INMETRO Instrumentos: Veículos Tanque

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

Annotations already indicate the tool is not read-only and is idempotent. The description adds valuable behavioral context: calling with no args yields a login link, calling with a token establishes a session-only login, and the token is a JWT. It does not disclose failure modes (e.g., invalid token handling), but for a simple auth tool it provides meaningful transparency 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 reasonably concise but slightly stream-of-consciousness, mixing user-facing instructions with tool API guidance. It front-loads the tool's purpose and each sentence contributes value, though it could be structured more cleanly (e.g., separate 'no args' vs 'with token' cases).

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 and no output schema, the description covers the workflow adequately: how to initiate (no args), how to complete (token), and the permanent alternative (config header). It does not describe return values or error conditions, but the flow context is sufficient for an 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?

With 0% schema description coverage, the description fully compensates by explaining the token parameter: 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' It also clarifies that the parameter is optional and gives the exact invocation format, which is more than the bare schema provides.

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 the tool's purpose: authenticate with the MCP.AI server by returning a login link (when called with no args) or accepting a pasted JWT token. It is specific about the resource and action, though it interleaves user instructions ('log in in the browser, copy the access token') with tool behavior, slightly reducing crispness.

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

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

It provides clear usage context: for a permanent connection, recommends configuring an Authorization header in the server config; for session-only login, call this tool with a token or with no args to get the link. This effectively distinguishes between configuration-based and session-based authentication, though it doesn't explicitly compare against sibling tools like 'connect'.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds value by explaining the response behavior in different states (all connected vs. missing credentials), which goes beyond the annotations. No contradiction found.

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

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

The description is two sentences, front-loaded with the core purpose, and every sentence adds value. It efficiently explains the tool's behavior without redundancy.

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

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

Given the tool has no parameters and no output schema, the description adequately explains the return values and states. It covers the main scenarios (all connected vs. missing credentials) and is complete for a simple status tool. Could mention edge cases like partial connectivity, but overall sufficient.

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 schema coverage is 100% (vacuously), and the description focuses on the output behavior, which is appropriate for a parameterless tool.

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

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

The description clearly states the tool returns connection status and URLs, and distinguishes it from siblings like authenticate and marketplace by focusing on status reporting. It is specific about the resource (connection status) and the action (returns), though it could be more explicit about being a read-only status check.

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

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

The description implies usage for checking connection status, but does not explicitly state when to use it versus alternatives like authenticate. It provides context on what the response looks like in different states, but lacks explicit when-not-to-use guidance.

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

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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description does not contradict these. However, the description focuses on legal and commercial aspects (LGPD, payment, data controller) rather than behavioral characteristics like what the tool returns, how it handles errors, or rate limits. It adds some context about data source (official Brazilian sources) and non-confidentiality, but that is not sufficient.

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

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

The description is a single paragraph of moderate length but is not front-loaded with the core action. It mixes legal disclaimer, payment details, and data privacy information. Every sentence is not earning its place; for example, 'não é dado sigiloso' and 'O cliente é o controlador dos dados' are legal boilerplate that could be omitted. It is not concise in terms of clarity.

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 a simple schema (one required parameter) and no output schema, the description is insufficiently complete. It does not explain what query results will contain, how to interpret the output, or any specific details about the consultation process. The description emphasizes legal and payment aspects but omits the essential functional details that an agent needs to correctly invoke the tool and interpret its response.

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

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

Schema description coverage is 0% for the single parameter 'placa'. The description does not describe what 'placa' means beyond the context of 'veículos tanque' (tank vehicles), and it does not specify format (e.g., license plate format, required pattern). The description mentions 'consulta' and 'placa' is implied, but the description does not add any parameter semantics beyond the schema's name. Given the low coverage, the description should compensate but does not.

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 does not use a clear verb+resource pattern. It mentions 'INMETRO Instrumentos: Veículos Tanque, consulta em fonte oficial' but lacks a specific action like 'Consultar dados de...' It does not distinguish from sibling tools (all are generic platform tools, none similar). The name implies 'consultar' but the description is more about legal/business context than the tool's function.

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 no guidance on when to use this tool versus alternatives. It mentions 'pague por consulta' and 'sem credenciais' but these are operational constraints, not usage context. It does not explain scenarios where this tool is appropriate, nor does it mention alternatives. The sibling tools are unrelated, but no explicit usage guidance is given.

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 only say readOnlyHint=false and destructiveHint=false; the description adds substantial behavioral detail: invoke runs tools one-off without installing or bloating the tool list, writes require workspace owner/admin, invoke returns auth/payment links, and search/describe flag installed_in_toolkit vs installed_in_workspace. No contradiction exists 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 long and dense, but every section adds value given the tool's 14 actions and 23 parameters. It is front-loaded with identity and core flow, then covers invoke vs install, permissions, and prompt library. A bit more structure (e.g., separating prompt-library content) would improve scannability, but there is no filler.

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

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

For a highly complex multi-action tool with no output schema and 23 parameters, this description covers the main architecture, auth/payment edge cases, permissions, and the prompt-library subdomain. It slightly omits explanations for actions like resume and parameters like immediate/tier_slug, but overall it is remarkably complete for this complexity level.

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

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

Schema description coverage is 0%, but the description compensates by explaining the semantic roles of key parameters: action controls search/describe/invoke/install/prompt operations, tool_id selects the exact tool, mcp_id identifies the MCP, arguments carries tool params, and prompt_vars corresponds to {{variables}} filling. It does not individually document all 23 parameters, but the flow-level explanation is unusually helpful for a tool with zero param 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?

Description clearly states this is the mcp.ai marketplace catalog for discovering and running MCPs/tools, with a concrete core flow (search → describe → invoke) and additional prompt-library functions. It distinguishes itself from sibling tools by naming its specific catalog/run role and even differentiates its own actions (invoke vs install, search_prompts vs search).

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

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

Provides explicit when-to-use guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and 'list_tools lists what is callable right now'. It also explains conditional flows like connect links for missing credentials and checkout links for empty wallets, giving clear decision context.

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

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

Annotations already disclose safety traits (readOnlyHint=false, destructiveHint=false, idempotentHint=true), so the description only needs to add behavioral context beyond that. It adds the reproducibility instruction about the conversation array, which is useful, but it does not describe post-submission behavior or consequences of sending duplicates. 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 entire description is a single, well-structured sentence that front-loads the purpose and follows with a key operating instruction. There is no filler, repetition, or unnecessary detail.

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

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

For a simple 3-parameter tool with no output schema and reasonable annotations, the description provides enough for an agent to know when and roughly how to invoke it. It is not completely exhaustive because the optional 'context' param remains ambiguous and there is no final guidance on what happens after report, but the core mechanism and scope are well covered.

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

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

Schema description coverage is 0%, so the description must compensate. It partially does: it explains the purpose of the 'conversation' parameter (reproduction array) and indirectly tells users to put the report content in 'message'. However, the 'context' parameter is entirely undocumented, and the description does not clarify how expected each parameter is in practice.

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 action verb ('report') followed by clear objects ('a bug, missing feature, or send feedback'), which distinctly conveys the tool's purpose. This clearly separates it from sibling tools like authenticate, connect, and marketplace, and even broadens the scope beyond a literal bug report.

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

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

The statement 'Report a bug, missing feature, or send feedback' gives a clear context for when this tool is appropriate. It does not explicitly name exclusions or alternatives, but the sibling list makes those obvious; additionally it gives one practical usage instruction: include the conversation array for reproduction.

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

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds no additional behavioral context beyond these annotations, so no extra credit is warranted.

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 fully communicates the tool's purpose without fluff.

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

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

For a simple version-check tool with no parameters and no output schema, the description sufficiently conveys what it does and what it returns. It lacks edge-case or error details, but these are not critical for this low-complexity tool.

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

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

There are no parameters, so schema coverage is 100%. The description adds no parameter details, but none are needed; baseline score of 3 applies.

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

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

The description clearly states the tool shows current MCP platform and adapter versions, which is distinct 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 implies when to use it (when version info is needed) but lacks explicit guidance on when not to use it or alternatives. It's a simple tool, so this is adequate but not 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description does not contradict them. The description adds useful behavioral context by specifying what state aspects are returned, which is especially valuable given there is no output schema.

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

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

A single, front-loaded sentence communicates exactly what the tool returns without filler or repetition. Every element in the list adds meaning.

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, the description fully covers the return contents and the overall purpose. No output schema exists, but the enumerated state fields provide sufficient context for an agent to decide when to call this 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, so schema coverage is complete and there are no parameter semantics to clarify. A baseline of 4 is appropriate because the description correctly indicates no inputs are 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 uses a specific verb ('Returns') and resource ('toolkit state'), then enumerates the exact information included: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes 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 clearly implies it should be used to inspect overall toolkit state, and the enumerated contents make the context obvious. It does not explicitly state when to use it over alternatives or mention exclusions, but no sibling tool overlaps with this general status-reporting role.

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