Cadastro Ambiental Rural: Download de Shapefile

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

Annotations already indicate idempotentHint=true and destructiveHint=false. The description adds valuable context about the two login modes (permanent vs session-only) and how the token is handled, which goes beyond the annotations. No contradictions detected.

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, somewhat dense sentence but remains readable. It front-loads the purpose and then provides examples. Slightly verbose with the 'MCP.AI for IDE agents' prefix, but every clause contributes to understanding.

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 authentication tool with one optional parameter and no output schema, the description covers the core use cases and behavior. It does not mention return values or error handling, but that is minor given the simplicity and existing annotations.

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 has only 'token' with no description (0% coverage). The description fully compensates by explaining the token is a JWT for session-only login and that calling without it returns a link. This gives clear meaning to the parameter and its optionality.

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: authenticating users via a browser login and token retrieval. It specifies the action ('log in', 'copy the access token') and distinguishes it from sibling tools implicitly by focusing on authentication flow. It is specific and not a tautology.

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 clear usage instructions: two methods (permanent via config header, or session-only via token argument) and explains the no-argument behavior. It does not explicitly contrast with sibling tools like 'connect', but the context is clear enough for the agent to know when to call it (initially or when token expires).

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 (read-only, idempotent, non-destructive), the description adds meaningful context: hosted platform, prepaid credit payment, official data sources, non-confidential data, and LGPD compliance. This enriches the agent's understanding of operational and legal constraints.

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 core purpose, followed by relevant operational and legal details. Every sentence adds 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 simple one-parameter tool with strong annotations and no output schema, the description covers purpose, access method, payment model, data origin, and legal responsibilities. It is fully adequate for an agent to select and invoke this 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?

The schema has one required 'car' string parameter with no description coverage. The description implies 'car' refers to the CAR registry identifier through domain context, but it doesn't explicitly explain what value to provide or its format. This is a minor gap.

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 downloads/consults shapefiles for the Cadastro Ambiental Rural (CAR) from official Brazilian sources. It distinguishes itself from sibling tools by naming a specific resource and action.

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 clear context: used for downloading CAR shapefiles from official sources, with payment per query and no platform credentials. However, it doesn't explicitly state when not to use it or mention alternatives, so it scores a 4 rather than 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 already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds behavioral context about the response format in two scenarios (authenticated:true with empty pending[], or connect_url for toolkit and per-install URLs), which goes 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 two sentences, front-loaded with the primary function, then a conditional breakdown. Every sentence contributes meaningful information, with no extraneous detail. Structurally clear and 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 low complexity (no parameters, no output schema) and rich annotations, the description is complete for a status-check tool. It covers the two main scenarios a user would encounter, making it sufficient 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?

With zero parameters, the schema provides no input semantics. The description explains the tool's behavior independent of parameters, aligning with the baseline of 4 for tools with no parameters. It adds meaning by describing what the tool returns without requiring any input.

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: returning connection status and URLs. It distinguishes itself from siblings like authenticate by focusing on status check rather than authentication. The conditional output scenarios (connected vs missing credentials) add specificity.

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 on when this tool is relevant: when all providers are connected vs when credentials are missing. It implies usage for status checking but doesn't explicitly contrast with alternatives like authenticate. However, the conditional behavior clarifies when to expect certain outputs.

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, and the description adds substantial behavioral context: writes 'require workspace owner/admin', invoke works even when the MCP is not installed, and auth/payment failures surface as connect/checkout links. It also discloses that invoke does not add the MCP to the toolkit, which is a key non-obvious behavior. No contradiction with the annotations is present.

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 dense paragraph but front-loads purpose and core flow before diving into specific behaviors. Every sentence adds information, and the length is largely warranted by 14 actions and 23 parameters. Bulleted structure would improve scannability, but the text is still efficient and well-ordered.

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 router with 23 parameters and no output schema, the description covers the main flows, permissions, invoke failure/link behavior, and the prompt-library subsystem. It leaves gaps around the 'resume' action, search/list_tools return formats, and the 'immediate' parameter, but overall it is notably complete given the tool's 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?

With 0% schema description coverage and 23 parameters, the description carries a heavy burden. It does explain the action enum in prose and clarifies relationships like describe → tool_id and prompt_vars for get_prompt. However, many parameters (limit, query, immediate, conversation, tier_slug, request_details, cancel_reason) remain unexplained in both the schema and description, so parameter-level guidance is incomplete.

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' and explains it is both a catalog and execution layer ('the way to run them'). It enumerates the core flow (search → describe → invoke) and separates the prompt-library functionality, so the broad router purpose is unmistakable. It distinguishes itself from siblings by being the central MCP catalog/runtime rather than a single-purpose tool like authenticate 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 gives explicit usage rules: 'prefer invoke for a single/occasional use' vs. 'Use install only to make an MCP PERMANENT' and 'list_tools lists what is callable right now.' It also explains when invoke returns connect/checkout links and that the user should retry after acting. This is strong when-to-use and when-not-to-use guidance, including the alternative prompt-library flow.

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 provide idempotentHint=true, readOnlyHint=false, and destructiveHint=false, indicating a non-readonly but non-destructive operation. The description adds that the conversation array is needed 'for reproduction,' implying the data is used for debugging. However, it does not disclose potential side effects (e.g., sending data to a server, possible delays, or that the report is stored). With annotations available, the description adds some context but not rich behavioral detail.

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 filler. It front-loads the core action and then adds a concise, actionable instruction. Every word earns its place, making it highly efficient and easy to scan.

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 3 parameters (one required) with no schema descriptions, no output schema, and only sparse annotations, the description is insufficient. It covers the overall purpose and one param (conversation) but fails to explain the required 'message' and optional 'context' parameters. It also does not mention what happens after a successful report (e.g., confirmation, no response). For a reporting tool with this complexity, the description is under-specified.

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 explicitly mentions the 'conversation' parameter ('Include the conversation array'), providing meaning for that param. However, it does not explain the required 'message' parameter (presumably the bug description) or the 'context' parameter (which has a default). The purpose implies message content, but without explicit mapping, the description only partially clarifies parameter meanings.

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.' It uses a specific verb ('Report') and identifies the resource (bug, missing feature, feedback). While it does not explicitly differentiate from siblings, the sibling tools are unrelated (e.g., authenticate, marketplace), so no confusion arises. The added instruction about including the conversation array reinforces the purpose.

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 by stating what the tool does, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. The instruction to 'Include the conversation array with recent messages for reproduction' gives context for proper invocation, but there is no exclusion or comparison to other tools. Since siblings are unrelated, this is minimally adequate but lacks explicit 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, idempotentHint, and destructiveHint, covering safety. The description adds that it shows 'current' versions of 'platform and adapter', providing context beyond the annotations. No contradiction exists, though it doesn't specify output format or potential side effects—minimal but adequate for such a simple read-only operation.

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, straightforward sentence conveys the entire purpose and scope. No fluff or redundancy. It is perfectly concise and front-loaded with the essential verb and resource.

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-checker with annotations covering safety, the description is complete. It explains what the tool returns (versions) without needing to detail output schema. The presence of sibling toolkit_info might imply overlap, but the description's clarity suffices for a tool this simple.

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. The description correctly mentions 'current' versions, but there is nothing more to explain about parameters. This score reflects that no parameter documentation 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 uses a specific verb ('Show') and resource ('platform and adapter versions'), clearly stating the tool's function. It is distinct from siblings like authenticate, connect, or marketplace, which serve different purposes. No ambiguity remains about what this tool does.

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 version information, but it does not explicitly contrast with alternatives like toolkit_info, which might also provide version details. No explicit when-to-use or when-not-to-use guidance is given, though the context is pretty obvious for a version-checking 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, idempotentHint, and destructiveHint, covering the safety profile. The description adds valuable context beyond these annotations by specifying the exact content of the returned state (installed MCPs, connection statuses, accounts, tool counts), which helps the agent understand what to expect. 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 description is a single, tightly worded sentence that front-loads the action ('Returns') and packs all relevant information without wasted words. It is exemplary in conciseness and 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's low complexity, the lack of parameters, and the absence of an output schema, the description fully covers what the tool does and what it returns. It lists the key categories of information included in the toolkit state, making it complete for an agent to decide whether to invoke it.

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 an empty input schema, so there are no parameter details to clarify. The baseline of 4 applies because the description correctly indicates there is nothing to parameterize, and it adds no extraneous 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's purpose with a specific verb ('Returns') and details the exact resource (current toolkit state) and its components (installed MCPs, connection status, accounts, catalog tool counts). It is easily distinguishable from sibling tools like show_version, which would focus only on version information.

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 the context of use clear (when you need an overview of the toolkit's state), but it does not explicitly mention when not to use this tool or name alternatives. The usage is implied rather than directly stated, so guidance is adequate but not thorough.

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