Prefeitura MG Divinópolis: Certidão Negativa de Débitos

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

Annotations already indicate idempotency and non-destructive behavior; the description adds useful context about session vs. permanent authentication, the token format, and the config header approach. It does not contradict 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 target audience and purpose. It includes concrete usage instructions without unnecessary fluff, though it packs several ideas into the second sentence.

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 login flow, token handling, and link retrieval are all covered, which is sufficient for a low-complexity auth tool. There is no output schema, and the return behavior is only implied ('get the link'), but the overall context 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 schema only defines an optional string token with no description. The description explains that token is a JWT, when to pass it, and that omitting it returns the login link. This significantly compensates for the missing schema parameter description.

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 authenticates to MCP.AI for IDE agents via browser login and an access token. It distinguishes itself from sibling tools by focusing specifically on the authentication flow rather than general connectivity or marketplace functions.

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 provides two usage paths: permanent configuration via Authorization header, and session-only login by pasting a token. It also explains the calling convention for each case, including calling with no args to retrieve the login link.

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, idempotent, non-destructive behavior. The description adds valuable conditional behavior details: what the response looks like when all providers are connected (authenticated:true, empty pending[]) versus when credentials are missing (connect_url returned). This goes beyond what annotations provide, enhancing transparency.

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 remarkably concise: two sentences that front-load the primary purpose ('Returns connection status and URLs') and then succinctly elaborate on the two main scenarios. Every sentence adds value with 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 simple read-only status tool with no parameters and no output schema, the description covers the principal states (all connected vs. missing credentials). It doesn't detail every possible edge case, but the information provided is sufficient for an agent to understand when and what the tool returns.

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 there is nothing for the description to explain. With empty schema and 100% coverage, the description correctly focuses on behavior rather than parameters, earning the baseline score for parameterless tools.

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, using a specific verb and resource. It implicitly distinguishes from sibling 'authenticate' by focusing on status rather than performing authentication, though it doesn't explicitly name alternatives.

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 this is for checking connection status, with conditions like 'when all providers are connected' and 'when credentials are missing', but does not explicitly state when to use this tool over alternatives such as 'authenticate'. No direct when-to-use or when-not-to-use guidance is provided.

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 indicate readOnlyHint=false, openWorldHint=true, and destructiveHint=false; the description adds substantial behavioral detail beyond that. It discloses that invoke runs tools one-off even when not installed, does not bloat the toolkit, requires workspace owner/admin for writes, returns a connect link when credentials are missing, and returns a checkout link when payment is needed.

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 dense and well-structured: it opens with a sharp one-line definition, then walks through the core flow, key nuance (invoke vs install), permissions, billing/auth behavior, and prompt-library features. No sentence is filler; every sentence adds decision-relevant guidance for a 23-parameter, 14-action 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 highly complex tool with no output schema, the description covers the main flow, action alternatives, permission requirements, auth/payment behavior, and prompt-library usage very well. It misses minor operational details such as what `resume` does, how `immediate` interacts with invoke, and the exact effect of uninstall, but the core selection-and-invocation path is complete enough for an agent to act 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?

With 23 parameters and 0% schema description coverage, the description must compensate heavily. It does explain the central `action` values and connects `mcp_id`, `tool_id`, and `arguments` to the search/describe/invoke flow, plus several prompt_* params via the prompt-library sentence. However, many parameters—`limit`, `immediate`, `tier_slug`, `request_details`, `prompt_targets`, `cancel_reason`, and others—receive no individual semantic explanation beyond their names/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 clearly identifies the resource (mcp.ai marketplace) and its broad purpose: cataloging, discovering, and running MCPs, plus handling capability requests and prompt-library lookups. It also distinguishes itself from siblings by explaining the core search → describe → invoke flow and when install/list_tools apply.

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 each mode: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and 'request_mcp asks us to build a NEW MCP when nothing fits'. It also tells the agent what happens with auth/payment ('returns a connect link', 'returns a checkout/top-up link'), making alternative-handling 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 and idempotentHint=true. The description adds valuable operational details beyond that: payment via prepaid credit, absence of platform credentials, official-source nature, non-confidential data, and LGPD data-controller responsibility. 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 three sentences and front-loads the core purpose. It is not overly long, though the LGPD legal boilerplate adds length without directly aiding tool invocation.

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 purpose, source, payment, credentials, and data governance. However, it omits parameter semantics (which identifier to provide) and return-value behavior, and there is no output schema to compensate. Adequate for a simple query tool, but gaps remain.

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 never mentions cpf/cnpj, their relationship (e.g., one required, mutually exclusive), or formatting. The parameter names are self-explanatory to Brazilian users, but the description does not compensate for the complete lack of schema-level meaning.

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 queries a 'Certidão Negativa de Débitos' from 'Prefeitura MG Divinópolis' at an official source. The verb 'consulta' and specific resource distinguish it from generic 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 provides useful context: hosted by the platform, no platform credentials needed, prepaid credit per query. However, it does not explicitly state when to prefer this tool over alternatives or when not to use it, though the siblings are unrelated platform utilities.

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=false, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context by instructing the user to include the conversation array for reproduction, which is not captured in annotations or the 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?

Two short sentences deliver the purpose and an essential usage detail without redundancy. It is front-loaded with the action and provides critical information efficiently.

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 with no output schema and minimal parameters, the description covers the primary use case and the key reproduction detail. It could mention expected message content, but the tool's simplicity and annotation support make the description adequately 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?

The schema provides only property names and types. The description explicitly mentions the 'conversation array', linking it to reproduction, which adds meaning. However, it does not explain 'message' or 'context', and schema description coverage is 0%, so the description only partially compensates for the lack of parameter info.

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 uses specific verbs and resources, and the instruction to include the conversation array differentiates it from sibling tools like 'show_version' 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 when to use the tool (when there is a bug, missing feature, or feedback). It does not explicitly provide exclusions or alternatives, but the context is clear enough for an agent to decide when this tool is appropriate.

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 clear. The description adds no additional behavioral context beyond the purpose, but for a simple zero-parameter version query this is adequate.

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 purpose, making it concise 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?

For a zero-parameter, read-only version tool, the description is complete enough: it names the exact output domain ('platform and adapter versions'). It does not specify the return format, but with no output schema and low complexity this 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 tool has zero parameters and schema description coverage is 100%, so the schema fully describes the input surface. The description does not need to elaborate on parameters, and the empty schema makes parameter semantics trivially clear.

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.' This clearly distinguishes it from unrelated sibling tools such as authenticate, connect, 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?

There is no explicit guidance on when to use this tool versus alternatives, but the use case is naturally implied: query version information. It does not mention exclusions, prerequisites, or alternative tools, so it only meets the minimum through implication.

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. The description adds useful behavioral detail about what the returned state contains, such as connections and accounts, going 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?

A single, well-structured sentence that front-loads the verb/resource and lists all return components without filler or redundancy. Every part of the sentence adds value.

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 zero-parameter, read-only tool with strong annotations, the description fully explains what the tool returns. No output schema exists, but the enumerated contents are sufficient for an agent to decide when 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 baseline is 4. The description accurately communicates that no parameters are needed, and there is nothing additional the schema or description needs 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 uses the specific verb 'Returns' and names the exact resource 'current toolkit state,' then enumerates the contents: installed MCPs, connection status, accounts, and catalog tool counts. This clearly differentiates it from sibling tools like authenticate and 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 clearly conveys when to use the tool: to inspect the overall toolkit state. It provides clear context (what information will be retrieved) but doesn't explicitly mention when not to use it or point to alternatives.

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