CAR (Cadastro Ambiental Rural)

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

The description explains behavioral traits not covered by annotations: it describes two different invocation modes and their effects (returning a link vs establishing a session). It also notes the permanent/non-expiring nature of the header approach. Annotations already indicate non-read-only, non-destructive, and idempotent, and the description aligns with these 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 dense but each sentence carries relevant information: the target audience, the auth flow, the two modes, and the call variants. It could be tightened slightly but remains efficient and front-loaded with the purpose.

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 there is no output schema, the description should ideally clarify what the tool returns in each mode. It implies the no-arg call returns a link, but does not state what happens when a token is passed (e.g., success message or session object). It also doesn't differentiate from sibling 'connect', but overall it provides sufficient context for an agent to invoke correctly in common scenarios.

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 only lists an optional 'token' property with no description. The tool description fully compensates by specifying the token is a JWT, how to pass it, and what happens when no args are provided. This adds meaningful context far beyond 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 clearly states the tool's purpose: authenticating IDE agents to MCP.AI. It uses specific verbs ('log in', 'copy the access token', 'paste') and distinguishes two usage modes (permanent header config vs session-only token). This differentiates it from siblings like 'connect' by focusing on MCP.AI-specific token auth.

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 guidance on when to use each approach: permanent connection via config header, session-only via token argument, or call with no args to get the login link. It also mentions the workflow (log in via browser, copy token). However, it doesn't explicitly compare with sibling tools or state when not to use this tool (e.g., for other connection types).

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=false. The description adds meaningful behavior context: no credentials needed, pay-per-query, public data only (not private/sigiloso), and LGPD compliance. This goes beyond 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 three sentences, front-loaded with the core purpose, then adding essential context (payment, credentials, data sensitivity). No redundant information, though it could slightly trim the LGPD detail without losing value.

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 has a simple input (1 required, 1 optional) and no output schema. The description mentions 'consulta informação' but does not specify what the response contains (fields, structure, success/error patterns). Given no output schema, some return-value detail would improve 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 carries the burden. It only explains 'NumeroCAR' as the input ('a partir do número do CAR') but completely omits the optional 'completo' boolean parameter. Agents cannot infer what 'completo' controls.

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 opens with a specific verb+resource+scope: 'Consulta o Cadastro Ambiental Rural (CAR) de um imóvel a partir do número do CAR.' This clearly states the tool queries the CAR by its number, distinguishing it from sibling tools like authenticate or report_bug.

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 clear context on when to use this tool: hosted on the platform, no credentials required, payment per query with prepaid credit, and access to public official data. It does not explicitly name alternatives or exclusions, but siblings are unrelated and the context is unambiguous.

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, so the safety profile is known. The description adds useful behavioral detail about the exact return payloads in different conditions, which is beyond the annotations. It does not describe partial connection states, but overall adds meaningful context.

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 long, starts with the main purpose, and every sentence provides concrete details. There is no filler or 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 read-only tool with no parameters and no output schema, the description covers the main behaviors well: successful connection and missing credentials. It leaves out the intermediate case of partially connected providers, which is a minor gap. Annotations handle the rest.

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 accepts zero parameters, so the schema is fully covered by default. Per the baseline for 0-param tools, a score of 4 is appropriate since the description doesn't need to add parameter-specific 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 'Returns' and identifies the resource as 'connection status and URLs'. It clearly distinguishes from sibling tools by focusing on status checking rather than actions like authenticate. The two detailed output scenarios further clarify the tool's 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 provides clear context for when the tool is relevant by describing the two states: all providers connected vs credentials missing. However, it does not explicitly mention alternatives or when not to use this tool, so it stops short of 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?

The description discloses critical behavioral traits beyond annotations: invoke runs uninstalled MCPs one-off, returns connect/checkout links on auth/payment failures, and requires owner/admin for writes. No contradiction with annotations (readOnlyHint=false, destructiveHint=false). This gives the agent operational details needed to anticipate side effects.

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 paragraph (~300 words) with no headers or bullet points. It is front-loaded with the main purpose but becomes a wall of text, repeating invoke/install advice and mixing the MCP marketplace and prompt library topics. While the content is valuable, the structure hampers quick scanning.

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 covers most actions, permissions, prompt library, and even error flows (connect/checkout links). However, it omits the `resume` action entirely and provides no details on output formats or pagination, which are important for a tool with no output schema. It is highly complete for core usage but not exhaustive.

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 coverage, the description compensates by explaining key parameters: `action` (all enumerated values), `tool_id` (used by invoke), `arguments`, and prompt parameters like `prompt_slug`, `prompt_vars`, and `prompt_body`. However, many parameters (limit, immediate, tier_slug, cancel_reason, etc.) are never mentioned, leaving gaps. Still, it adds substantial meaning for the core flow.

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: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It also explains the core flow (search → describe → invoke) and distinguishes marketplace actions from the sibling tools (e.g., report_bug, toolkit_info). This is a specific, verb-driven purpose that leaves no ambiguity.

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 when-to-use guidance, e.g., 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also defines the core flow and states that writes require workspace owner/admin. This clearly tells an agent when to use each action versus 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?

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds behavioral context by explaining the need for the conversation array for reproduction purposes. However, it does not detail post-submission behavior or any other side effects beyond what annotations imply. This is acceptable but not rich.

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 every word earns its place. No 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?

The tool has three parameters, no output schema, and annotations are present. The description covers the main purpose and the key conversation parameter, but the undocumented 'context' parameter and lack of any guidance on response or side effects leave gaps. It is adequate for a simple reporting tool but not fully 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?

Schema description coverage is 0%, so the description must compensate for the three parameters. It mentions the conversation array and implicitly covers the message, but it completely ignores the 'context' parameter. This is insufficient coverage for an undocumented 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 clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This uses a specific verb and resource, and it is easily distinguishable from the sibling tools (authenticate, marketplace, etc.) which serve unrelated functions.

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 on how to use the tool by instructing to 'Include the conversation array with recent messages for reproduction.' It does not explicitly mention when not to use it or alternatives, but the sibling tools are unrelated, so the usage context is reasonably clear.

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, which already cover the safety profile. The description adds no additional behavioral context beyond stating the function. While consistent, it does not reveal any side effects, return format, or other details. However, for a simple version query, the combination of description and annotations 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 sentence that directly states the tool's function with no unnecessary words. It is perfectly concise and front-loaded.

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?

With no parameters, no output schema, and a simple read-only operation, the description is sufficient to understand the tool's purpose and expected result. It doesn't need to elaborate on return formats or error conditions given the 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 no parameters, and the schema is empty. The description correctly omits parameter details, and with zero parameters, the baseline is 4. There is nothing more 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 the specific verb 'Show' and identifies the resource as 'the current MCP platform and adapter versions.' This clearly distinguishes it from sibling tools like authenticate or marketplace, which have different purposes.

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 any guidance on when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. It simply states what the tool does, leaving the agent to infer usage. Given the simplicity, this is a minor gap, but the rubric expects explicit guidance 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 clear. The description adds context about what the state includes (installed MCPs, status, accounts, tool counts) but does not disclose additional behavioral traits such as whether the state is cached, if it requires connectivity, or if it triggers any background refresh. This is acceptable but not rich.

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 sentence that front-loads the action ('Returns') and then provides a compact enumeration of the content. Every word earns its place with no redundancy or 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 an info tool with no parameters and no output schema, the description covers the key aspects of what is returned: installed MCPs, connection status, accounts, and catalog tool counts. It is complete enough for an agent to understand the tool's purpose and output. It could optionally mention that it reflects current live state, but that is implied.

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 schema provides no semantic burden. The baseline for 0 parameters is 4; the description does not need to add parameter details. It correctly focuses on the output rather than inputs.

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' and names the resource 'current toolkit state', then enumerates the specific details: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like authenticate, connect, and show_version, which serve different functions.

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 when to use the tool (when you need the toolkit state) and the scope of that state. It does not explicitly mention exclusions or alternatives, but the sibling tools are distinct enough that the purpose implicitly guides selection. A minor gap is the lack of explicit 'use when' or 'instead of' guidance.

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