SEFAZ PE: Certidão Negativa de Débitos

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

The description adds valuable behavior beyond the annotations: it explains that the header-based approach is 'permanent, non-expiring', while pasting a token is session-only, and that calling with no arguments returns a link. It is consistent with idempotentHint=true and does not contradict 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 compact and uses 'Best:' and 'Or:' to structure alternatives cleanly. It stays focused on user actions and does not repeat or embellish schema/annotation 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?

The description is sufficient for a simple tool with one optional parameter: it covers login, the token parameter, the no-arg case, and the persistent configuration case. The only minor gap is that it does not explain what success/error responses look like, but that is not essential here.

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?

Even though schema description coverage is 0%, the description fully explains the token parameter as a JWT pasted by the user. It also clarifies that the parameter is optional and defines the effect of omitting it (getting a link). This is meaningful semantic added value beyond the raw 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 clearly states the tool authenticates an MCP.AI server for IDE agents, either by generating a login link or validating a pasted JWT token. It is specific about the resource and action, but it does not explicitly distinguish itself from the sibling tool '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 explicitly covers two use scenarios: a persistent connection via Authorization header and a session-only login by pasting token. It also explains the no-argument behavior ('get the link'). It does not explicitly say when to avoid using this tool or mention alternatives, but 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, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral detail beyond annotations by explaining the two return scenarios: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing.

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 necessary detail about conditional outcomes. There is no filler or repetition of schema/annotation information.

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

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

For a simple read-only status tool with no output schema, the description covers the main return cases and the meaning of key fields. It could be slightly more complete by explaining partial-connection states or the contents of pending[], but the current level is sufficient for a low-complexity 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 the schema is empty, so there are no parameter semantics to document. Per the baseline for 0-parameter tools, a score of 4 is appropriate; the description does not need to compensate for missing parameter 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 uses a specific verb ('Returns') and a clear resource ('connection status and URLs'), and the conditional behavior distinguishes it from sibling tools like authenticate. It clearly states what the tool does and the two main result scenarios.

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 tool is for checking connection status and provides context about when different results appear, but it does not explicitly state when to use this tool versus alternatives such as authenticate. There are no exclusions or alternative tool references.

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 annotations (which state no fully read-only hint), description discloses that invoke can execute uninstalled MCPs temporarily, actions may require owner/admin for writes, and invoke may return connect or checkout links requiring user action. This is significant behavioral detail not otherwise known, and consistent with annotations.

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

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

The description is dense and front-loaded with the main flow, but it packs a lot into long sentences, making it challenging to parse. Though every part adds value, lack of structure (no bullets or clear sections) reduces scannability; still, it's not wasteful.

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 high complexity (14 actions, prompt library) and no output schema, the description covers each action's function, clarifies core flows, and addresses install vs. invoke. However, lacks specifics on return formats or how certain params like limit, immediate, or conversation are used, leaving some minor gaps for an agent.

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?

Although schema coverage is 0%, the description explains many parameters implicitly (action, mcp_id, tool_id, arguments, and prompt-related ones) by describing workflows of search, describe, invoke, and prompt operations. It does not detail every param like limit, immediate, or cancel_reason, but covers the core ones.

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 identifies the tool as the marketplace for MCPs with multi- faceted functionality (search, describe, invoke, install). Distinguishes its role in the MCP ecosystem and differentiates from sibling tools by specifying its scope (in-platform catalog and execution).

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?

Explicitly explains core flow (search → describe → invoke) and distinguishes single-use invoke from permanent install, including when to use each. Directs to list_tools for current callable tools and mentions subscribe/cancel for billing, providing clear guidance against using alternatives.

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 indicate this is not read-only (readOnlyHint=false), is idempotent, and is not destructive. The description adds the instruction to include the conversation array for reproduction, which hints at a side effect (submitting data) but does not disclose other behaviors like authentication requirements or potential outcomes. Since annotations cover the safety profile, a mid score is appropriate.

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 purpose and providing one essential usage hint. Every word adds value, 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 tool with 3 parameters, no output schema, and no description coverage, the description is too sparse. It does not explain all required inputs or what happens after reporting. An agent would need additional information to use this tool 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?

Schema description coverage is 0%, so the description must compensate. It only mentions the conversation parameter ('Include the conversation array'), leaving 'message' and 'context' unexplained. The agent cannot infer the meaning of 'context' or the expected content of 'message' from the description 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's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb ('Report') and identifies the resources (bugs, features, feedback). This clearly distinguishes it from sibling 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 primary usage is explicitly stated: use when you have a bug, missing feature, or feedback. It does not explicitly mention exclusions or alternative tools, but the context is clear and no contradictory guidance is provided. However, it lacks 'when not to use' 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?

Beyond the idempotent/readOnly annotations, the description discloses critical behavioral details: it is a paid service (prepaid credit), it does not require platform credentials, and it includes LGPD data-controller responsibility. It also clarifies that the data is not confidential, adding transparency not present in 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 short paragraph, but it contains slight redundancy, repeating the 'official source' concept. Overall, it is efficient and avoids unnecessary length, though it could be tightened by removing repetitive phrases.

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 context about data sensitivity, LGPD, payment, and source, but it lacks information on parameter usage and any specific constraints (e.g., required fields, formatting). For a read-only query tool, the description is adequate but not exhaustive, leaving some gaps for the user.

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 seven parameters (ie, cpf, cnpj, login_cpf, login_senha, pkcs12_cert, pkcs12_pass) with zero description coverage. The description does not explain any of these fields, their format, or which are required. The parameter names are suggestive but the description adds no clarification, failing to compensate for the lack of schema descriptions.

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 for a negative debt certificate (Certidão Negativa de Débitos) from SEFAZ PE, an official source. It distinguishes itself from generic sibling tools like 'authenticate' or 'connect' by specifying the exact resource and action.

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 usage context: it is hosted by the platform, requires no platform credentials, and is paid per query with prepaid credit. It also clarifies that it queries official non-confidential data, giving the user a clear picture of when to use it, though it does not explicitly contrast with alternatives.

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 indicate read-only, non-destructive, idempotent behavior. The description adds that the tool returns platform and adapter versions, matching annotations but not providing deeper behavioral context such as output format or potential failure modes.

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 states the tool's function immediately. It contains no filler or redundant wording.

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 display tool with clear annotations and no output schema, the description is sufficient and complete. It clearly communicates what the tool reports.

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 has no parameter documentation burden. The baseline score of 4 applies, and no additional parameter semantics are needed.

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: showing the current MCP platform and adapter versions. It is specific and actionable, though it does not explicitly differentiate itself from sibling tools like toolkit_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?

There is no guidance on when to use this tool or when an alternative might be better. The description simply states what it does, leaving the agent to infer appropriate use cases.

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 meaningful behavioral context by detailing what the returned state includes, which is especially valuable given there is no output schema.

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 action and resource, then lists the specific data points returned. Every clause 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?

Given the tool has no parameters, no output schema, and strong annotations, the description fully covers what the agent needs to know: what the tool returns and the scope of that information. It is complete for a simple read-only state inspection 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, so there is no parameter semantics burden on the description. Per the rubric, a zero-parameter tool receives a baseline of 4; the description appropriately focuses on return content instead of parameter details.

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') with a clear resource ('current toolkit state') and enumerates exactly what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like authenticate, connect, and show_version.

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

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

The description implies when to use the tool—whenever the agent needs to inspect the toolkit's current state—but it does not explicitly state when not to use it or mention alternatives. There is no direct comparison with sibling tools, so usage guidance remains 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.