Prefeitura MT Rondonópolis: Certidão Negativa de Débitos

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

The description explains that with no args it returns a link, and with token it performs a session login. It does not explicitly state the behavior when called with a token (e.g., whether it validates or stores it), but the annotations (readOnlyHint false, idempotentHint true) align with the notion of a non-destructive authentication side effect. The permanent config alternative is described, but the tool's own behavior is somewhat implicit. Still, it provides useful context 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 a bit long and mentions configuration details (adding header to server config) that are tangential to the tool itself. However, it's structured logically: first says what it does, then best practice, then how to call. It could be tightened but is not verbose.

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 single-parameter authentication tool with no output schema, the description covers the workflow, arguments, and usage scenarios. It tells the agent exactly what to do: get the link, present it to the user, and then call with the token. This is complete for its 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?

Schema coverage is 0%, but the description thoroughly explains the token parameter: it's a JWT that the user pastes, and calling without it yields the auth link. This adds meaning that the schema lacks entirely.

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 explains the tool's purpose: authentication for MCP.AI in IDE agents. It specifies the exact flow (browser login, copy token, call with token or no args to get link) and distinguishes between permanent (config header) and session-based (token argument) usage. This is a specific, actionable purpose statement.

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?

Provides step-by-step instructions for both authentication modes: configuring an Authorization header for permanent connection, or calling the tool with a token for session-only login, or with no args to get the login link. Clearly states when to use which approach, which is excellent 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?

Adds conditional output details (authenticated:true vs connect_url) beyond the readOnly and idempotent annotations, fully describing behavior.

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 clear sentences convey all necessary information 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?

Given no parameters and no output schema, the description fully explains the return values and conditions, making it 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?

No parameters exist; schema coverage is trivially 100%, so baseline 3 applies without needing param descriptions.

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?

Clearly states the tool returns connection status and URLs, distinguishing it from sibling tools like authenticate or 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?

Implies usage for checking connection status, but does not explicitly state when to prefer this over alternatives or provide exclusions.

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 annotations, the description discloses important runtime behavior: invoke works even when the MCP is not installed, credentials produce a connect link, empty wallet produces a checkout link, and write actions require workspace owner/admin. It also flags installed_in_toolkit vs installed_in_workspace. There is 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 long and dense, but the length is justified for a complex multi-action tool with 14 action enum values. It is front-loaded with the core flow and key invoke behavior. A cleaner structure with bullets or separate sections would improve scannability, but every sentence contributes operational 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?

Given the absence of an output schema and the high complexity, the description covers the main return behaviors (profile from describe, connect/checkout links from invoke, shareable link from publish_prompt) and the auth model. Yet it omits explicit return/behavior details for some actions like search results, list_tools output, report_bug, and resume, so it is not fully 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?

With 0% schema description coverage, the description compensates by explaining the semantics of the main action field and the search/describe/invoke install flow, plus tool_id and arguments for invoking. It also explains prompt_* parameters and billing-related actions. However, it does not cover every parameter (e.g., resume, immediate, cancel_reason, conversation, report_context), leaving some gaps for a 23-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 identifies the tool as the mcp.ai marketplace: a catalog of MCPs/tools plus a runtime for invoking them. It names the core flow (search → describe → invoke), covers capability requests, and distinguishes the prompt-library sub-feature. This goes well beyond the tool name and cannot be confused with 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 gives explicit usage direction: prefer invoke for occasional use, use install only for permanent toolkit additions, use list_tools for currently callable tools, and use request_mcp when nothing fits. It also clearly separates prompt-library actions from MCP actions. This is strong when-to-use guidance with named 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?

The annotations already declare readOnly, idempotent, non-destructive. The description adds valuable context beyond that: it mentions the service is hosted on the platform, requires payment with pre-created credits, does not require platform credentials, and clarifies that the data is not confidential and falls under LGPD responsibility. These details help the agent anticipate side-effects (cost) and obligations, which the annotations alone do not provide.

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 long sentence that packs the purpose, payment, and legal obligations into one block. It is somewhat dense but avoids unnecessary fluff. The information is front-loaded with the core purpose, but the LGPD sentence at the end might be considered extra. It is not overlong, but lacks structure (e.g., bullet points or separate paragraphs) which could 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?

Given there is no output schema and only 3 parameters, the description is incomplete. It does not explain the expected invocation pattern (which parameters to provide or in what combos), the meaning of 'preferencia_emissao', or what output/response to expect (PDF, certificate code, etc.). It also does not state any error conditions or limitations. The tool is essentially underspecified for successful use.

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 input schema lists three parameters (cpf, cnpj, preferencia_emissao) with zero schema descriptions and 0% coverage. The tool description does not mention any of these parameters, their formats, semantics, or relationships (e.g., whether CPF and CNPJ are alternatives or required together, or what 'preferencia_emissao' refers to). This forces the agent to guess, which is a severe gap.

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 with a specific verb ('consultar' i.e., query) and resource ('Certidão Negativa de Débitos' from Prefeitura de Rondonópolis). It is distinct from the sibling tools which are all platform-level operations (authenticate, connect, etc.), so the purpose is unambiguous and easily differentiated.

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 for querying official public data on negative debt certificates, but does not explicitly state when to use it versus any alternatives (though none exist among siblings). The mention of 'the same source available to citizens' gives context that this is a public data lookup, but there is no clear exclusion or comparison against other querying tools.

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 behavioral context beyond the annotations by instructing to include the conversation array for reproduction, but it does not mention side effects (e.g., whether a bug report is created, email sent) or any rate limits. The annotations (idempotentHint: true, destructiveHint: false) are minimal but not contradicted.

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 clear sentences with no unnecessary fluff. It efficiently conveys the purpose and a key usage requirement.

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 feedback tool, the description covers the essential context: what it does and what to include. It does not detail output or post-submission behavior, but given the tool's straightforward nature, 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 description explains the purpose of the 'conversation' parameter ('with recent messages for reproduction') but does not clarify 'message' or 'context.' With schema description coverage at 0%, the description only partially compensates for three parameters.

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 ('Report') and identifies the resource (feedback submission), 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?

The description implies when to use the tool (when a bug or feedback is needed) and provides a specific usage instruction ('Include the conversation array...'). However, it does not explicitly mention when not to use it or alternative tools, so it's slightly below perfect.

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 this is a safe read operation. The description adds no additional behavioral context beyond what annotations provide. It doesn't mention any potential side effects or prerequisites, but for a version query, the annotations are sufficient.

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 sentence with no fluff. It is front-loaded with the verb 'Show' and immediately identifies what is shown. Every word 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 that this is a simple version query with no parameters and a straightforward purpose, the description is complete. It doesn't need to explain return values because the output is self-evident (versions). The annotations cover safety, and there is no complexity to address.

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?

There are 0 parameters, and the schema coverage is 100%. The description provides a baseline score of 4 since there are no parameters to document. The description effectively communicates that the tool requires no input, which is consistent with the 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 clearly states the tool's purpose: it shows current versions of the MCP platform and adapters. It uses a specific verb ('Show') and a specific resource ('current MCP platform and adapter versions'). While it doesn't explicitly distinguish from siblings, the purpose is unambiguous and distinct enough given the sibling names.

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 this tool: when you need version information. However, it doesn't provide explicit guidance on when not to use it or mention any alternatives. Given that siblings include 'toolkit_info' and 'marketplace', a note on how this differs from 'toolkit_info' could add value, but the context is clear enough for a simple info 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, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful context by enumerating what the returned state includes, which goes beyond the annotations. It does not disclose potential caveats like data freshness or authentication prerequisites, but for a read-only status tool this is sufficient.

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, then lists the key output components. Every part 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 zero-parameter, read-only status tool with no output schema, the description is complete: it states the purpose and the categories of information returned. There are no hidden inputs or complex behaviors that would require further explanation.

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 coverage is 100%, so there is no parameter documentation burden. The description appropriately focuses on the output rather than inputs, matching the baseline 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 a specific verb ('Returns') and clearly identifies the resource ('current toolkit state') and the exact contents returned: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from siblings like show_version, connect, and 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 that this tool is for inspecting toolkit state, but it does not explicitly state when to use it over alternatives or when not to use it. There is no mention of sibling tools or exclusions, so the guidance is only implicit.

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