Prefeitura MG Uberlândia: Certidão Negativa de Débitos

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

The description discloses that the tool initiates a browser login and returns a link, and that tokens can be stored permanently or used for a session. It does not contradict annotations (idempotentHint=true is consistent with repeated calls being safe). It adds context about the token's non-expiring nature when configured, which 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?

The description is concise and front-loaded with the tool's purpose. It packs a lot of information into two sentences, but the second sentence is a bit dense with multiple clauses. Still, every sentence earns its place.

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 (one optional param, no output schema), the description covers the essential usage modes and the authentication flow. It could mention what the response looks like (e.g., success message) but that's not critical for an auth tool. The description is complete enough for an agent to use it 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 schema has one optional parameter 'token' with no description. The description explains that 'token' is a JWT to paste for session-only login, and that calling with no args returns the link. This adds meaning beyond the bare schema, though it could be more explicit about the token format and validation.

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 authenticate an IDE agent by logging in via browser and obtaining an access token. It distinguishes itself from siblings by specifying the authentication flow and the two modes (permanent config vs session-only).

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 this tool: to log in and obtain a token, with clear instructions for both permanent (config header) and session-only (paste token) usage. It also explains the no-args call to get the link, covering all usage 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=true tent and destructiveHint=false, so this is a safe read operation. The description adds useful behavioral details: it returns authenticated:true and empty pending[] when all connected, and provides connect_url when credentials missing. It also mentions per-install URLs. 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 two sentences, front-loaded with the main purpose, and every clause adds value. It avoids redundancy and is appropriately concise for a simple tool.

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 is simple (no params, no output schema) and annotations are rich, the description fully explains the tool's behavior. It could mention that this is a status check only, but the readOnlyHint already implies that. It's complete enough for an agent to use effectively.

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 parametersnew, and schema coverage is 100%, so the baseline is 4. The description adds no parameter information because there are none, but it compensates by explaining the response behavior, which is relevant to interpreting the result. Since there are no params to document, the high baseline is appropriate.

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, which is a specific resource and purpose. It distinguishes from siblings like authenticate (which likely initiates connection) and report_bug, but doesn't explicitly mention those alternatives. However, the purpose is clear and non-tautological.

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 context on when to use this tool (to check connection status) by describing two states (all connected vs. missing credentials). It implies it's for diagnostics. It doesn't explicitly state when not to use it or mention alternatives, but the context is clear enough for an agent to decide.

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 significant behavioral context beyond the sparse annotations: invoke runs one-off without installing or bloating the tool list, returns connect/checkout links when needed, and writes require workspace owner/admin. It also discloses installed_in_toolkit vs installed_in_workspace flags. 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 dense and front-loaded, opening with the tool's purpose and the critical invoke caveat, with no filler sentences. It could be more scannable with bullets or subheadings, but every sentence contributes useful information for such a complex tool.

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 with 14 actions, 23 parameters, and no output schema, the description covers core flows, permissions, billing, and the prompt library, which is more than minimal. However, it omits semantics for several actions/parameters (resume, immediate, tier_slug, conversation, etc.) and does not describe return shapes or error/retry behavior beyond the connect/checkout links.

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 23 parameters and 0% schema description coverage, the description must carry the parameter-semantics burden. It explains the action enum and core flow well (search/describe/invoke, tool_id selection, prompt variable filling), but many parameters (limit, query, immediate, tier_slug, request_details, cancel_reason, etc.) are left semantically unexplained, and JSON-string argument formats are not clarified beyond schema types.

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 role: 'official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' then details the search/describe/invoke flow and the prompt library. It clearly states what the tool does, but because it is a multi-action hub it does not explicitly draw boundaries against sibling tools like report_bug or toolkit_info.

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 guidance is explicit: 'use install only to make an MCP PERMANENT' and 'prefer invoke for a single/occasional use,' with additional direction for when to use list_tools, subscribe/cancel, report_bug, and request_mcp. It also explains what to do in credential and wallet-empty scenarios, so an agent knows when to use this tool vs 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 indicate read-only and idempotent behavior, and the description confirms these by describing a consultation of public (non-sensitive) data. It adds context about hosting and no credentials, but lacks detail on data return format or potential limitations. 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 one long sentence that covers multiple points (purpose, hosting, payment, data ownership) but lacks clear structure. It is somewhat verbose but not excessively long; however, breaking into sentences would improve 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 read-only consult tool with no output schema, it explains the general behavior well. It covers the fact that it uses pre-paid credit and that the client is data controller. However, it omits the return format, any error handling, and details on how the four parameters are used, making it incomplete for an agent expecting clear selection.

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 all four parameters are plain strings with no descriptions. The tool description mentions parameters implicitly (cpf, cnpj, im, inscricao_imovel) but does not explain their formats or business meaning. It fails to compensate for the lack of schema information.

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 consults a Certidão Negativa de Débitos from an official source, which is specific and useful. It does not explicitly differentiate from sibling tools, but the operation and target are clear.

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 does not state when to use this tool versus alternatives. The description mentions it covers official Brazilian sources, but no explicit exclusion or alternative guidance is provided. Use-case inference only.

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, idempotentHint=true, and destructiveHint=false. The description adds the nuance that the conversation array is used for reproduction, which helps understand the tool's purpose. However, it does not disclose what happens after reporting (e.g., creates a ticket, sends an email) beyond the annotations. Credits for the reproduction detail keep it at a solid 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?

Two short sentences, front-loaded with the primary action and followed by a targeted tip. Every word earns its place. Excellent structure.

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 simplicity (3 params, no output schema, no nested objects), the description is sufficient. It tells what the tool does and what the user should include. A minor improvement would be to mention the expected format of 'context' or 'message', but overall it is complete enough for an agent to use it correctly. No output schema means return values need not be 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?

With 0% schema description coverage, the description must explain all parameters. It explicitly mentions the 'conversation array' and its purpose, which clarifies that parameter. However, 'context' and 'message' are not described, leaving users to infer their meanings from the schema alone. The description adds value only for one of three parameters. Given the burden on compensating for missing schema docs, this falls short.

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.' It uses a specific verb and resource, and the distinction from siblings (authenticate, connect, etc.) is immediate. No ambiguity about 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 provides clear context on what to include ('Include the conversation array with recent messages for reproduction'), which is an explicit usage hint. However, it does not mention when not to use this tool or compare it to alternatives, but given the distinct siblings, this is acceptable. Lacks an explicit exclusion statement.

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 agent knows it's a safe, non-mutating operation. The description adds the specific information returned ('current MCP platform and adapter versions'), which is useful context beyond the annotations. No contradictions.

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, efficient sentence that conveys all necessary information. There is no filler or redundant content, making it highly concise and 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?

This is a simple, parameterless, read-only tool with rich annotations covering safety and idempotency. The description specifies what it returns, which is sufficient. No output schema exists, but the return value is straightforward. Overall, it's complete for its 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 0 parameters, and the schema is empty. The description adds meaning by clarifying what 'versions' are being shown (platform and adapter), which is helpful. With no parameters, the baseline is 4, and the description meets it.

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: 'Show the current MCP platform and adapter versions.' It uses a specific verb ('Show') and specifies the resource ('current MCP platform and adapter versions'), which distinguishes it from siblings like 'authenticate' or 'marketplace' that serve 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 usage: it's for checking versions. However, it does not explicitly state when to use it versus alternatives, nor does it mention any conditions or exclusions. Given the tool's simplicity, this is adequate but lacks explicit guidance.

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, which establishes the safety profile. The description adds meaningful behavioral detail beyond annotations by specifying the exact categories of state returned, which is useful for an agent deciding whether to call this 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?

The description is a single, well-structured sentence that front-loads the verb and resource ('Returns the current toolkit state') and then lists specific return categories. Every clause adds relevant information, with no wasted words or redundant restatement of the tool name.

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 low complexity (zero parameters, no output schema), the description provides sufficient context by naming the key return categories: installed MCPs, connection status, connected accounts, and catalog tool counts. There is no missing critical guidance for an agent to use this tool 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 tool has zero parameters, and the input schema confirms this by having an empty properties object. The description requires no parameter elaboration since there is nothing to configure; a baseline score of 4 is appropriate for a parameterless 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 the specific verb 'Returns' with a clear resource ('current toolkit state') and enumerates exactly what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from action-oriented siblings like connect, authenticate, and 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 opening phrase 'Returns the current toolkit state' establishes a clear context for when this tool should be invoked: whenever the agent needs an overview of the toolkit's MCP installations, connections, accounts, or exposed catalog tools. It does not explicitly discuss alternatives or when not to use it, so it falls 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.