DETRAN PR: Multas (Descritivos)

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

The description mentions that calling with no args yields a link, and indicates token is a JWT. It does not contradict the annotations (readOnly false, destructive false, idempotent true). It could elaborate on side effects, but it 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 clear and well-structured but slightly verbose. It could be condensed without losing essential meaning, but it is not excessively wordy.

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 and no output schema, the description covers all necessary aspects: both authentication methods, call syntax, and token format. It is complete for an agent to use 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 only parameter 'token' is described as a JWT, and its usage is explained (for session login). This adds meaning beyond the empty schema description, though a more detailed format description would be helpful.

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 purpose: to authenticate IDE agents (MCP.AI for IDE agents) and provides specific instructions on obtaining and using the token. It distinguishes itself from other tools like connect, 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?

It gives explicit guidance on when to use permanent config (adding to server config) versus session login (passing token or getting a link). It also clarifies how to call with token or without, covering both scenarios.

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 non-destructive behavior, so the description correctly aligns with those. It adds behavior context: authenticated:true with empty pending[], and the fallback connect_url/per-install URLs when credentials are missing. This is useful 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?

Two sentences, front-loaded with 'Returns connection status and URLs,' and every sentence adds a distinct behavioral fact. No fluff or redundant restatement of the annotations.

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 is simple, has no parameters, and no output schema, so the description must carry the load for return behavior. It covers the success case and the missing-credentials case, although it doesn't fully enumerate all possible states (e.g., partial connectivity), but for a status checker this is adequate.

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 the input schema is empty, so there is no parameter documentation burden. The description is empty-setting baseline 4 and does not have to explain parameter 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 begins by explicitly stating the resource and action: 'Returns connection status and URLs.' It distinguishes this infrastructure-status tool from sibling authentication/action tools such as authenticate and show_version, and it names concrete return states rather than merely restating the tool name.

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—when an agent needs to check connectivity, authentication state, or obtain the connect URL—and it explains the state conditions (all providers connected vs credentials missing). It does not explicitly name alternatives or say 'use X instead,' but 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 description aligns with the readOnlyHint annotation, noting it is a non-confidential query, and adds context about data source and LGPD compliance, though it does not fully explain the credential requirements.

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 repetitive and includes extraneous details about hosting and payment, but remains relatively brief.

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 does not specify the output structure or content of the query result, and lacks information on how the certificate is used, leaving many operational aspects unexplained.

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 no parameter descriptions and the description does not elaborate on renavam, pkcs12_cert, or pkcs12_pass, leaving users without guidance on their meaning or format.

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 DETRAN PR fines from an official source, distinguishing it from sibling tools like authenticate or 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?

It mentions the query is from an official source and involves prepaid credits, but it does not explicitly state when to prefer this tool over 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 only state readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false. The description adds substantial behavioral context: writes require workspace owner/admin, invoke runs one-off without adding to toolkit, paid/empty-wallet returns a top-up link, and prompt links open without login. This goes well beyond the structured 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 dense paragraph, but every sentence carries distinct operational information for a complex 14-action tool. It is front-loaded with the core flow and then expands into edge cases and prompt-library features. Slightly long, yet appropriately sized given the tool's 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?

For a high-complexity tool with no output schema, the description covers the primary workflow, auth/payment failure paths, permission requirements, and ancillary features. It does not detail return shapes for search/list_tools, nor fully enumerate all action semantics (e.g., resume, immediate, tier_slug), but the core usage is sufficiently explained.

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 meaningfully explains the core parameters (action=search, describe returns tool_id profiles, invoke RUNS the tool, prompt_vars filled into get_prompt). However, with 23 parameters, many (limit, immediate, tier_slug, cancel_comment) are not explained, leaving the agent to infer too much from names and defaults.

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 immediately identifies the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates a clear set of verbs (search, describe, invoke, install) and covers capability requests, distinguishing it from the 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 gives explicit when-to-use guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT in the active toolkit.' It also clarifies edge cases (credentials return a connect link, empty wallet returns a checkout link) and differentiates sub-actions like report_bug and request_mcp.

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 readOnlyHint=false and destructiveHint=false, and idempotentHint=true. The description adds the expectation to include conversation data for reproduction but doesn't disclose what happens to the submitted data or any side effects. It is not contradictory 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?

Single sentence with clear purpose and a useful instruction about conversation. No wasted words.

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 no output schema and 0% parameter descriptions, the description should explain the parameters more thoroughly. It provides basic purpose and one useful detail, but lacks clarity on message/context and post-submission behavior. For a simple tool, it's partially 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 carries the burden. It explains the 'conversation' parameter for reproduction but leaves 'message' and 'context' ambiguous. The required 'message' is only implicitly the report content, and 'context' is not explained at all.

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 action ('Report') and the resources ('a bug, missing feature, or feedback'), using a specific verb and scope. It distinguishes itself from siblings, which are unrelated operational tools.

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 specifies the use case: reporting bugs, missing features, or sending feedback. It also instructs to include a conversation array for reproduction, which is a clear usage guideline. However, it doesn't explicitly mention alternatives or exclusions, though none exist among siblings.

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, destructiveHint=false, so the description adds minimal but useful context by specifying what versions are shown (platform and adapter). It does not contradict annotations and complements them adequately.

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, front-loaded sentence of 10 words that is immediately scannable. Every word earns its place with zero verbosity.

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 version utility with no parameters, no output schema, and clear sibling context, the description is complete. It could explicitly mention returning version strings, but the enrichment is minor.

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 description doesn't need to add parameter semantics. The baseline for no params is 4, and the description appropriately omits irrelevant details.

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 ('MCP platform and adapter versions'), clearly distinguishing it from siblings like 'connect' and 'authenticate'. It unambiguously states what the tool does without any 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?

While there is no explicit 'when to use' statement, the purpose is self-evident for a version-inspection tool, and the sibling set (authenticate, connect, report_bug) makes the context clear. It could have mentioned 'use when checking compatibility' but is not necessary.

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 establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered by structured data. The description goes beyond by disclosing the precise contents of the returned state (installed MCPs, connection status, connected accounts, catalog tool counts), which is meaningful behavioral context given the absence of an output schema. It could have noted whether the call makes live network requests, but this is minor for an informational tool.

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 22-word sentence that is front-loaded with the subject ('current toolkit state') followed by a colon-style list of its components. Every word earns its place; no filler, no redundancy, and the structure makes it 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?

For a zero-parameter, read-only state-inspection tool with a fully annotated safety profile, the description supplies exactly the necessary information: what state is reported. Without an output schema, the description is the only guide to the return value, and it covers the four key facets (installed MCPs, status, accounts, catalog tool counts) succinctly leaving no major 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?

With zero parameters, the schema fully documents everything (vacuously, 100% coverage), so the baseline of 4 applies. There are no undocumented parameters for the description to clarify, and the empty input schema needs no elaboration.

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') plus a well-defined resource ('current toolkit state') and enumerates exactly what that includes: installed MCPs, their connection status, connected accounts, and catalog tool exposure counts. This level of specificity clearly distinguishes it from siblings like show_version (which would only return version data) and connect/authenticate (which are actions).

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?

Usage is implied rather than stated: an agent can infer to call this when it needs to inspect MCP installation status, connection health, or account bindings. However, the description does not explicitly name when NOT to use it, nor does it reference sibling tools (e.g., show_version) as alternatives, leaving situational discrimination to inference.

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