Prefeitura SP Mogi das Cruzes: Certidão Negativa de Débitos

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

Annotations indicate readOnlyHint:false, idempotentHint:true, destructiveHint:false, but the description adds essential behavioral context: it clarifies that the tool is non-destructive and idempotent (can be called multiple times to get the link), and that it does not mutate state permanently unless a token is pasted, which is a session-only side effect. It also explains the permanent vs. session distinction, which the annotations do not capture.

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 for the complexity it covers, with a clear flow: it starts with the target audience, then the recommended permanent method, then the session-only fallback. Each sentence serves a purpose, and it is front-loaded with the primary action, making it easy for an agent to parse quickly.

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 has one optional parameter, no output schema, and the annotations are sparse, the description is remarkably complete. It covers the two invocation modes, the authentication flow, and the configuration alternative. This is more than sufficient for an agent to correctly select and invoke the tool without additional 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 schema has only one optional 'token' parameter with 0% description coverage, so the description must carry the full burden. It explains that token is a JWT string the user pastes from the browser, and that omitting it triggers a link generation. This adds semantic meaning beyond the mere property name, fully compensating for the schema's lack of 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 identifies the tool's purpose as the authentication entry point for IDE agents, spelling out the verb 'log in' and the resource 'access token'. It distinguishes itself from siblings like 'connect' by explicitly targeting IDE agents and describing the login flow, which is unique among the sibling list.

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 when-to-use and how-to-use guidance: it explains the recommended permanent configuration via a header, versus the session-only paste flow. It also instructs the agent on when to call with no args (to get the link) versus with a token, which is critical for correct invocation.

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 readOnlyHint and idempotentHint annotations, the description discloses the exact conditional behavior: successful connection returns authenticated:true and empty pending[], while missing credentials produce connect_url and per-install URLs. This adds meaningful behavioral context without contradicting 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, front-loaded with the core purpose, and each sentence adds concrete detail about conditional outcomes. There is 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, zero-parameter, read-only status tool with no output schema, the description sufficiently explains return values in both relevant scenarios. Annotations cover safety and idempotency, and the description completes the behavioral picture.

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 and the schema coverage is 100%, so there is no parameter information needed. The description focuses on outputs, which is appropriate for a zero-parameter 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 clearly states the tool returns connection status and URLs, with specific conditional outcomes ('authenticated:true and empty pending[]' vs 'connect_url'). This distinguishes it from sibling tools like authenticate, which implies initiating a connection rather than reporting status.

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 the tool is used to check whether all providers are connected and to retrieve connection URLs when credentials are missing. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for a zero-parameter status 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?

Beyond the sparse annotations, the description reveals critical behaviors: invoke runs tools without installing or bloating the toolkit, auth failures return a connect link, empty wallets return a checkout link, writes require workspace owner/admin, and the prompt library share links work without login. This is rich and non-contradictory with 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 dense but front-loaded with the core purpose and workflow. Every sentence contributes useful information, though the single-paragraph structure makes the many actions and sub-features harder to scan than a bulleted breakdown would be.

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 is impressively complete on core workflows, auth, billing, and the prompt library. However, the 'resume' action is never mentioned, and several parameter-specific behaviors such as immediate and tier_slug remain unaddressed.

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 meaning burden. It explains the role of action, tool_id, and prompt-related parameters at a high level, but leaves many other parameters (limit, query, message, immediate, tier_slug, cancel_reason, report_context, request_details, prompt_targets, etc.) unexplained.

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 and runtime, with a concrete workflow: search to discover, describe to inspect, invoke to run. It explicitly distinguishes this hub-style tool from siblings by covering catalog lookup, execution, billing, and prompt-library actions in one place.

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: prefer invoke for one-off use, use install only to make an MCP permanent, use list_tools for what is callable now, and use request_mcp when nothing fits. It also outlines the search→describe→invoke flow and explains when connect/checkout links will appear.

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, destructiveHint=false, idempotentHint=true. The description adds valuable context beyond annotations: payment via prepaid credit, no platform credentials, LGPD data controller responsibility, and clarification that data is not confidential. This enriches behavioral understanding without 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 compact—three sentences that front-load the core purpose and then add essential operational details. It avoids redundancy and stays focused, though it could be slightly more structured by separating legal info.

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 three optional parameters, the description omits return format or content details and provides no parameter guidance. It covers payment, credentials, and legal aspects, but misses operational specifics needed for a complete usage understanding.

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 does not mention any of the three parameters (ccm, cpf, cnpj) or explain their formats, usage, or selection criteria. Since coverage is low, the description must compensate but fails to provide any guidance on 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 clearly specifies the action (consulta) and resource (Certidão Negativa de Débitos) for a specific municipality (Mogi das Cruzes). It distinguishes from unrelated siblings by naming the official source and domain, making the tool's purpose 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 provides concrete usage conditions: no platform credentials required, requires prepaid credit for payment, and states the tool accesses official Brazilian sources available to citizens. While it doesn't explicitly compare to alternatives, siblings are unrelated, so this context is sufficient for when to use it.

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 idempotentHint=true and destructiveHint=false. The description adds context that conversation data should be included for reproduction, implying that the report will be used for debugging. It does not elaborate on side effects like data transmission or whether a confirmation/ticket is returned, but the annotation coverage lowers the burden. 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 entire description is two sentences. It opens with the primary purpose and follows with a specific usage requirement. No filler or redundant details; every word contributes.

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 relatively simple with three parameters and no output schema. The description covers the main scenario (reporting an issue), identifies the required message field, and provides guidance on the conversation field. It doesn't mention return values or confirmations, but that's not critical for a bug-report tool. Annotations add safety context, making it reasonably 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 has 0% description coverage, so the description must compensate. It explicitly instructs to include the 'conversation' parameter with recent messages, giving it purpose. The 'message' parameter is implicitly described as the text of the bug/feedback. 'context' is not explained, but its name and default suggest it's optional contextual data. Overall, partial compensation for a low-coverage 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 specifies the tool's function with a clear verb ('Report') and resource ('a bug, missing feature, or send feedback'). It distinguishes this tool from siblings like authenticate or show_version, none of which handle bug reporting. It also hints at the required parameter (message) as the content of the report.

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 identifies when to use the tool: when there's a bug, missing feature, or feedback to submit. It does not explicitly mention alternatives or exclusions, but the sibling tools are unrelated, so the context is sufficient. However, it lacks explicit guidance on when not to use it, such as for general queries or non-technical issues.

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 annotations (read-only, idempotent, non-destructive) by using 'Show', which implies no side effects. It adds context by specifying what is shown (platform and adapter versions), beyond what annotations provide, though it does not mention any additional behavioral details like network calls or caching.

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, clear sentence with no unnecessary words. It is well-structured and directly conveys the tool's function.

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 (no parameters, read-only operation, no output schema), the description fully covers what the tool does. There is no need for further elaboration on return values or side effects.

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 schema coverage is 100% and the baseline score applies. The description does not need to explain parameter semantics, and it provides no additional parameter-related 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 the action (Show) and the resource (MCP platform and adapter versions), making the tool's purpose unambiguous. It is easily distinguished from sibling tools like authenticate, connect, or report_bug, which serve different 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 does not explicitly state when to use this tool versus alternatives, but the purpose is simple enough that an agent would infer usage when version information is needed. No explicit conditions or exclusions are provided, so guidance is implied rather than stated.

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 valuable detail about exactly what state is returned (installed MCPs, statuses, accounts, catalog tool counts). This goes beyond the annotations without contradicting them, although it doesn't mention rate limits or side effects (not needed for a read-only 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, well-structured sentence that front-loads the verb 'Returns' and then lists the key components of the state. Every element adds value and there is no 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 zero-parameter read-only status tool, the description fully covers what the agent needs to know: what the tool does and what information it provides. It's complete for its purpose and leaves no obvious gaps for the expected use case.

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 and 100% schema coverage (trivially), the description doesn't need to explain any parameters. The baseline for 0 parameters is 4, and the description provides no param-specific info, which 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 action ('Returns the current toolkit state') and the specific resource (installed MCPs, connection status, connected accounts, catalog tool counts). This distinguishes it from sibling tools like 'connect' or 'authenticate', which are action-oriented, while this is a read-only status/inspection tool.

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 makes it obvious it's for retrieving state and not for taking actions, giving clear context for when to use it. It doesn't explicitly name alternatives, but for a simple status tool, that's not necessary. No exclusions are stated, but the purpose is self-evident.

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