Prefeitura RJ Rio de Janeiro: Certidão Negativa de Débitos

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

Beyond the annotations, it explains the auth flow: browser login, token copying, session-only token acceptance, and no-args behavior returning a link. It does not detail expected outputs or failure modes, but the main behavioral characteristics are transparent and consistent 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 front-loaded with context and contains necessary operational details, but it is slightly run-on and mixes configuration advice with tool-invocation instructions. Still, every sentence contributes useful information.

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 one-parameter auth tool with no output schema, the description covers invocation modes, token semantics, and the relationship to permanent configuration. It is complete enough for an agent to know exactly how to use the tool.

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 only defines 'token' as an optional string with 0% description coverage, but the description fully compensates by explaining the token is a JWT for session-only login and that omitting it returns an auth link. This is more than sufficient for the single parameter.

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 via a browser-obtained access token, with explicit call patterns for passing a token or getting a link. It differentiates itself from permanent config-based auth by describing the session-only flow.

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 explicitly contrasts the recommended permanent approach (adding an Authorization header to config) with this tool's session-only login, and specifies when to call with or without the token argument. This gives clear guidance on when to use the tool vs. an alternative setup.

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 mark this as read-only and idempotent. The description adds value by disclosing the exact return states: authenticated:true with empty pending[] when all connected, and connect_url plus per-install URLs when credentials missing. This goes beyond the annotation coverage.

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 the core purpose, followed by conditional details. 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?

For a zero-parameter status tool with annotations, the description explains the primary outcomes and return values in both main scenarios. It is sufficiently complete given the tool's 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?

No parameters exist, so the schema covers everything. The description's reference to connection states is consistent with the empty schema, and the baseline for 0-param tools is 4.

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' paired with the resource 'connection status and URLs,' and distinguishes this from sibling tools like 'authenticate' by focusing on status rather than action. The conditional behavior clarifies what the tool reports.

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 the tool to check if all providers are connected and obtain URLs when credentials are missing. It provides clear contextual conditions but does not explicitly compare to 'authenticate' or other siblings, so it falls short of a full when/when-not 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?

The description adds significant behavioral context beyond the annotations: it requires workspace owner/admin for writes (install/uninstall/subscribe/cancel), explains that invoke works even when an MCP is not installed, and details the handling of missing credentials (connect link) and empty wallet (checkout link). This is substantial extra info that the agent needs. No contradiction with the annotations (readOnlyHint=false, openWorldHint=true, etc.) is present.

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 of about 200 words. It is front-loaded with a clear purpose statement, then explains the core flow and key distinctions. While it packs a lot of useful information, it could be structured with headings or bullet points for easier scanning, but it remains appropriately sized for the tool's complexity and avoids redundancy.

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 23 parameters and complex behavior, the description covers the essential operations (search, describe, invoke, install, list_tools, prompt library), auth requirements, and edge cases like connect and checkout links. It does not have an output schema, so no return values are mandated. It provides sufficient context for an agent to make informed decisions in most scenarios, though it leaves some parameter details unexplored.

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 has 0% coverage from the description (no parameters are explicitly described). The description compensates partially by explaining the core flow and naming key parameters like action, mcp_id, tool_id, and prompt-related fields through examples (e.g., 'action=search', 'invoke RUNS that tool', 'search_prompts finds one'). However, it does not systematically document all 23 parameters, leaving many (limit, immediate, tier_slug, conversation, etc.) unaddressed. It gives enough for the main use cases but not full 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 identifies the tool as the official mcp.ai marketplace, covering both discovery and execution of MCPs. It states the core flow (search, describe, invoke) and explicitly distinguishes its purpose from sibling tools like authenticate and connect by framing it as the catalog and runner. The verb+resource structure is evident: it is the way to find and run MCPs.

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 different actions: 'prefer invoke for a single/occasional use' versus 'use install only to make an MCP PERMANENT', and clarifies that list_tools shows what is callable now. It also explains when to use the prompt library actions. This directly helps an agent select the appropriate action within the 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 readOnlyHint and idempotentHint annotations, the description adds critical behavioral details: it incurs prepaid credit charges, accesses official non-confidential data, and clarifies the client's LGPD data control responsibilities. These go well beyond the annotation and provide valuable operational context.

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 paragraph with a clear opening stating the purpose. It includes some redundancy (repeating 'official sources' twice) but overall remains concise and front-loaded. Minor waste but generally efficient.

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 the core purpose, payment model, and data source nature, but omits parameter explanations and any indication of the response format. With no output schema, the agent lacks guidance on what the tool returns. This is a notable gap for a simple query tool.

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 defines two required parameters (email and inscricao_municipal) with zero description coverage. The description does not explain what these parameters mean, their expected formats, or their role in the query. For a Brazilian-specific tool, this is a significant gap that leaves the agent guessing.

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 performs a query (consulta) for a negative debt certificate (Certidão Negativa de Débitos) from the Municipality of Rio de Janeiro, using official sources. This specific verb+resource combination distinguishes it from unrelated 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?

The description provides context that it is hosted on the platform, requires prepaid credits, and does not require platform credentials, which implies when it should be used. Although it doesn't explicitly compare with alternatives, the siblings are generic and unrelated, so the context is sufficient for usage 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 indicate idempotentHint=true and readOnlyHint=false, but the description doesn't contradict these. It adds that the tool sends feedback, implying a write operation, but not explicitly stating it. With annotations present, the bar is lower; however, the description doesn't disclose what happens after submission (e.g., confirmation, async processing), so it adds minimal value 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, with two sentences that front-load the main purpose and then provide a key usage hint. It is appropriately sized for its simplicity, though it could be more structured with bullet points for parameter guidance, but it is not overly 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?

Given the tool has 3 parameters and no output schema, the description provides the essential purpose and a hint about conversation usage, but lacks detail on parameter formats or expected behavior (e.g., what constitutes 'recent messages', whether context is optional). The tool is simple, so the description meets the minimum viable level but could be more 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%, but the description mentions the conversation array and its purpose (reproduction). It also notes to include recent messages, adding some meaning to the conversation parameter. However, it doesn't explain the 'context' parameter or elaborate on the 'message' parameter beyond the schema. With 3 parameters, the description partially compensates but not fully.

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 is for reporting bugs, missing features, or sending feedback, which distinguishes it from siblings like marketplace or show_version. However, it doesn't explicitly name the sibling tools it competes with, but the purpose is clear enough.

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 a directive to include the conversation array for reproduction, which implies when it should be used (when reporting an issue) but offers no guidance on when not to use it or alternatives. Given the sibling tools are unrelated (auth, marketplace, etc.), the description doesn't need to differentiate much, but it lacks explicit context.

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 safety traits are covered. The description adds that it shows platform and adapter versions, which is self-explanatory. No additional behavioral context is needed for such a trivial read-only tool, so a 3 is suitable.

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 concise sentence that is front-loaded with the action and resource. It contains no filler or redundant information. Perfectly sized for such 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 has zero parameters, no output schema, and simple annotations, the description is complete. The tool is trivial – it just displays version info. Nothing else is needed.

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 schema is empty. Per the rules, 0 params = baseline 4. The description does not add any parameter info, but since there are no parameters to explain, the 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 that the tool shows the current MCP platform and adapter versions. It uses a specific verb 'show' with a clear resource ('current MCP platform and adapter versions'), which is distinct from the sibling tools like '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?

The description implies that the tool should be used when the user wants to know the versions of the platform and adapter. However, it does not explicitly mention when to use it vs alternatives, though the purpose is straightforward and no alternates are needed for version information. Given the simplicity, a baseline of 3 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, covering the safety profile. The description adds meaningful context by detailing the return content (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations and clarifies the tool's behavioral output.

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, concise sentence that is front-loaded with the purpose ('Returns the current toolkit state') and followed by a clear list of what that state includes. No wasted words or redundant information.

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, no output schema), the description is nearly complete. It specifies the key aspects of the return value, though it does not mention potential formatting, pagination, or any edge cases. Still, for a straightforward state-inspection tool, the coverage 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, so the input schema provides no semantic information. With 0 parameters, the baseline is 4, and the description correctly does not attempt to describe non-existent 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 function with a specific verb ('Returns') and resource ('current toolkit state'), and enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like show_version, which likely only reports version 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?

The description implies the tool is used to inspect the toolkit's current state, but does not explicitly state when to use it versus alternatives. No exclusions or prerequisites are mentioned, leaving the usage context implied rather than explicit.

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