Prefeitura RS Canela: Certidão Negativa de Débitos

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

Annotations already provide idempotentHint=true and destructiveHint=false; the description adds meaningful behavior beyond that: the browser login flow, permanent vs session-only connection, and no-args behavior returning the link. It does not disclose error handling or token expiration specifics, but it gives useful behavioral context.

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 login steps, and every sentence contributes useful guidance. It is slightly dense and informally structured, but it has no filler or redundant restatement.

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 one optional parameter and no output schema, the description adequately covers invocation modes, session vs permanent usage, and token format. It omits details like success/failure responses or exact token expiration, but it provides enough context for correct tool selection and 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?

Despite 0% schema description coverage, the description fully compensates by explaining the single 'token' parameter: it is a JWT/access token pasted from the browser, and omitting it triggers the login-link flow. This clarifies both the parameter's meaning and its optionality.

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 authentication entry point: it guides the user through logging in via browser, copying an access token, and configuring it. It does not explicitly use a verb like 'authenticates' and does not differentiate from sibling tools such as 'connect', but the purpose is still 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 gives explicit usage contexts: add the token to config for permanent non-expiring access, paste it for session-only login, or call with no args to get the login link. It does not mention when not to use this tool or compare it directly with sibling alternatives, so it is strong but not fully 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 mark the tool as read-only and idempotent, and the description adds useful state-dependent behavior: connected providers yield authenticated:true with empty pending[], while missing credentials yield connect_url and per-install URLs. 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 compact sentences front-load the core purpose and then give the conditional output behavior. Every sentence earns its place with no 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 0-parameter read-only status tool with no output schema, the description sufficiently covers both relevant states and the returned fields. It is complete enough for an agent to select and invoke the 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?

The tool has zero parameters and the schema is fully covered by an empty properties object, so the description has no parameter meaning to add. The baseline of 4 for a no-parameter tool 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 opens with a specific verb and resource: 'Returns connection status and URLs,' clearly identifying the tool as a status/connectivity check. The conditional details about authenticated:true vs connect_url further distinguish it from siblings like authenticate.

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 first sentence gives clear context: use this tool when you need connection status and URLs. However, it does not explicitly state when not to use it or name alternatives like authenticate for establishing connections.

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 goes far beyond annotations, disclosing that invoke works without installation, that it handles credential/payment flows via links, that install makes MCPs permanent, and that search/describe flag installed status. It also introduces the prompt library as a separate capability. No contradictions with annotations (readOnlyHint=false is consistent with write actions described).

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 dense paragraph with no formatting or bullet points. While it packs a wealth of information, it is not front-loaded with the most critical info first and requires careful parsing. For a tool with this many capabilities, some structure would improve readability. It is overly long but every sentence carries value.

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 complexity (23 parameters, 14 actions, no output schema), the description covers the core flows, edge cases (credentials, payment), permission requirements, and even the separate prompt library. It explains the distinction between installed and not-installed MCPs and when to use each action. This is remarkably complete for such a multifaceted 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 coverage is 0%, but the description compensates by explaining the purpose of key parameters like action, query, mcp_id, tool_id, arguments, and prompt-related fields within the flows. However, it does not explicitly document all 23 parameters (e.g., limit, immediate, tier_slug, cancel_reason), leaving some ambiguity for less central parameters. Still, it adds substantial meaning beyond raw names and defaults.

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 is the official mcp.ai marketplace that catalogs and runs MCPs/tools, and explicitly lists the core flow (search → describe → invoke). It distinguishes itself from siblings by being the central marketplace entity, and differentiates actions like invoke vs install.

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 explicit guidance for when to use invoke (one-off) vs install (permanent), when to use list_tools, subscribe/cancel for billing, report_bug, request_mcp for new MCPs, and the prompt library functions. Also notes that writes require owner/admin and that invoke returns connect/checkout links for credential/payment obstacles.

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. The description adds valuable context beyond these: payment per consultation with prepaid credits, no need for platform credentials, and LGPD-related responsibilities for the client as data controller. It also explicitly states the data is not confidential, which is relevant for compliance. 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 paragraph that covers purpose, payment model, data source, and legal responsibility. It is reasonably concise but not front-loaded; the core purpose appears first, which is good. Slightly more structure or brevity could earn a 5.

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 two-parameter tool without an output schema, the description adequately explains the purpose, pricing, and legal boundaries. It lacks guidance on how to provide the CPF/CNPJ and what the returned certificate looks like, but the overall context is sufficient for an agent to understand the tool's role.

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 two parameters (cpf, cnpj) with zero description coverage. The description does not explain the role of these parameters, whether at least one is required, or how to choose between them. Since the description must compensate for low schema coverage but fails to do so, this is a significant 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 states the tool consults a Certidão Negativa de Débitos (Negative Debt Certificate) from Prefeitura RS Canela, using the verb 'consulta' and identifying the specific resource and municipality. This distinguishes it from the generic sibling tools 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 provides clear context on how the tool is used: it is hosted by the platform, requires no platform credentials, and charges per query with prepaid credit. It implies the use case is querying official Brazilian sources, but it does not explicitly state when to use this instead of an alternative or include exclusions, so it stops short of a 5.

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 idempotentHint=true and destructiveHint=false. The description adds useful behavioral context by instructing the user to include the conversation array for reproduction, but it does not disclose what happens after submission, such as confirmation, rate limits, or whether the report is stored locally or sent externally.

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 long and front-loads the core purpose. No redundant phrasing or unnecessary details dilute the message.

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 reporting tool with no output schema and minimal parameters, the description covers the purpose and gives one concrete input instruction. However, it fails to explain the required 'message' parameter and leaves room for ambiguity about the 'conversation' type, which prevents it from being fully 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?

Schema description coverage is 0%, so the description must compensate. It mentions 'conversation' but omits the required 'message' parameter and the optional 'context' parameter. It also calls conversation an 'array' while the schema types it as a string (JSON array), which adds confusion rather than clarifying.

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?

Description uses a specific verb and states the resource and purpose: 'Report a bug, missing feature, or send feedback.' This clearly distinguishes it from sibling tools like authenticate, marketplace, or show_version, none of which overlap with user feedback.

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 indicates when to use the tool: for reporting bugs, missing features, or sending feedback. It does not explicitly name alternatives for exclusion, but the sibling list shows no competing reporting tool, so the usage context is sufficiently 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, idempotentHint, and destructiveHint, covering the safety profile. The description adds that it reports platform and adapter versions, which is slightly more specific but doesn't disclose return format or timing. Minimal added value beyond 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?

A single, front-loaded sentence with zero filler. It wastes no words and delivers the purpose efficiently.

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 tool with comprehensive annotations, the description sufficiently conveys its function. Though no output schema exists, the output is version info, which is low complexity. A minor lack of detail on output format is excusable.

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; the baseline for 0 params is 4. The description correctly implies no parameters are needed, and the schema confirms 100% coverage with no properties.

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 identifies the resource as 'current MCP platform and adapter versions'. This clearly distinguishes it from sibling tools like 'authenticate' or 'report_bug', making the purpose 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 is self-explanatory and no alternatives are mentioned, but for a trivial version-reporting tool, context is clear. It doesn't explicitly state when not to use it, but given its simplicity, this is a minor gap.

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, covering safety. The description adds what data is returned (MCPs, connection status, accounts, catalog counts), which complements the annotations without repeating them. No hidden side effects or contradictions.

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 that covers the tool's purpose and output details without any fluff or repetition. Every clause contributes to understanding the tool's function and return value.

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 no output schema, the description fully specifies the return format (installed MCPs, connection status, accounts, catalog tool counts). It is complete for a no-input, read-only query tool, and the annotations cover safety aspects, making the overall context 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 baseline is 4. The description adds value by specifying the output content, which compensates for the lack of an output schema. No parameter documentation is needed, and the description provides meaningful detail about what the response will contain.

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 ('current toolkit state') with enumerated details (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like show_version or marketplace, which focus on different aspects.

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 communicates usage as a diagnostic/state query. It doesn't explicitly name alternatives or exclusions, but given the sibling set, there's no obvious conflicting tool. The context is clear enough for an agent to select it when needing an overview of the toolkit's current state.

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