DETRAN RS: CNH

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

Beyond the annotations, the description discloses that a config-based token is permanent/non-expiring, that pasted tokens are session-only, and that calling with no args returns the login link. It does not state the output format or what happens with invalid tokens, but it adds meaningful behavioral 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 compact at three sentences and front-loads the core action. The opening phrase 'MCP.AI for IDE agents (Cursor, etc.)' adds audience context but is slightly distracting; still, every sentence contributes usable information.

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 simple one-optional-parameter schema, no output schema, and sparse annotations, the description covers the main user flows: permanent config, session token, and link retrieval. It lacks explicit return-value details and error handling, but for this complexity level it is largely 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 schema has only an undocumented optional 'token' parameter with 0% description coverage. The description compensates by explaining that token is a JWT for session login and that omitting it returns the login link, which is essential semantic information not present in the 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 this tool authenticates the user by browser login and token entry, with a specific action of obtaining an access token or login link. It does not explicitly distinguish itself from the sibling 'connect' tool, but the verb and resource are reasonably 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 gives concrete when-to-use guidance: prefer adding the token to the server config for a permanent connection, or paste a JWT for a session-only login, or call with no args to get the link. It does not mention alternatives among sibling tools or exclusion cases, 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds valuable behavioral context by specifying conditional outputs: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing. This goes 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 two sentences, front-loaded with the core purpose, and then provides conditional details. Every sentence adds meaningful information without redundancy or fluff. This is an appropriately sized and well-structured description.

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 no output schema, so the description carries the burden of explaining return behavior. It covers the all-connected and credentials-missing cases well, but it does not clarify partial connection states, the meaning of pending[], or what 'per-install URLs' represent. This leaves some ambiguity for an agent interpreting the 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?

The tool has zero parameters, so the schema fully covers the input side. The description correctly focuses on output behavior rather than parameter details. A baseline of 4 is appropriate since there are no parameter semantics to clarify.

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 connection status and URLs.' It identifies the resource (connection status) and the action (returns), which distinguishes it from sibling tools like authenticate. However, it does not explicitly contrast itself with authenticate or other siblings, so it stops short of full differentiation.

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 the tool by describing two conditions: all providers connected versus credentials missing. This gives context for interpreting results but does not explicitly state when to use connect versus authenticate or other alternatives. There are no exclusions or when-not-to-use instructions.

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 adds beyond that: no platform credentials, prepaid per-query billing, non-confidential official data, and LGPD data controller responsibility. This is useful behavioral context not present in 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 compact and front-loaded with the main purpose, followed by brief billing and legal context. It is not overly verbose, though the LGPD sentence adds only governance context rather than operational 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?

With eight parameters, no output schema, and no parameter descriptions, this tool needs a richer description to be complete. The description covers official data source and payment model but omits parameter meanings, return values, and error/edge-case 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?

Schema description coverage is 0%, so the description must compensate, but it does not. None of the eight parameters (rg, cnh, nome, birthdate, login_cpf, login_senha, pkcs12_cert, pkcs12_pass) are explained, and 'sem credenciais da plataforma' even creates ambiguity about the optional credential parameters.

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 'DETRAN RS: CNH, consulta em fonte oficial', clearly specifying the resource (CNH from DETRAN RS) and the action (query). It also distinguishes the tool from generic sibling tools like authenticate, connect, and marketplace by naming a concrete official data source.

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 context: query official Brazilian CNH data, pay per query with prepaid credit, and no platform credentials are needed. However, it never explicitly states when to use this tool versus alternatives or mentions any 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?

The description discloses many non-obvious behaviors beyond annotations: invoke works even when the MCP is not installed, runs one-off without bloating the tool list, returns a connect link if credentials are needed, returns a checkout/top-up link for paid MCPs with empty wallet, requires workspace owner/admin for writes, and explains the prompt library. This adds significant context not available from annotations alone, 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 long but well-structured and front-loaded with the tool's purpose. It organizes content into core flow, key behavioral notes, and prompt library. For a tool with 23 parameters and many actions, this length is justifiable, and most sentences add value, though it could be tightened in places.

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 complexity (multiple actions, no output schema), the description covers the main flows, edge cases (connect/checkout links, permissions), and the prompt library. It also describes some return values (e.g., 'invoke returns a connect link', 'publish_prompt returns a shareable link'), which compensates for the missing output schema. However, some actions and their returns are not detailed, so it is 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?

With 0% schema description coverage, the description must compensate but only partially. It explains the action parameter through the core flow, implies tool_id is for invoking a specific tool, and hints at prompt_vars via '{{variables}} filled.' However, it does not explain many other parameters (limit, query, message, arguments, immediate, tier_slug, conversation, cancel_reason, etc.), leaving a significant gap in parameter understanding.

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, the catalog of every MCP/tool, and the way to run them. It distinguishes it from siblings by covering capability requests, listing specific actions (search, describe, invoke, install), and mentioning the prompt library, making it unmistakable 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 gives explicit guidance on when to use invoke vs install: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT in the active toolkit.' It also clarifies the core flow (search → describe → invoke) and notes that search/describe flag installed status. However, it does not directly mention alternative sibling tools (e.g., authenticate, connect) or when not to use this tool, so it falls short of a perfect 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 indicate idempotentHint=true and destructiveHint=false, but readOnlyHint=false, implying side effects. The description adds no extra behavioral context beyond 'report', which could imply sending data. It does not contradict annotations, but also doesn't elaborate on potential side effects or idempotency in practice.

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, using two short sentences without redundancy. It directly communicates the purpose and a key parameter requirement, earning full marks for brevity 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 absence of an output schema, the description adequately covers the tool's primary function and the key input for reproduction. It does not mention return values or post-action expectations, but because the output schema is not defined, this is acceptable. The description is complete enough for typical 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?

The description explicitly mentions the 'conversation' parameter, instructing to include recent messages for reproduction. However, it does not clarify the 'message' (likely the core feedback) or 'context' fields. Since schema descriptions are entirely absent, this partial coverage is the only guidance, leaving some parameters unexplained.

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: reporting bugs, missing features, or sending feedback. The verb 'report' and the specific resources ('bug', 'missing feature', 'feedback') make it distinct from sibling tools like 'authenticate' or 'marketplace'.

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 explicitly indicates when to use the tool (for bug reports, missing features, feedback). However, it does not mention when not to use it or provide alternatives, though the described scenarios are sufficient for typical usage.

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 that the tool reports current versions, which is consistent and sufficient for this 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 sentence that is concise, front-loaded, and contains no filler. Every word contributes to understanding the tool's function.

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 version-inspection tool, the description is fully adequate. It conveys the scope (MCP platform and adapters) without needing to explain return values 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, so the description carries the necessary semantic burden. It clearly indicates what information will be returned, meeting the baseline for a no-parameter 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 uses a specific verb ('Show') and identifies the exact resource ('current MCP platform and adapter versions'), clearly distinguishing it from siblings 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 purpose is self-evident and implies when to use it: whenever version information is needed. No exclusions or alternatives are mentioned, but no sibling tool performs a similar function, so the context is 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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral value by specifying the exact information returned, which is especially helpful 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 sentence that is dense yet scannable, front-loading the verb and resource before listing the returned details. Every phrase adds useful information with 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?

Given the tool has no parameters, no output schema, and strong annotations, the description fully covers the tool's behavior and return content. There are no meaningful gaps for an agent deciding 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, so the description correctly focuses on the return value rather than input semantics. Baseline of 4 for a parameterless tool is appropriate; the description does not need to explain parameters that do not 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 uses a specific verb ('Returns') with a clear resource ('current toolkit state') and enumerates exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like authenticate, connect, and 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 makes it obvious this is a read-only inspection tool for checking toolkit status, contrasting with action-oriented siblings. It does not explicitly name alternatives or exclusion scenarios, but the context is clear and no further guidance is necessary for such a tool.

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