Cadastro Ambiental Rural: Demonstrativo (PDF)

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

Annotations declare idempotentHint=true and destructiveHint=false. The description elaborates meaningfully by distinguishing permanent (config header) vs. session-only login and stating that calling with no args returns the login link. This adds behavioral context 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 compact and front-loaded with context, followed by two clear usage modes. It is slightly dense with colons and conditionals, but every clause adds useful information and 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 tool with one optional parameter and no output schema, the description covers the input workflow and the no-arg behavior ('get the link'). However, it doesn't explicitly state what the tool returns after a successful token submission or what error/edge-case behavior the agent should expect, leaving some ambiguity.

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 provides only a bare 'token' string with 0% description coverage. The description compensates by clarifying that the token is a JWT, that it is optional, and exactly how it should be used ('{ token: "<jwt>" } after the user pastes'). This is enough to understand the parameter's 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 identifies the tool as a way to authenticate IDE agents to MCP.AI, using a browser login and access token. It explains the two main usage forms (permanent header config vs. session token). It does not explicitly contrast itself with sibling tools like 'connect', so it isn't a perfect 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?

The description gives explicit guidance: 'Best: add it to this server's config as a header...' and 'Or paste it here for a session-only login: call with { token: "<jwt>" }... or with no args to get the link.' This clearly explains when to use each invocation pattern, though it doesn't discuss alternatives or exclusions among sibling 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 the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral context: it queries official sources, the data is public ('não é dado sigiloso'), and there is a cost per query. It also clarifies the customer's legal role, which goes beyond the annotations. No 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 a single run-on sentence but remains concise and information-dense. It covers purpose, payment, data source, and legal context in under 300 characters. While not segmented for skimming, it is efficient and free of 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's simplicity (one parameter, no output schema), the description provides adequate context about the data source, payment, and LGPD compliance. However, the lack of parameter explanation and lack of mention about error handling or response format (though PDF is implied) leaves it slightly incomplete for an agent to use it with full confidence.

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 one parameter 'car' with 0% description coverage, and the description does not elaborate on what format or value to provide for this parameter. Although 'car' likely stands for Cadastro Ambiental Rural (inferred from the tool name), the description fails to explicitly explain that the parameter expects the registry code or how to format it. This is a significant gap for a mandatory 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 states 'Cadastro Ambiental Rural: Demonstrativo (PDF), consulta em fonte oficial' which specifies the exact resource (CAR demonstrativo) and action (consulta). It differentiates this tool from siblings by mentioning PDF output and official source. The purpose is unambiguous and 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?

The description provides useful context about payment ('pague por consulta com crédito pré-pago') and legal responsibility (LGPD), but it does not explicitly explain when to use this tool versus alternatives or when not to use it. The guidance is implied rather than directive.

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 read-only, idempotent annotations, the description explains specific behaviors for different states (all connected vs. missing credentials), adding context about returned URLs. This exceeds basic annotation disclosure, though it does not cover all possible states (e.g., partial connectivity).

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, using two sentences to convey the core functionality and key conditional outputs. There is no redundancy or unnecessary detail, making it highly 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?

The description explains return values for two key scenarios (all connected, missing credentials) without an output schema, providing useful context. However, it omits edge cases like partial provider connectivity, which could be important for full understanding.

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 in the schema, so coverage is trivially complete. Per the rubric, with high schema coverage and no parameters, the baseline score is 3, and the description adds no parameter-related information because none exist.

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, using a specific verb ('returns') and defining the resource. It distinguishes itself from sibling tools by focusing on status and URL retrieval rather than authentication or marketplace actions.

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 like 'authenticate' or 'marketplace'. It implies usage for checking connection status but lacks direct guidance on appropriate contexts, prerequisites, or when to avoid using 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 adds substantial behavioral context beyond annotations. It discloses that invoke runs the tool one-off without adding to the toolkit, returns connect/checkout links when credentials or funds are needed, and that writes require workspace owner/admin. It also explains the prompt library's sharing behavior, all of which go beyond the generic annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true).

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 (multiple paragraphs) but well-structured: it begins with a general overview, then walks through the core flow, adds key notes about invoke, and then covers each ancillary action (list_tools, subscribe, cancel, report_bug, request_mcp) and the prompt library. It is front-loaded with the most critical info, but its length and density make it less concise than ideal.

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 high complexity (23 parameters, 14 actions, plus a prompt library sub-system), the description is fairly complete. It explains return links (connect, checkout, shareable slug), authentication requirements, installation semantics, and the difference between one-off and permanent operations. However, it does not detail return formats for every action (e.g., what search returns beyond flags), leaving minor gaps, but overall it provides enough context for an agent to navigate the 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?

Schema coverage is 0%, so the description must compensate for parameter meaning. However, it only hints at the 'action' parameter by listing action values in the flow (search, describe, invoke, install, etc.) and briefly mentions 'arguments' and 'tier_slug' but does not explain most parameters like query, mcp_id, tool_id, message, limit, immediate, prompt_* fields. The description provides no explicit parameter semantics for the 23 parameters, leaving agents underinformed.

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', stating it is the in-platform catalog of every MCP/tool and the way to run them. It distinguishes itself from siblings by covering capability requests like 'find an MCP that does X' and 'consulta um CPF', and outlines the core flow (search → describe → invoke) with specific verbs and resources.

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 explicitly states when to use different actions: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and describes when to use report_bug, request_mcp, subscribe/cancel. It also specifies that search/describe flag installation status, and even explains the alternative for infinite use cases, covering both use cases and 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 already declare idempotentHint true and destructiveHint false, so the tool's non-destructive, idempotent nature is covered. The description adds no behavioral details beyond that—it only instructs on including conversation data, which is parameter-related rather than behavioral. No new behavioral insight is provided, and there is 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?

The description is two sentences, front-loaded with the purpose, and includes only essential procedural guidance. There is no fluff, repetition, or unnecessary detail, making it highly concise and well-structured.

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 (3 params, no output schema), the description could still be more complete. It fails to explain the 'context' parameter, doesn't mention what happens after reporting (e.g., response or confirmation), and doesn't compensate for the lack of output schema. While the purpose is clear, the guidance for all parameters and expectations is incomplete.

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 'conversation' as containing recent messages for reproduction, but it does not clarify 'context' at all, and 'message' is only implied by the purpose. The conversation parameter is described as an 'array' despite being a string in the schema, which is slightly misleading. Overall, it adds some value but leaves 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 states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is specific and distinct from sibling tools (authenticate, marketplace, etc.), which handle unrelated operations. The main action and resource are 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 provides no explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it. It only instructs that the conversation array should be included, which is about invocation, not selection. Given the siblings are unrelated, the usage context is implied but not articulated.

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 aligns with the annotations (readOnlyHint, idempotentHint, destructiveHint) and adds specificity by clarifying that it shows both platform and adapter versions, which is more detailed than just 'versions'. No contradictions exist.

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 the function without any filler or redundancy. It is perfectly front-loaded and easy to 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 zero-parameter, read-only version check tool, the description is sufficiently complete. It names the two specific version types (platform and adapter), which covers all relevant information needed to understand the tool's behavior.

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%. The description adds no parameter-specific details, but the baseline for no-parameter tools is 4, and nothing more 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's function: to show the current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('current MCP platform and adapter versions'), making its purpose unmistakable and 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?

No explicit when-to-use or alternative guidance is provided. However, the tool's purpose is self-evident—checking version info—and no competing sibling tool offers similar functionality, so usage is implied rather than explicitly 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 and idempotentHint: true, so the description only needs to add extra context. It does so by detailing what state is returned, which goes beyond the annotations and confirms a non-destructive read operation 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 a single, well-structured sentence that front-loads the primary action and then lists the returned components in a clear enumeration. Every word contributes value with no 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?

For a zero-parameter read-only tool without an output schema, the description fully captures what the tool returns, covering the key aspects of toolkit state. It is complete enough for an agent to infer expected results.

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 baseline is 4 per the rubric. The description does not need to explain parameter meanings since there are none, and the schema coverage is trivially complete.

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 the specific verb 'Returns' to identify the tool as an information query, and precisely enumerates what it returns: installed MCPs, connection status, connected accounts, and tool counts per catalog. This clearly distinguishes it from sibling tools like authenticate or connect, which are action-oriented.

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 tool is for retrieving toolkit state, which implicitly differentiates it from the action-oriented siblings. However, it does not explicitly state when not to use it or mention alternative tools, missing the full 'when-not' guidance that would merit a 5.

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