ANP: Postos

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

Annotations already declare readOnlyHint and non-destructive behavior. The description adds meaningful context: it is hosted by the platform, requires no platform credentials, charges prepaid credit per query, returns non-confidential official data, and assigns data controllership to the customer. It does not explain response behavior, but the added operational and legal context goes beyond annotations.

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

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

The description is compact and front-loaded with the core purpose. It includes necessary billing and legal context, though there is minor redundancy between 'consulta em fonte oficial' and 'informação de fontes e órgãos oficiais brasileiros'.

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 one-parameter read-only query tool, the description covers source, authentication model, billing, and legal obligations. However, with no output schema and no parameter explanation, details about expected return values, error cases, or CNPJ formatting are missing, making it only moderately complete.

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

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

The schema has only one parameter, 'cnpj', with no description and 0% schema description coverage. The tool description does not mention the parameter, its format, requiredness, or expected input, so it fails to compensate for the missing schema coverage beyond the parameter's self-explanatory 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 performs a query ('consulta') for ANP gas stations ('Postos') from an official source. It distinguishes itself from generic sibling tools like authenticate or marketplace, though it does not mention the CNPJ parameter explicitly.

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 context for use: no platform credentials required, prepaid credit per query, and LGPD responsibilities. However, it does not explicitly state 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?

The description goes beyond annotations by explaining the side effects of authentication, such as establishing a 'permanent, non-expiring connection' or a 'session-only login'. It also clarifies the behavior when called with no arguments versus with a token, which aligns with the idempotent annotation without contradiction.

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

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

The description is somewhat verbose and mixes introductory context with instructions, but it does follow a logical structure: first explaining the login flow, then detailing the 'Best' (permanent) and 'Or' (session) alternatives. It could be tightened, but the organization is functional.

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 lack of output schema, the description covers the essential context: purpose, usage steps, parameter meaning, and behavioral implications. It does not address error handling or edge cases, but for an authentication tool, this level of detail is 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 description provides meaningful context for the 'token' parameter, specifying it is a JWT that the user pastes after logging in. It also explains the alternative of calling with no arguments to receive a link, effectively compensating for the lack of schema-level parameter 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 clearly states the tool's purpose of authenticating the user, providing two distinct methods (permanent config or session token). It uses action-oriented language like 'log in', 'copy', and 'add', making the intent unambiguous. While it doesn't explicitly compare to sibling tools, the intended function is evident.

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 detailed step-by-step instructions on how to use the tool, including both permanent and session-based approaches. However, it does not explicitly state when to choose this tool over others or provide exclusion criteria. It implies usage by explaining the flow but lacks comparative 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, so the safety profile is clear. The description adds value by detailing the exact response behavior (authenticated:true and empty pending[] when connected; connect_url and per-install URLs when missing credentials), which complements the annotations well 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 that are direct and informative, front-loading the core purpose. Every sentence adds value, covering normal and failure modes without verbosity.

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

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

For a status tool with no parameters and clear annotations, the description is comprehensive. It covers the key scenarios and output structure. Without an output schema, it explains return values sufficiently. It could add a note about how to interpret pending[], but overall it is complete for the tool's 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?

The tool has 0 parameters, so the description need not explain parameter semantics. The description focuses on output semantics, which is appropriate. The schema is empty, and the description adds meaning by explaining the conditional output based on connection state.

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 reports connection status and URLs, with specific behaviors like returning authenticated:true and pending[] when all providers are connected. It distinguishes itself from siblings like authenticate (which presumably initiates connection) and toolkit_info by focusing on status and URLs.

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 (to check if all providers are connected and retrieve connect URLs when missing), but does not explicitly state when not to use it. It provides clear context for status checking but lacks explicit exclusions or naming of 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?

Beyond annotations, the description discloses permission requirements (writes require workspace owner/admin), the side-effect distinction between one-off invoke and permanent install, and auth/payment edge cases where invoke returns connect or checkout links. It does not detail error semantics for every action, but it is unusually transparent about the important behavioral traits.

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 but dense, with no filler; it front-loads the purpose and core flow before detailing alternative actions and the prompt library. It could be better structured with bullets or short sections, but every sentence carries operational value for a 14-action tool.

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

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

For a complex 23-parameter tool with no output schema and no per-parameter schema descriptions, the description covers the essential workflows, permission model, auth/payment edge cases, and prompt-library behavior. It is not exhaustive for every action or return shape, but the core context is complete enough to select and begin invoking the tool correctly.

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

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

Schema description coverage is 0%, so the description must carry parameter meaning. It explains the core parameters—action values, query, mcp_id, tool_id, and prompt fields—but leaves many parameters undocumented or only implied, such as limit, immediate, tier_slug, conversation, cancel_reason, prompt_targets, report_context, and request_details. This is adequate for the main flow but has clear gaps.

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 this as the official mcp.ai marketplace: the catalog of every MCP/tool and the way to run them. It names the core flow (search -> describe -> invoke), the prompt-library capability, and many action verbs, making the tool's purpose unmistakable and distinct from 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 gives explicit action-selection guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', 'list_tools lists what is callable right now', and 'request_mcp asks us to build a NEW MCP when nothing fits'. It does not explicitly contrast with sibling tools like authenticate or connect, but it clearly tells when to use the main internal 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?

The description adds a behavioral note that the conversation array is used 'for reproduction,' which goes beyond the annotations. Since annotations already declare readOnlyHint=false and destructiveHint=false, the description only adds a small extra detail. It doesn't mention side effects like external communication or rate limits, but given the annotations, this is adequate.

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 purpose and includes a necessary usage hint. Every word earns its place, with no padding.

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

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

Despite the tool being relatively simple with three plain string parameters, no output schema, and no enums, the description is still sparse. It omits guidance on what happens after reporting, required fields beyond 'message', and how to structure the conversation array. The provided instruction is good but not sufficient for unambiguous use.

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

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

Schema description coverage is 0%, so the description must compensate. It mentions 'conversation array' which hints at the 'conversation' parameter, but it doesn't explain 'message' or 'context' at all. The parameter types are all strings, and the default values are not explained. This is insufficient for a 3-parameter tool with no other parameter details.

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: 'Report a bug, missing feature, or send feedback.' This uses specific verbs and resources and is clear about its function. However, it does not differentiate from sibling tools, though the instant purpose is obvious enough for a near-top score.

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 instruction to 'Include the conversation array with recent messages for reproduction' provides some usage context, but there is no guidance on when to use this tool versus alternatives or any exclusions. It lacks the explicit 'when/when-not' structure needed for a higher 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds slight context by specifying 'MCP platform and adapter versions' but does not describe the return format or any other behavior beyond the core read action.

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, clear sentence with no filler. It front-loads the purpose and leaves out 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, zero-parameter, read-only version tool, the description is fully complete. It states exactly what is shown and there is no missing context about input, output, or side effects.

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 100%, so the schema is already complete. Per the baseline for zero-parameter tools, the description needs to add nothing further to satisfy parameter semantics.

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

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

The description uses a specific verb ('Show') and names a clear resource ('current MCP platform and adapter versions'), making the tool's purpose obvious. It does not explicitly contrast with sibling tools like toolkit_info, but the resource is specific enough to avoid confusion.

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

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

Usage is implied by the tool name and description: one calls this to inspect current versions. However, there is no explicit guidance on when to prefer this over sibling tools or any exclusions, but for a zero-parameter informational tool this gap is minor.

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

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

The description goes beyond annotations by specifying what the current state includes (installed MCPs, connection status, accounts, catalog tool counts). Annotations already indicate read-only and non-destructive, and the description adds useful output details 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 a single, concise sentence that directly states what the tool returns. No unnecessary words or repetition; it's front-loaded with the action verb.

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

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

For a read-only info tool with no parameters and no output schema, the description fully specifies the expected return content (toolkit state, MCPs, connection status, accounts, catalog tool counts). Annotations already cover safety, so this is 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?

There are zero parameters, so the schema provides no parameter documentation. The description clarifies that the tool returns state information, which is sufficient given the tool's simplicity. Baseline for no params is 4.

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

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

The description clearly states the tool's function: 'Returns the current toolkit state' and lists specific data points (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes from siblings like authenticate or connect by focusing on read-only state inspection.

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: it's the tool to call when you need an overview of the toolkit's integration status. However, there's no explicit when-to-use, exclusions, or mention of alternative sibling tools, so it relies on implicit context.

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