SEFAZ MA: Certidão Negativa de Débitos

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

The description reveals behavioral traits: no-args call returns a link, token call authenticates for the session, and the permanent config option. It adds context beyond annotations like idempotentHint=true by showing the two distinct invocation modes and their outcomes.

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 compact and front-loaded with the main purpose. It packs two usage modes into two sentences, each earning its place, though slightly dense due to the multiple clauses.

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 auth tool with one optional param and no output schema, the description covers the essential workflow, including permanent vs session modes and how to invoke. It doesn't detail the exact return format, but the link and token handling are sufficiently explained.

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 lists 'token' with no description (0% coverage). The description fully compensates by explaining the token is a JWT pasted by the user, and clarifies it's optional since calling with no args is allowed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly explains the tool's purpose: authenticate by obtaining a browser login link or accepting a token. It uses specific verbs and provides concrete workflow steps, distinguishing it from sibling tools like connect by focusing on token-based auth for IDE agents.

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 gives clear usage guidance: either add a permanent header to config or pass a token for session-only login, and explains calling with no args to get the link. It doesn't explicitly exclude alternatives, but the context makes when to use each mode 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 provide readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds valuable behavioral context: it explains the return format (authenticated flag, pending[], connect_url) and the conditional behavior when credentials are missing. This goes beyond what annotations convey.

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 primary action, and no wasted words. Every sentence adds meaningful detail about behavior and return values.

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 (no params, no output schema), but the description fully covers the expected return data and edge cases. Annotations cover safety, and the description provides sufficient behavioral context. Nothing essential is missing.

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 per the rubric, the baseline is 4. The description correctly avoids parameter explanations since none exist.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool 'Returns connection status and URLs', which is a specific verb and resource. The description differentiates from siblings like 'authenticate' (which likely initiates auth) and 'show_version' (which reports version info) by focusing on connection state.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides implicit usage context (when all providers connected vs. when credentials missing) but does not explicitly state when to use this tool over alternatives. No exclusions or competitor tool names mentioned, though the purpose is clear enough for a status check.

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 discloses key side effects and behaviors beyond the annotations: invoke does a one-off run without bloating the toolkit, credential gaps return a connect link, unpaid paid tools return a checkout/top-up link, and all writes require workspace owner/admin. It also reveals installed_in_toolkit vs installed_in_workspace flags and that account on prompts work without login, giving the agent a realistic behavioral contract.

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 informationally dense and every sentence contributes, but it is a long wall of text with heavy capitalization and run-on phrasing rather than organized into clear sections. For a tool with this many actions, structured paragraphs or bullet lines would make the decision process easier for an agent.

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 complexity with 25 parameters and no output schema, this description covers broad workflows well but omits some behaviors: the 'resume' action is never mentioned, and the "action" enum also includes actions without plain textual speaking. It does not explicitly describe what most actions return, which is important when no output schema is provided. It is mostly complete but not fully self-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?

With 0% schema description coverage, the description must compensate; it does add high-level action semantics (action=search/describe/invoke, tool_id, prompt variables, publish slug), but the 25 parameters remain mostly implicit. Parameters like immediate, tier_slug, conversation, prompt_targets, report_context, and cancel_reason are not mapped or explained, so an agent would have difficulty filling them correctly beyond guessing from enum names.

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, cataloging MCPs/tools, and the way to launch them via search → describe → invoke. It distinguishes the tool from siblings by naming report_bug and framing install/invoke usage, and it covers the added prompt-library responsibility.

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?

Explicit guidance is abundant: use invoke for one-off use even when not installed, use install only to make an MCP permanent, prefer invoke for single/occasional use, and call list_tools for what is callable right now. It also names subscribe/cancel, report_bug, request_mcp, and prompt-library actions, showing when each path 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 include idempotentHint: truechers and readOnlyHint: false, which suggest the operation may have side effects (like creating a report) but is idempotent (repeated calls have no additional effect). The description does not explicitly mention side effects or idempotency, but it does add context about including the conversation array for reproduction, which is beyond annotations. However, it does not clarify what happens after reporting (e.g., how the report is processed) or any side effects like creating a ticket. Given annotations cover some safety aspects, but description could add more behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, consisting of two sentences, and front-loads the purpose. It provides essential information without excessive detail. It earns a high score for brevity, but loses a point because it could be slightly more structured (e.g., breaking down what to include for different report types).

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 with no output schema and limited annotations, the description provides enough to understand the main input (message) and the reproduction aid (conversation). However, it lacks details on the 'context' parameter and does not describe expected outcomes or response behavior. For a simple reporting tool, this might be acceptable, but it could be more complete by clarifying parameter usage and what happens after submission.

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 missing parameter explanations. The description mentions 'conversation array' and 'recent messages' but does not elaborate on 'message' or 'context' parameters. The schema shows 'message' is required, 'context' defaults to empty, and 'conversation' is a string that likely represents the array. The description adds some meaning for 'conversation' but not for 'message' or 'context'. Since it partially compensates but not fully, a score of 3 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 the tool's purpose: to report a bug, missing feature, or send feedback. It distinguishes itself from siblings by mentioning the conversation array for reproduction, which is unique among the listed tools. However, it does not explicitly differentiate from all sibling tools, but the verb 'report' and specific use case make it clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: when reporting a bug or feedback. It does not provide explicit when-not-to-use guidance or mention alternatives, but the context signals show sibling tools like 'marketplace' or 'show_version' are unrelated, so the purpose is clear. It lacks explicit exclusions or alternative recommendations.

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 signal read-only, idempotent, non-destructive behavior. The description adds valuable context beyond annotations: prepaid payment is required, the data comes from official non-confidential sources, and the client is the LGPD controller. This meaningfully supplements the annotation-only 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 compact sentence that front-loads the main purpose and then adds important operational and legal context. It is somewhat dense but every clause contributes useful information, and there is no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, source, cost, and privacy responsibilities, but it omits essential call-level context: how to choose among ie/cpf/cnpj, whether at least one is required, and what the response represents. With no output schema and minimal parameter documentation, this incompleteness hurts usability.

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 three undocumented parameters (ie, cpf, cnpj) and 0% schema description coverage. The description does not explain these parameters, their relationships, which one to use, or that one is likely required. This is a critical gap because the description adds no semantic value for the 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: consulting a 'Certidão Negativa de Débitos' from SEFAZ MA via official sources. It uses a specific verb ('consultar'), names the resource, and distinguishes itself from the unrelated platform-level sibling 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 provides clear usage context: it is for querying official Brazilian tax debt certificates, requires no platform credentials, and is paid per query with prepaid credit. It does not explicitly name alternatives or state when not to use it, but the context is sufficient given the unrelated sibling 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?

Annotations clearly indicate readOnlyHint: true, idempotentHint: true, and destructiveHint: false. The description 'Show' aligns with these hints, providing complete transparency about the tool's non-mutating behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that conveys all necessary information without superfluous text. The structure is efficient and easy to parse.

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?

While the description and annotations provide sufficient information for a read-only version tool, there is no output schema or detailed statement about what information is returned. However, given the simplicity of the tool and its clear purpose, the overall context 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, and the input schema correctly reflects this with an empty properties object. Schema description coverage is 100% as there are no parameters to document, so parameter semantics are fully clear.

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' clearly states what the tool does, and the title 'Show Version' reinforces this. It is specific and unambiguous.

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 tool's purpose makes its usage self-evident as a read-only informational tool. Since it takes no parametersched and is part of a larger MCP toolkit, users know when to call it, but no explicit prerequisites or context are provided.

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 safe, non-mutating nature is covered. The description adds useful context by disclosing the concrete return contents (installed MCPs, connection status, accounts, catalog tool counts). There is no contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single well-structured sentence that front-loads the main verb and resource, then efficiently lists the specific state components. Every part adds value 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?

With no parameters, no output schema, and simple read-only behavior, the description provides sufficient context by naming the main categories of returned information. It is fully adequate for an agent to know what to expect from this 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 tool has zero parameters and schema description coverage is 100%, so the baseline is 4. The description appropriately focuses on what the tool returns rather than needing to explain parameter 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 states a specific verb ('Returns') and a specific resource ('current toolkit state'), then enumerates exactly what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly differentiates it from action-oriented siblings like connect, authenticate, and report_bug.

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 diagnostic/status usage by enumerating state details, but it does not explicitly name alternatives or say when not to use this tool. The context is clear enough for an agent to distinguish it from the other sibling tools, but it lacks explicit exclusion or alternative guidance.

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