SEFAZ RJ: Certidão Negativa de Débitos (Certificado Digital)

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

Annotations already declare idempotentHint=true and destructiveHint=false, and the description adds behavioral context beyond that: it explains the non-expiring nature of config-based tokens versus session-only tokens, and that calling with no args returns a link. No contradictions 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 moderately sized but well-structured with two clear usage paths. Some initial phrasing like 'MCP.AI for IDE agents (Cursor, etc.)' adds context, but could be slightly more streamlined. Each sentence contributes to explaining the authentication flow.

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 tool with one optional parameter and no output schema, the description covers the full user flow: browser login, token acquisition, permanent vs session-only options, and how to invoke the tool. It lacks explicit error scenarios, but is otherwise complete for the tool's scope.

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 shows an optional 'token' string with no description, and coverage is 0%. The description compensates thoroughly by explaining the token is a JWT, how to use it with { token: "<jwt>" }, and that omitting it retrieves the login link. This fully clarifies parameter 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 the tool's purpose: authenticating to MCP.AI for IDE agents by logging in via browser and copying an access token. It distinguishes itself from sibling tools like 'connect' by focusing specifically on authentication flow and token handling.

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 approaches: adding the token to the server config for a permanent connection, or pasting it for a session-only login. It also explains when to call with no arguments to get the login 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, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds value by explaining the return behavior in different scenarios (all providers connected vs. missing credentials), including the structure of the response (authenticated, pending, connect_url). This goes beyond what annotations provide and gives actionable insight into expected outputs.

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 exceptionally concise, consisting of two sentences. It front-loads the primary purpose in the first sentence and provides the key behavioral variations in the second. Every word adds value, with no fluff or repetition. This is a model of efficient communication.

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) and the robust annotations, the description is largely complete. It covers the two main response states, but it does not address partial connectivity scenarios (e.g., some providers connected, others not). However, such details are likely inferred from the 'all providers' phrasing. The description sufficiently equips the agent to understand the tool's output for typical use cases.

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 for this dimension is 4 per the rubric. The description does not need to explain parameter semantics since there are none. The complete schema coverage of 100% is trivial because the schema is empty, and the description appropriately focuses on the response behavior.

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: 'Returns connection status and URLs.' It specifies the resource (connection status) and the action (returns). It distinguishes from siblings like authenticate (which presumably performs authentication) and show_version (which reports version). The two response states are explicitly described, leaving no ambiguity about the tool's function.

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 implicitly indicates this is a read-only status check, which naturally suggests it is for verifying connectivity before other operations. However, it does not explicitly state when to use it versus alternatives (e.g., authenticate). No exclusions or alternatives are mentioned, so it falls short of a 5 but provides clear context for typical usage.

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?

Even though annotations are minimal (readOnlyHint=false, destructiveHint=false), the description discloses critical behavioral details: invoke runs tools without permanently installing them; install makes MCPs permanent; credential requirements trigger connect links; payments may require wallet top-up; and search/describe flag installed_in_toolkit vs installed_in_workspace. This goes well 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 long but intentionally dense, covering an unusually complex tool with many actions, subfeatures, and caveats. It is organized logically: summary → core flow → key caveats → permission/authentication → prompt library feature. Every sentence adds unique value, though the length might challenge quick scanning.

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, no output schema, and weak annotations, the description is remarkably complete: it covers core actions, edge cases (connect links, checkout links), permission requirements, and a nested prompt-library feature. Some gaps remain: it doesn't list every action in the schema (e.g., 'resume', 'list_tools' is mentioned but not fully bound to action values), and it doesn't explain the response format or retry logic in more detail.

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 coverage and 23 parameters, the description does heavy lifting by explaining the 'action' parameter values (search, describe, install, uninstall, subscribe, cancel, resume, list_tools, search_prompts, get_prompt, publish_prompt) and the purpose of prompt-related parameters (prompt_body, prompt_slug, prompt_vars, prompt_tool, prompt_title, prompt_category, prompt_targets). However, many parameter meanings (e.g., conversation, request_details, report_context, immediate, tier_slug) are only implicitly covered. No parameter syntax details are provided, but the description gives enough high-level meaning for an agent to infer usage.

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, encompassing catalog search, MCP execution via invoke, installation, subscription management, and prompt library access. It uses specific verbs (search, describe, invoke, install, list_tools) and distinguishes itself from generic 'marketplace' sibling tools by explaining its unique scope.

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 when-to-use guidance: use invoke for one-off tasks, install for permanent toolkit additions, list_tools to see callable tools, request_mcp for new MCPs, and the prompt library functions for prompt text. It also clarifies the flow for auth (connect link) and payment (checkout/top-up link) and notes that writes require owner/admin access.

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 context about including the conversation array for reproduction, which is beyond what annotations provide. It does not mention side effects, rate limits, or idempotency, but annotations already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description doesn't contradict annotations and modestly supplements 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 core purpose and immediately followed by a practical usage note. There is no fluff, redundant wording, or unnecessary detail. 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 simplicity of the tool (3 string parameters, no nested objects, no output schema), the description covers the essential aspects: what it does and what to include. It lacks explanation of 'context' and potential return values, but for a simple tool with decent annotations, this is adequate. It could be slightly richer by clarifying all parameters.

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 compensate. It explains the 'conversation' parameter by saying 'Include the conversation array with recent messages for reproduction.' However, it does not clarify the meaning of 'context' or add detail to 'message' beyond its obvious role as the report content. Partial compensation, but incomplete for all 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.' This is a specific verb-action-resource combination that unambiguously indicates the tool's function. It also naturally distinguishes itself from sibling tools (auth, version, etc.) which 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 provides a concrete usage instruction: 'Include the conversation array with recent messages for reproduction.' This guides the agent on how to invoke the tool correctly. However, it does not explicitly state when to use this tool versus alternatives, though no direct alternatives appear among siblings. The lack of explicit 'when to use / when not to use' diminishes the score.

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 annotation, the description discloses that the operation is a query, requires prepaid credits, does not need platform credentials, and involves data privacy responsibilities under LGPD. It also clarifies that the data is not confidential, adding transparency about the data handling.

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 somewhat verbose and repetitive, repeating the same ideas about official sources, LGPD, and payment. While it is not excessively long, it could be more concise by removing redundant phrases and focusing on essential facts.

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 provides good context about the purpose, payment, and data privacy, but it omits details about expected output format and parameter usage. Given the lack of an output schema and parameter explanations, the description is not fully complete for a user to understand how to invoke the tool 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 schema has four parameters (ie, cnpj, pkcs12_cert, pkcs12_pass) with no descriptions, and the tool description does not explain any of them. The mention of 'Certificado Digital' hints at the certificate parameters but does not map them clearly, leaving parameter semantics completely 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 states that this tool consults a negative debt certificate (Certidão Negativa de Débitos) from SEFAZ RJ using a digital certificate. It explicitly mentions the source as official and distinguishes it from generic 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 lacks explicit guidance on when to use this tool versus alternatives. It mentions payment and lack of credentials but does not specify scenarios where this tool is preferred or required over other methods.

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 specify readOnlyHint, idempotentHint, and destructiveHint, providing the safety profile. The description adds no extra behavioral context beyond what the name implies. This aligns with the baseline where annotations exist; there is no contradiction, but the description could have mentioned that no authentication is required or that it performs a network call, though none is necessary.

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 sentence, directly front-loaded with the action and object, with no unnecessary words. 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?

For a parameterless, stateless tool with no output schema, the description is entirely sufficient. It fully explains what the tool does and what the agent can expect (version information). No gaps exist.

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, the schema is complete and the description need not explain parameters. The baseline of 4 applies as per the rubric for zero-parameter tools, and the description adds no irrelevant or missing 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 'Show the current MCP platform and adapter versions' uses a specific verb ('show') and resource ('MCP platform and adapter versions'), clearly distinguishing it from siblings like 'toolkit_info' which might have broader scope. It unambiguously states the tool's function.

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 when an agent needs current version information, which is clear from context. No alternatives are mentioned, but none are needed for a simple version query. The main gap is not explicitly stating when *not* to use it (e.g., if another tool also reports versions), but this feels minor given the tool's specificity.

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, and the description aligns perfectly. It adds behavioral context beyond the annotations by specifying the detailed contents of the returned toolkit state (installed MCPs, connection status, accounts, tool counts), giving the agent a concrete idea of what to expect.

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 core purpose and uses a clear list to enumerate the returned state components. Every phrase earns its place 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 sufficiently complete. It names the key return categories (installed MCPs, connection status, connected accounts, catalog tool count) so an agent knows what to expect without needing a separate output schema.

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 description carries no parameter documentation burden. With an empty input schema and 100% schema description coverage, there is nothing for the description to add about parameter semantics; baseline 4 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 uses a specific verb ('Returns') and clearly enumerates the exact resource and content: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like show_version or report_bug by specifying exactly what toolkit state is covered.

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 no explicit guidance on when to use this tool versus alternatives. It implies a status-checking role but does not state when to prefer it over show_version or other sibling tools, nor does it mention any exclusions or prerequisites.

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