SEFAZ BA: Certidão Negativa de Débitos

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

The description explicitly discloses the side effects of both login methods (permanent vs. session-only), which is valuable context beyond the annotations. It also provides implementation details like the header format. While the description does not contradict the annotations, it omits specific potential outcomes (e.g., error messages for invalid tokens or failure states), hence not a perfect score.

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 informative but contains some informality and redundancy. The sentence 'MCP.AI for IDE agents (Cursor, etc.)' is useful context, and 'log in in the browser' is slightly awkward. The instructions could be more direct, e.g., 'Log in via the browser and copy the access token.'

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 only one optional parameter, the description thoroughly covers the authentication flow. It explains the two modes (permanent config-based and session-based), the required syntax for both, and the user interaction needed for the session-based flow. This is complete for the tool's described functionality.

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 parameter by giving an example call `{ token: "<jwt>" }`. However, it does not explicitly state that the parameter should be a JWT string, although the word 'jwt' is mentioned. Since the schema provides no description or type, the description carries the entire burden, and it just meets the minimum viable threshold by providing an example.

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 an IDE agent (like Cursor) to the MCP server. It specifies the core actions (login in browser, copy access token) and mentions the primary input parameter (token). While the title 'authenticate' is generic, the description's reference to 'MCP.AI for IDE agents' provides necessary context. However, it does not explicitly distinguish itself from its sibling tools, though the context makes it the obvious authentication entry point.

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?

This is a major strength. It explicitly guides the agent on the ideal path: use the config with a bearer token for permanent access. It then clearly states when to use the token parameter: 'Or paste it here for a session-only login: call with { token: "<jwt>" } after the user pastes...' It also tells the agent what to do if the user provides no arguments, defining the required behavior for both success and no-input 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 non-destructive behavior, so the description's burden is lower. It adds meaningful context about the two response states (authenticated vs. connect URLs), giving an agent useful expectations about returned data without needing to call the 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?

Three concise sentences cover purpose, state behavior, and URL semantics with no redundancy. The key success condition is front-loaded, and every sentence adds 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 zero-parameter, read-only status tool with no output schema, the description provides enough context to anticipate the main response fields (authenticated, pending, connect_url). It could mention whether the response is JSON or whether fetch/refresh is needed, but overall it is complete enough for an agent to select correctly.

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 trivially 100%. The description adds value by explaining what the no-arg call returns in different connection states, which is more useful than the empty schema alone.

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 that this tool returns connection status and URLs, with specific behavior for connected vs. missing-credential states. It distinguishes itself from siblings like authenticate, which presumably initiates connection, by being a status/read tool rather than an action 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 implies this is for checking connection status, especially when credentials may be missing, and contrasts with authenticate's likely action role. It does not explicitly name an alternative or state when not to use it, but the context plus sibling names gives clear enough 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 are thin (title only; readOnlyHint=false; openWorldHint=true; no other safety context), so the description carries much of the transparency burden. It adds meaningful behavioral context above what annotations provide: 'invoke works even when the MCP is NOT installed — runs the tool one-off, without adding the MCP to the toolkit and without bloating the tool list,' 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin,' and the connect/checkout-link retry mechanic. No contradiction with annotations; it simply goes beyond them. Category 4 because it does not surface a few pitfalls, like what 'resume' or 'uninstall' exactly does to the toolkit.

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 with genuinely useful facts, but it is a single unbroken paragraph with no bullet points or subsections despite covering roughly twelve subpathway flows. Every sentence does contribute new information, but load-wise it is a wall of text; the pacing is okay for a central swiss-army-knife tool, but the structure makes it harder to scan and skill to follow. Slightly improving would break the 'Key' and 'Writes' hints into bulleted sections.

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 highly complex tool (23 params, ~20 action values, no output schema, mixed catalog/runner/prompt-library semantics), the description covers the main pillars: the discover→describe→invoke path, the distinction from install, the auth/payment retry flows, the admin permission requirement, and the separate prompt library sub-path plus its sharing links. It is not fully complete: `resume`, cancel-related params, and `report_context`/`request_name` behaviors are unspoken, and the `installed_in_toolkit vs installed_in_workspace` distinction is merely mentioned. Overall, impressive coverage for its surface area but with notable blind spots.

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 schema_description_coverage at 0% across 23 parameters, the description must compensate, and it does only partially. It explains the primary `action` enum values (search, describe, install, invoke implicitly, subscribe, cancel, search_prompts, get_prompt, publish_prompt, etc.), and it provides flow meaning for `query` and the prompt library's `prompt` args. But many parameters like `limit`, `immediate`, `tier_slug`, `conversation`, `cancel_reason`, `cancel_comment`, `report_context`, `request_name`, `request_details`, and `prompt_targets` are left entirely unexplained, and the schema itself provides no descriptions. Given the number of parameters, this is a meaningful 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 as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' which is a specific resource with a well-defined functional role. It also distinguishes itself from siblings by enumerating search/describe/invoke/install flows rather than focused helpers like authenticate or show_version. It loses a point because it is an umbrella across ~12 distinct actions (search, describe, invoke, install, subscribe, prompt library, etc.) rather than a single sharp verb+resource 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?

The description explicitly provides decision guidance: 'Use install only to make an MCP PERMANENT in the active toolkit; prefer invoke for a single/occasional use,' and 'list_tools lists what is callable now; subscribe/cancel handle per-MCP billing; request_mcp asks us to build a NEW MCP when nothing fits.' It also gives the full search→describe→invoke flow, plus recovery instructions for credential/payment links ('user opens it, then you retry'). This is exemplary when-to-use / when-not-to-use coverage.

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?

While annotations already provide readOnly=false and destructive=false, the description adds context about including conversation data for reproduction. Yet it does not disclose what happens after reporting (e.g., whether an issue is created, data is sent), leaving some ambiguity about side effects.

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, two sentences long, with the main purpose front-loaded and no wasted words. It immediately tells users what the tool does and how to use it effectively.

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 adequately covers the main use and provides a critical hint about the conversation array. However, given the lack of schema descriptions and output schema, more details could be included, such as the required 'message' parameter's role or error handling, making it minimally complete rather than fully detailed.

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 partially by explaining the 'conversation' parameter's purpose and implying 'message' for feedback. However, the 'context' parameter remains unexplained, and the description does not fully detail all parameters' expected values or formats.

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 reports bugs, missing features, or feedback, with a specific verb and resource. It also provides a key instruction about including the conversation array, which distinguishes the tool's purpose without ambiguity.

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 explicitly instructs to include the conversation array for reproduction, which is a concrete usage guideline. However, it does not mention when not to use the tool or compare to alternatives, though siblings are unrelated, so the guidance is adequate for the 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 the safety profile is clear. The description adds context about payment requirements and data controller responsibilities, which is useful but does not detail response behavior or error conditions.

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 key information front-loaded (purpose, official source, payment model). It is concise but could be better structured with bullet points or clearer separation of usage vs. legal notes.

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 0% parameter coverage, the description should compensate more. It covers purpose, payment, and legal context, but lacks details on input requirements, response format, or typical use cases, making it incomplete for a complex 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?

Schema description coverage is 0%, and the description does not explain the parameters (ie, cpf, cnpj) beyond their names. The description mentions the certificate type but not which identifier is required or how they relate, leaving the agent to infer from parameter names alone.

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 queries SEFAZ BA for Certidão Negativa de Débitos from an official source. It distinguishes from siblings by specifying the Brazilian tax authority and certificate type, though it doesn't explicitly contrast with other query tools.

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 payment model (prepaid credits) and data privacy context (LGPD), but does not specify when to use this tool versus alternatives or provide exclusions. It implies usage for official debt certificate queries but lacks explicit 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 aligns with the annotations: readOnlyHint is true, idempotentHint is true, and destructiveHint is false. It adds minimal behavioral context by specifying 'current' and 'platform and adapter' scope, but it does not describe return format or any other side effects; annotations already cover the safety profile.

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, grammatically simple, and front-loaded with the action verb 'Show'. Every word earns its place and there is no redundant or filler content.

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 minimal complexity, zero parameters, and strong annotation coverage, the description is complete enough for an agent to select and invoke it correctly. It clearly states what versions will be displayed.

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 zero parameters, so the baseline of 4 applies. The description does not need to add parameter-level detail because the input schema has no properties 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 uses a specific verb ('Show') and names a concrete resource ('current MCP platform and adapter versions'). This clearly distinguishes it from sibling tools like authenticate, connect, marketplace, and report_bug, 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 makes the use context clear: invoke this tool when version information about the MCP platform and adapter is needed. It does not explicitly discuss alternatives or exclusions, but for a zero-parameter informational tool the context is sufficient.

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 bar is lowered. The description adds useful behavioral context by specifying what the state report includes, which details what the read operation reveals about the system.

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, front-loaded sentence that immediately states the purpose and then provides a compact, useful enumeration of the returned information. Every part of the sentence adds information; there is no filler or 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?

Given that this is a simple, parameterless introspection tool with strong read-only/idempotent annotations, the description is complete for an agent to understand what it will receive. The enumerated return content compensates for the absence of an 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, and the schema coverage is 100%, so there is no parameter ambiguity to resolve. A baseline of 4 is appropriate because the description correctly signals that no input is needed to obtain the toolkit state.

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 names a concrete resource: the current toolkit state. It goes further and enumerates the exact contents (installed MCPs, connection status, accounts, catalog tool counts), which clearly differentiates it from siblings 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 clearly implies this is the tool to invoke when an agent needs a snapshot of the current toolkit environment. It does not explicitly name exclusions or alternatives, but the clear scope and context make the appropriate usage unambiguous given the sibling tools.

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