DETRAN RJ: Multas (Guia de Recolhimento de Multas)

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

Annotations indicate idempotent and non-destructive hints, and the description adds context on the two login flows (permanent vs session) and that no-args returns a link. It does not contradict annotations, though it omits potential side effects like token invalidation.

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 purpose, and each sentence adds necessary detail without 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 a simple auth tool with one optional parameter and no output schema, the description covers all functional aspects, including alternative config method and output (link), making it self-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 one optional parameter 'token' with 0% description coverage, but the description fully explains its meaning (JWT from browser) and the behavior of calling without the token (returns a link), providing complete 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: authentication for IDE agents, with specific instructions on obtaining and using an access token. It distinguishes itself from sibling tools (e.g., 'connect', 'marketplace') which are unrelated.

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 usage scenarios: adding a header to config for permanent access, passing a token for session login, or calling with no arguments to get a link. It clearly outlines when to use each mode.

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, and the description adds useful conditional context, such as returning 'authenticated:true' when all providers are connected and 'connect_url' 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 tightly written in two sentences, leading with the core function and then elaborating on conditional returns. Every word adds value, and the structure is 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 read-only status endpoint with no output schema, the description covers the main success and failure scenarios (all connected vs. missing credentials). It doesn't mention rate limits or pagination, but those are unlikely to be relevant here, so the information provided 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?

The tool has zero parameters, so the baseline of 4 applies. The description is not required to explain parameters, and no additional parameter details are provided or 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 'Returns connection status and URLs' and elaborates on specific output conditions, such as 'authenticated:true' and 'connect_url'. While it doesn't explicitly differentiate from sibling tools, the behavior is well-defined and 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?

There is no explicit guidance on when to use this tool vs. alternatives like 'authenticate' or 'toolkit_info'. The description only describes what the tool does, leaving the agent to infer when it should be invoked.

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 goes well beyond the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) by disclosing the payment model (pay per query with prepaid credit), the absence of platform credential needs, the data sensitivity classification (not confidential but LGPD-governed), and the data controller responsibility. This significantly enriches the agent's understanding of side effects 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?

Four sentences front-load the core purpose and then cover payment, data scope, and legal responsibility efficiently. Each sentence adds new information, though the legal phrasing around LGPD and data controller feels slightly verbose and could be condensed.

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 excels at clarifying the business and legal context (pricing, data nature, compliance), but fails to address the most operationally critical aspect: input parameters. With three parameters, zero documentation coverage, and no output schema, the agent cannot reliably construct a valid request. The lack of any parameter semantics makes this incomplete for a 3-parameter 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 description coverage is 0%, and the description fails to compensate. None of the three parameters (cpf, cnpj, renavam) are explained or even mentioned, leaving the agent without any guidance on what these mean or what format they should take. The required 'renavam' parameter remains entirely opaque, which is a critical gap for correct invocation.

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 queries 'Multas (Guia de Recolhimento de Multas)' from DETRAN RJ official sources, using the specific verb 'consulta'. It distinguishes itself from utility siblings like 'authenticate' or 'report_bug' by focusing on a specific data consultation (fines) within a specific domain (DETRAN RJ).

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 by noting it's a paid per-query service with prepaid credit and LGPD compliance responsibilities, but it does not explicitly state when to use this tool instead of alternatives. For a niche data query tool among generic utilities, the paid/source context is helpful, but 'when not to use' and explicit alternatives are missing.

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 richly discloses behaviors beyond the annotations: invoke runs one-off without installing the MCP, returns connect/checkout links for auth/payment, and does not bloat the tool list. It also clarifies that writes require owner/admin, search/describe flag installed status, and prompt links open without login. No contradictions with annotations were found.

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 dense and fairly long, but every sentence adds essential information for a tool with 14 actions. It is front-loaded with the overall purpose and core flow, though it could be improved with bullet points or shorter paragraphs for readability.

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 of this complexity (23 parameters, no output schema, 14 actions), the description is notably complete. It covers the end-to-end flow, permissions, auth/payment scenarios, and the prompt library subsystem. However, a few actions (e.g., `resume`) and several parameters are not explicitly addressed, leaving minor gaps.

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 carries the burden of explaining parameters. It effectively explains the central `action` values (search, describe, invoke, install, subscribe, cancel, etc.) and the roles of `mcp_id`, `tool_id`, `arguments`, `prompt_vars`, and `prompt_slug`. However, several fields (e.g., `immediate`, `conversation`, `request_name`, `cancel_reason`) remain unexplained, so it falls short of full coverage.

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 in-platform catalog of every MCP/tool, AND the way to run them', and outlines the core flow (search → describe → invoke). It distinguishes itself from sibling tools by covering the full lifecycle of MCP discovery, execution, installation, and the prompt library, which is unique among the provided siblings.

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 invoke vs install ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use'), when to use request_mcp ('when nothing fits'), and how search/describe fit in. It also notes permission requirements ('Writes ... require workspace owner/admin') and gives context for list_tools, subscribe/cancel, and the prompt library actions.

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 a behavioral detail (including conversation array) but does not mention side effects, permissions, or reversibility. Annotations indicate idempotent and non-destructive, which are consistent. No contradiction, but limited additional transparency beyond 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 concise, consisting of two sentences with no redundancy. It leads with the purpose and includes a practical instruction, making it 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?

The description covers the core purpose and one usage detail, but lacks information about the return value, any expected outcomes, or the meaning of 'context'. For a simple reporting tool, it is adequate but not comprehensive.

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 no descriptions for the three parameters. The description clarifies the 'conversation' parameter (conversation array) and implies 'message' is required, but leaves 'context' ambiguous. Partial semantic coverage.

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. It is specific and distinguishable from sibling tools which focus on other functions like connecting, marketplace, etc.

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 the tool (reporting issues) and instructs to include the conversation array for reproduction. It does not explicitly mention alternatives or when not to use, but the context implies it is the designated reporting 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=true and destructiveHint=false, and the description's use of 'Show' aligns with a safe read operation, so there is no contradiction. Below that annotation baseline, the description only adds 'adapter versions' detail—useful info about scope but not deeper behavioral disclosure (e.g., network calls, performance). Acceptable for such a simple tool, hence a neutral 3.

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, eminently readable sentence front-loads the verb 'Show' and packs information efficiently. Every word serves a purpose without redundancy. Could not be more concise.

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 version-inspection tool with zero params, a simple description is appropriate and complete - there are no complex dependencies or return values (no output schema) that would require more elaboration. One could quibble about not documenting whether this requires an active connection (given the sibling 'connect' tool), but that is far outside the typical scope of a version check.

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?

Zero parameters exist in the schema (100% coverage trivially). With no params to describe, the baseline of 4 applies - the description isn't expected to explain inputs that don't exist. No deduction needed here.

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?

Clear verb + resource: 'Show' + 'current MCP platform and adapter versions' leaves no ambiguity about what the tool does. The scope is explicit, and despite being alongside potentially similar-sounding tools, the specific mention of versions makes it distinguishable. Nothing misleading or vague.

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 usage is implied via the description ('Show the current MCP platform and adapter versions'). Given the tool has zero parameters and a trivial return, explicit when-to-use guidance is less critical. However, no explicit mention of when not to use it or alternatives is given, placing it at baseline for a tool of this simplicity.

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 the return behavior (returns state) and does not hint at side effects. The annotations (readOnlyHint, idempotentHint) reinforce that it is safe and non-destructive. The description adds detail on what the state includes, which is transparent enough.

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 efficiently conveys the tool's purpose without unnecessary words. It is well-structured and directly states the return content.

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?

Since there is no output schema, the description fully explains what the return value will contain (installed MCPs, connection status, accounts, catalog tool counts). This is complete for a read-only informational tool, and no parameters require further 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 tool has no parameters (empty schema), so parameter semantics are trivially satisfied. The description correctly omits parameter details, as there are none to explain.

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 the current toolkit state, listing specific elements (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like authenticate or connect, 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 implies use when needing to inspect toolkit state, but does not explicitly state when to prefer this over other tools. It lacks direct comparison or scenarios, though the purpose is clear enough to infer its usage.

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