DETRAN RR: Gravame

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

Annotations already indicate this is not read-only, not destructive, and idempotent. The description adds useful behavioral context beyond those hints: there are two distinct authentication modes, the no-args call produces a login link, and the config-header method provides a non-expiring connection. No contradiction with annotations exists.

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 one tight paragraph that front-loads the purpose and then provides actionable branches. It is slightly verbose with commentary about IDE agents, but every sentence contributes meaningful guidance, and it avoids unnecessary repetition.

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 full user workflow: browser login, token capture, permanent config, session-only usage, and no-args fallback. It does not describe error cases or explicit success responses, but those are not critical given 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 input schema provides only an optional token parameter with no description and 0% schema coverage. The description compensates well by explaining that token is a JWT the user pastes after browser login, and that omitting it returns the login link. This makes the parameter behavior clear despite the sparse 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 communicates the authentication flow: log in via browser, obtain a token, and authenticate either permanently via config or per-session by passing the token. It distinguishes itself from typical data tools, though it does not explicitly differentiate itself from the sibling tool '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?

The description gives explicit usage guidance: the recommended permanent approach is adding an Authorization header to server config, while the session-only approach is passing a token. It also explains that calling with no arguments returns the login link. However, it does not explicitly list when not to use this tool or compare it to 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 it as read-only, idempotent, and non-destructive. The description adds valuable context about response contents under different conditions (authenticated:true when all providers connected, connect_url when credentials missing), going 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 main purpose, and includes only necessary details. No redundancy or 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 zero-parameter read-only tool, the description adequately explains the expected output in both common states. It does not describe error scenarios or the full structure of 'pending[]', but given the simplicity and lack of output schema, this 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?

There are no parameters, so the baseline is 4. The description does not need to add parameter details, as none exist. It correctly focuses on the tool's behavior and return values.

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, with specific behavior described for two scenarios. It distinguishes from sibling 'authenticate' (which likely initiates authentication) by focusing purely on status retrieval. The verb 'returns' and resource 'connection status and URLs' are precise.

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 connection status) by explaining what it returns in different states. It does not explicitly mention alternatives or when not to use it, but the sibling context (e.g., 'authenticate') and the read-only nature make it clear this is for checking, not making changes.

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 known. The description adds meaningful context beyond that: no platform credentials are needed, payment is per query via prepaid credit, the source is official and non-confidential, and the client is the LGPD data controller. This is valuable behavioral context with 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 moderately concise and front-loaded with the core purpose. It contains several useful pieces of contextual information (payment, credentials, LGPD, official source) that all earn their place. It is slightly longer than strictly necessary but not bloated.

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?

This is a low-complexity query tool with one parameter and no output schema. The description covers the source, payment model, access credentials, and legal/privacy context, which is fairly complete for the tool's simplicity. It does not describe the return format, but given no output schema and simple nature, this gap is acceptable.

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 parameter 'chassi' with 0% coverage in the description. The description does not explain chassi formatting, required syntax, or how it relates to the query beyond the schema itself. Since schema coverage is low, the description should compensate but does not, leaving parameter semantics mostly implicit.

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 consultation for gravame (vehicle lien) data from DETRAN RR via an official source. It uses a specific verb ('consulta') and resource ('DETRAN RR: Gravame'), and it is clearly distinguished from the generic sibling tools like authenticate, report_bug, and 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?

The description provides clear contextual usage guidance: it is hosted on the platform, requires no platform credentials, and is paid per query with prepaid credit. It also clarifies that the data is the same available to citizens and not confidential. However, it does not explicitly state when not to use it or mention alternative tools, 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?

Goes well beyond annotations by revealing critical runtime behaviors: invoke runs uninstalled MCPs (one-off), returns a connect link for credential requirements, returns a checkout/top-up link for unpaid scenarios, and notes that writes require owner/admin privileges. Also explains installed_in_toolkit vs installed_in_workspace flags. 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 every sentence adds value and is well-organized: it opens with purpose, then explains the core flow, key invoke behavior, write prerequisites, and the prompt library. The structure makes complex information easily digestible without 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 complexity (23 params, no output schema), the description covers the most critical behaviors thoroughly: auth, payment, one-off vs permanent execution, ownership requirements, and prompt library operations. However, it omits details on the 'resume' action and does not address certain parameters like 'limit' or 'immediate', leaving minor gaps for full operational 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?

The description explains the semantics of the 'action' parameter by enumerating each action value and describing its purpose (e.g., search, describe, invoke, install, search_prompts). It also partially clarifies tool_id, mcp_id, arguments, and prompt_vars. However, with 0% schema coverage and 23 optional parameters, many fields (limit, immediate, tier_slug, cancel_reason, report_context, prompt_targets, etc.) remain unexplained, leaving a significant 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 it is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It outlines the core flow (search → describe → invoke) and explicitly distinguishes itself from sibling tools by being a meta-tool for discovery and execution, not a task-specific utility.

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 explicit when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT in the active toolkit.' It also delineates the prompt library flow (search_prompts/get_prompt/publish_prompt) and notes that writes require workspace owner/admin, giving clear context for choosing the appropriate action.

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 annotations (readOnlyHint false, idempotentHint true), the description adds the instruction to include a conversation array for reproduction, which clarifies expected input behavior. It does not detail side effects, but the report action is straightforward and the annotations cover safety (not read-only, not destructive).

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, with two short sentences that convey the core purpose and an important instruction. There is no redundant information, and the structure is clear and direct.

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 reporting tool, the description is adequately complete. It states what the tool does and gives a key hint about the conversation parameter. It does not mention output or return values, but since there is no output schema, this is acceptable. The description covers the essential usage context.

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 partial clarity: it explains that the 'conversation' parameter should contain recent messages, but it does not elaborate on 'context' or 'message'. The schema lacks field descriptions, so the description adds some value but leaves the other parameters ambiguous. Also, it calls 'conversation' an array while the schema declares it as a string, which could cause confusion.

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: to report a bug, missing feature, or send feedback. It distinguishes itself from sibling tools (authenticate, connect, etc.) by specifying a distinct action, making it 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 implicitly tells when to use the tool: when encountering a bug, missing feature, or wanting to provide feedback. It lacks explicit mention of alternatives, but given the sibling tool names, there is no competing tool for this purpose, so the guidance is sufficient.

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, covering the safety profile. The description adds the 'current' detail, implying live information, but does not describe output format or any other behavioral nuance.

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 front-loaded sentence with no filler. Every word contributes to the tool's purpose and scope.

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, zero parameters, and rich annotations, the description is sufficient for an agent to understand and invoke it. It does not detail the return value structure, but for a version query this is not a critical gap.

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 is no parameter burden for the description to carry. The baseline for zero-parameter tools is 4, and no additional parameter semantics are 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 identifies the exact resources ('current MCP platform and adapter versions'). This is unambiguous and distinct 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 clearly implies when to use the tool: when the agent needs current platform and adapter version information. It offers no exclusions or alternatives, but for a simple zero-parameter version query, the context is clear enough.

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 annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the primary behavioral aspects. The description adds detail on the returned content, which is consistent but does not introduce additional behavioral side effects beyond what the annotations already convey.

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 lists the key information returned without superfluous words. It is well-structured 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?

The description provides a clear overview of the returned state (MCPs, connection status, accounts, catalog tool counts). While it does not specify exact output structure or error handling, it sufficiently covers the essential information for a simple status tool with no output schema.

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, so the description does not need to explain parameter semantics. The schema is fully covered with an empty properties object, and the description adds nothing contradictory or incomplete in this regard.

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 the current toolkit state, including installed MCPs, connection status, connected accounts, and catalog tool counts. The verb 'Returns' is specific and effectively distinguishes this read-only status tool from sibling tools like 'connect' or 'authenticate'.

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 as a read-only status check but does not explicitly state when to prefer this over other tools. No explicit guidance on when to use or not use alternatives is provided, making the intended context only implicit.

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