SEFAZ RN: Certidão Negativa de Débitos

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

The description discloses key behavioral traits: calling with no args retrieves a link, and calling with a token performs a session-only login. It adds context about permanent vs. session-based auth. Annotations already indicate idempotency and non-readOnly behavior, and the description is consistent. However, it does not explain error handling, return values on success/failure, or whether the tool modifies server state beyond session establishment.

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 longer than necessary and mixes instructions for humans (log into browser, copy token) with agent-facing usage. It is structured in three sentences and front-loads the authentication purpose, but it could be tightened to avoid redundant or confusing phrasing. It earns a mid-range score because every sentence adds some value but it is not maximally concise.

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 no output schema and no annotations describing return behavior, the description partially covers what to expect (e.g., 'get the link' when called with no args). However, it does not specify what a successful token acceptance returns, whether errors are surfaced, or the exact format of the login link. It is adequate but incomplete for an interactive authentication flow.

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 'token' as a string with no description. The description compensates by clarifying that the token is a JWT, that it is optional, and that calling without it returns a login link. This adds meaningful semantic information beyond the raw schema, especially important given 0% schema description coverage.

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 indicates the tool's purpose: to authenticate IDE agents (like Cursor) to the MCP server. It explains the two primary modes (providing a token or requesting a login link) and distinguishes from siblings by focusing on authentication rather than other features. While it is a bit verbose and includes instructions for humans, the core action is unmistakable.

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 practical guidance on how to use the tool: call with { token } after pasting, or with no args to get a login link. It also mentions a preferred alternative (adding a header to the server config) for a permanent connection. However, it does not explicitly compare to sibling tools like 'connect' or state when NOT to use this tool, leaving some room for ambiguity.

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, destructiveHint=false. The description adds valuable context: it specifies response fields (authenticated, pending, connect_url) and behavior in different states. This exceeds the annotation-only information.

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 each sentence adds a distinct behavioral detail. No wasted words.

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 is a simple status checker with no parameters and annotations already declare safety traits, the description covers the key states and response elements. It does not list all possible response fields exhaustively, but for this simplicity it is sufficiently 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 tool has zero parameters, so the description carries no parameter burden. The schema coverage is 100% (vacuous). The description explains the return states sufficiently, so the baseline of 4 is appropriate because no parameters exist 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 states the tool returns connection status and URLs, with specific details about the conditions (all providers connected vs. missing credentials). This clearly distinguishes it from siblings like authenticate (which likely initiates connection) and show_version (which shows 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 explains the two states (connected vs. missing credentials) but does not explicitly say when to use this instead of authenticate or other tools. However, given the readOnlyHint and simple nature, the usage context is implied for checking connection status.

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 generic annotations (readOnlyHint false, destructiveHint false), the description explains that write operations need owner/admin, invoke can return connect or checkout links, install behind invoke is one-off and does not bloat the toolkit, and search/describe flags installed vs. not installed. These details materially improve an agent's ability to anticipate side effects and next steps.

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 packed with substantive, non-redundant information for an extremely broad tool. It front-loads the identity and core search→describe→invoke flow first, then addresses permissions and bigger detail. It lacks visual structure or bullets, though the paragraphs are each focused on a coherent theme.

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 large 23-parameter/action-based tool with no output schema, an agent gets a lot of context: user intent examples, one-off vs permanent execution, auth/billing side effects, writes requiring owner/admin, and prompt library differences. It is missing explicit mention of the 'resume' action/param and does not fully describe either search/describe output format or all param values.

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 significantly clarifies the key 'action' parameter and the core flow for search/describe/invoke, plus the meaning of prompt-related variables. However, it does not explain the purpose or constraints of many other schema parameters (e.g., limit, immediate, tier_slug, cancel_reason, prompt_description), and the schema has 0% description coverage, leaving a large semantic gap for such as 23-parameter surface.

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 is explicit about the tool's role: it is the official marketplace catalog of MCPs/tools, but also the mechanism to run them interactively. It clearly differentiates the main workflows (search, describe, invoke), temporary vs. permanent use, and the separate prompt library, so there is little ambiguity about what this tool does.

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 strong selection guidance: use search to discover MCPs, describe to get full profile, invoke to run one-off even without install, and install only for permanent inclusion. It also distinguishes list_tools for currently callable tools, report_bug for feedback, request_mcp for new library needs, and subscribe/cancel for billing. This is better than most 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 annotations already declare idempotentHint=true and destructiveHint=false, so the description does not need to repeat safety traits. It adds the context that the conversation array is needed for reproduction, which is useful behavioral guidance, but it does not explain what side effects occur when a report is submitted. 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?

Two short sentences deliver the purpose and the key usage instruction without any wasted words. The description is front-loaded and immediately understandable.

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 simple (3 flat parameters, no output schema), so the description need not be lengthy. However, with zero parameter descriptions in the schema, the two sentences do not fully cover what 'context' and 'message' should contain. The description is adequate for a human but leaves an AI agent guessing about required content.

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%, so the description must compensate for all three parameters. It only explains the purpose of 'conversation' (reproduction) and leaves 'message' and 'context' undefined, forcing the agent to guess what content belongs in each field. This is a significant gap for a simple but loosely specified input 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 uses a specific verb ('Report') with a clear resource ('a bug, missing feature, or send feedback'), which distinguishes it from the unrelated sibling tools. There is no tautology or ambiguity about what action is performed.

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 implies when to use this tool (for reporting bugs or feedback) and instructs the agent to include the conversation array for reproduction. It does not explicitly state when not to use it or name alternatives, but the sibling tools are sufficiently different that the intended usage is 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 destructiveHint=false, so the description adds value by disclosing that the platform hosts the service, requires prepaid credit per query, and that the client is the data controller under LGPD. This goes beyond the annotations to explain operational and legal aspects, though it doesn't detail rate limits or exact response format.

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, reasonably concise paragraph that front-loads the purpose. It covers multiple aspects (purpose, hosting, payment, legal) without excessive verbosity. However, it could benefit from structured bullet points for clarity, but as is, it's adequately concise.

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, the description should clarify what the tool returns (e.g., certificate status, document). It does not specify the output format or the expected response. Additionally, the lack of parameter semantics further reduces completeness, making it difficult for an agent to invoke it correctly. The legal and usage context is helpful but not sufficient for correct invocation.

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 three parameters (ie, cpf, cnpj) with zero description coverage, and the description fails to explain their meaning or usage. It does not say which identifiers can be used or whether they are mutually exclusive. This is a critical gap since the agent must know how to construct the query.

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 a consultation for a negative debt certificate (Certidão Negativa de Débitos) from SEFAZ RN, a specific official source. The verb 'consultar' (query) and resource are unambiguous, making it distinct from sibling tools which are unrelated (authenticate, connect, etc.).

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 about the data being public and from official sources, and mentions payment via prepaid credit. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. The guidance is implicit rather than explicit.

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 covered. The description adds that the tool reports platform and adapter versions, but no additional behavioral context (e.g., network usage, exact output structure) is disclosed. This aligns with the annotation-grounded baseline.

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, front-loaded sentence of 11 words. Every word earns its place, and the structure is immediately parseable. No fluff or repetition.

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 with strong annotations, the description is complete. It states exactly what information is returned (platform and adapter versions), which is sufficient without an output schema. No additional context is necessary.

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 description correctly implies no inputs are required. The schema is trivially 100% covered, and the description adds no parameter-specific meaning but doesn't need to. Baseline for 0 params 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 a specific verb ('Show') and names the resource ('current MCP platform and adapter versions'), making the tool's function unmistakable. It distinguishes itself from siblings like toolkit_info by calling out platform and adapter versions specifically.

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?

No explicit when-to-use or alternative guidance is provided, but the use case is strongly implied by the tool name and description. For a simple version-checking tool, this implicit guidance is adequate, though it doesn't mention exclusions or relationships to overlapping siblings like toolkit_info.

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 fully covered. The description adds value by specifying exactly what information is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes 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 single, well-structured sentence that front-loads the purpose and lists the key information returned. No wasted words.

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 no parameters and no output schema, the description provides a complete picture of what the tool does and what it returns. It could potentially mention the format of the output, but for a state-checking tool, this is sufficient.

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 doesn't need to explain parameter semantics. The baseline for 0 params is 4, and the description appropriately focuses on the return value rather than 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 returns the current toolkit state, listing installed MCPs, connection status, connected accounts, and catalog tool counts. This is specific and distinguishes it from sibling tools like authenticate or connect, which handle setup rather than introspection.

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 the state of the toolkit, which is clear from the context. It doesn't explicitly state when not to use it or mention alternatives, but given the sibling tools are all action-oriented, the usage context is reasonably clear.

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