=false).

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 ~400-word paragraph with no bullet points or section headers, making it hard to scan despite information-dense content. Every sentence does earn its place given the 14-action complexity, but the wall-of-text structure hurts readability and front-loading beyond the initial core flow.

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 14 actions, 23 parameters, and no output schema, the description covers the main workflows thoroughly but leaves gaps: the general return format of search/describe is never stated (only special-case returns like connect links are mentioned), and several parameters (message, immediate, conversation) remain unexplained. Strong breadth but incomplete for the tool's high complexity.

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% across 23 parameters, so the description must compensate. It explains the critical action enum (all 14 values via the core flow and prompt-library section), tool_id selection, arguments, prompt_* fields, and cancel_* fields. However, several parameters (message, immediate, conversation, tier_slug) are never elaborated, so the burden isn't fully met despite strong coverage of the central action 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 identifies the tool as the mcp.ai marketplace — a catalog AND execution layer for MCPs, then enumerates distinct purposes per action (search/describe/invoke/install/subscribe/prompt library). The verb+resource is identifiable (catalog + run tools), but because this is a 14-action dispatcher, the single purpose is inherently diffuse, which keeps it below a 5.

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

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

Excellent internal guidance: explicitly spells out the core flow (search → describe → invoke), gives a when/when-not rule ('prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT'), and explains the connect-link and checkout/retry flow for credential/paid cases. However, it does not reference external sibling tools (e.g., authenticate, toolkit_info) as alternatives, so it misses the cross-tool comparison that would earn 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 declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and the description adds context that it's a read-only consultation of official data, not confidential ('não é dado sigiloso'), and that the client is data controller under LGPD. This aligns with annotations and provides some extra context about data ownership and legal compliance, but does not disclose potential fees, rate limits, or failure behaviors.

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 of moderate length, front-loaded with the core purpose. It is concise but includes some unnecessary details about LGPD and payment which, while informative, could be trimmed. Overall efficient.

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 (4 required parameters, no output schema), the description covers the purpose and legal context, but lacks details on input format (e.g., plate format), what the response contains, and how the login credentials are used. With no output schema and 0% param coverage, the description should provide more operational guidance.

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

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

Schema description coverage is 0%, and the description does not explain the purpose of each parameter beyond the tool's name. Parameters like placa and renavam are somewhat obvious, but login_usuario and login_senha are not explained; the description does not clarify whether they are platform credentials or DSV Digital credentials. The description adds minimal value over the raw 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 states it performs a consultation ('consulta') for São Paulo DSV Digital with official source ('fonte oficial'), which is clear enough. It does not explicitly mention the resource (vehicle data by placa/renavam), but combined with parameters it is inferable. It does not distinguish from siblings, which are generic (authenticate, connect), so not a major issue.

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 mentions payment via prepaid credits and that it is hosted on the platform, but it does not explain when to use this tool versus alternatives (e.g., other consulta tools). No explicit when-to-use or when-not-to-use guidance, and no mention of prerequisites like having a valid login (though login parameters are required).

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 disclose readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds the practical expectation that recent conversation messages should be included for reproduction, but it does not explain what happens after submission or whether any external system is affected. 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 only two sentences long, front-loads the purpose, and uses every word meaningfully. The reproduction instruction is focused and directly actionable.

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 three parameters and no output schema, the description is too thin. It does not document the required 'message' parameter, explain 'context', or describe what the tool returns or confirms after successfully reporting. Annotations help with the safety profile but not functional completeness.

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 parameter meaning. It explains that 'conversation' should contain recent messages for reproduction, but it omits the required 'message' field and the 'context' field. It also refers to 'conversation' as 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 uses a specific verb 'Report' and clearly identifies the three supported subjects: a bug, a missing feature, and feedback. This makes the tool's purpose distinct from siblings like authenticate, marketplace, and 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 gives clear context for when to use the tool: reporting bugs, missing features, or providing feedback. It does not explicitly mention when not to use it, but there is no obvious overlapping sibling tool requiring 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?

The annotations already indicate readOnlyHint=true and destructiveHint=false, which cover key behavioral aspects. The description adds no additional context such as authentication requirements or side effects, but it does not contradict the annotations either.

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

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

The description is a single, concise sentence with no superfluous words. It fully captures the tool's function without unnecessary elaboration.

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 it is a simple tool with no parameters and no output schema, the one-line description is complete. It clearly states what the tool does, and there is no missing information that would affect usability.

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 no parameters, and the schema coverage is 100% (vacuously). Since there are no parameters to explain, the description does not add or omit any meaningful parameter semantics, warranting a baseline score.

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: showing the current MCP platform and adapter versions. It uses a specific verb ('Show') and identifies the resource (versions), effectively distinguishing it from sibling 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 does not provide explicit guidance on when to use this tool versus alternatives. It only describes what it does, without mentioning context or exclusions, so the intended usage must be inferred.

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, so safety is covered. The description adds specific information about the returned content (MCPs, status, accounts, catalog counts), which is useful. No mention of side effects, but none are expected for a read-only query.

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 front-loads the verb and resource, then lists the specific data points. Zero filler or redundant text.

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 stateless info tool with no parametersaisles and no output schema, the description fully specifies what the agent can expect. It enumerates all relevant components, making it complete for the agent's decision-making.

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?

No parameters, so the baseline 4 applies. The description does not need to explain parameters, and none are present. The description is clear about what the tool returns.

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 names the resource ('current toolkit state'), then enumerates the components: installed MCPs, connection status, accounts, and catalog tool counts. This unambiguously distinguishes it from sibling tools like show_version or 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?

The description clearly implies usage for checking toolkit status but does not explicitly state when to use it over alternatives. However, its purpose is self-evident and distinct from siblings, so it provides adequate context without explicit exclusions.

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