Prefeitura GO Catalão: Certidão Negativa de Débitos

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

Annotations already indicate it's non-read-only, non-open-world, idempotent, and non-destructive. The description adds some behavioral context (permanent vs session login) but does not fully disclose side effects or implications of the operation.

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 verbose and mixes user-facing instructions with tool details, making it unstructured and not concise. It could be reduced to a few lines for clarity.

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 sibling tools like 'connect' and 'marketplace', the description does not clarify when 'authenticate' is the appropriate choice. It also omits information about the tool's output or return value.

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 explicitly explains the 'token' parameter, stating it is optional and how to use it for session login. This adds meaning beyond the raw schema, which has no parameter 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 indicates the tool is for authentication, mentioning 'log in' and 'token'. However, it's written more as user instructions than a concise tool purpose, and does not explicitly differentiate from 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 gives detailed steps on how to authenticate but does not state when to use this tool versus alternatives. It lacks guidance on scenarios where calling this tool 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 already declare readOnly, idempotent, and non-destructive behavior. The description adds useful conditional details about response fields (authenticated, pending[], connect_url), which goes beyond annotation coverage.

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 primary action ('Returns connection status and URLs'), followed by concise conditional details. Every word contributes value with no 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?

For a zero-parameter status tool with no output schema, the description sufficiently explains both possible response states and their triggers. Combined with the annotations, the agent has a complete understanding of the tool's behavior.

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 parameter semantics are trivial. The description doesn't need to explain parameter behavior, and the baseline of 4 applies due to the absence of 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 connection status and URLs' and provides specific conditional outcomes (authenticated:true vs connect_url), distinguishing it from siblings like 'authenticate' 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 gives clear context for when the tool is used by describing the two states (all connected vs missing credentials). It does not explicitly name alternatives or exclusions, but the scenarios are enough to guide the agent.

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 significant behavioral traits beyond the annotations: it explains that invoke runs an MCP without installing it (side effect), that it returns a connect link if credentials are needed, and a checkout link if payment is needed, and that writes require workspace owner/admin. It also clarifies that search/describe flag installation status. This context is rich and does not contradict any annotations (readOnlyHint=false, openWorldHint=true).

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 highly structured and information-dense. It front-loads the core flow first, then key notes on invoke vs install, then authentication requirements, and finally the prompt library. Every sentence adds value; there is no fluff. While length is significant, it's justified by the tool's complexity (a multi-action router with 23 params). It could arguably be split into sections, but the linear narrative is logical.

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 (14 distinct actions, 23 parameters, no output schema), the description is remarkably complete. It explains the overall purpose, the workflow, edge cases (auth, payment), the difference between transient and permanent installation, and the prompt library functionality. It covers the main user intents and what results to expect (e.g., invoke returns a connect/checkout link). It does not explain return values for every action, but with no output schema, the description provides a sufficient mental model.

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 23 parameters and 0% schema coverage, the description carries the burden of explaining semantics. It thoroughly explains the most central parameter 'action' by enumerating its enum values and their purposes (search, describe, install, invoke, search_prompts, etc.). It also gives context for mcp_id, tool_id, arguments, prompt_vars, and other params implicitly. However, it does not systematically explain every parameter (e.g., limit, query, immediate, tier_slug, cancel_reason), leaving some ambiguity for less central params. Still, it compensates heavily for the coverage 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 is 'The official mcp.ai marketplace' and explains its dual role as a catalog and executor for MCPs/tools. It goes beyond a generic verb+resource by detailing the core actions (search, describe, invoke) and distinguishing it from sibling tools like authenticate or connect. The scope is 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 description explicitly provides usage guidance: the core flow ('action=search discovers MCPs... describe... invoke RUNS that tool'), when to use invoke vs install, when to use subscribe/cancel, and how to use the prompt library. It even gives a direct recommendation ('prefer invoke for a single/occasional use') and explains the difference between invoking and installing. Alternatives are clearly named.

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 adds significant behavioral context beyond the annotations: it discloses payment requirements, data source, confidentiality status, and LGPD obligations. These are operational details not captured in the schema or annotations, and they align with the readOnly, idempotent, and non-destructive 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 concise, with three sentences covering purpose, operational details, and legal context. It is front-loaded with the main purpose and avoids redundancy, making efficient use of each sentence.

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 context such as cost, source, and legality, but it does not clarify the exact input format (CPF vs CNPJ) or what the output will be. Given that there is no output schema, a hint about the return value would improve completeness, but the description still provides enough for a basic 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?

The schema has two parameters (cpf and cnpj) with no descriptions, and the tool description does not explain their meaning, which one is required, or if either can be used. It only implies that they are identifiers for the certificate query. With 0% schema description coverage, the description should have clarified parameter usage but did not.

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 Negative Debt Certificates (Certidão Negativa de Débitos) from the Prefeitura GO Catalão. It names the specific resource and operation, and it is distinct from the generic 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 description provides context on how to use the tool: it is hosted by the platform, requires no platform credentials, and is paid per query with prepaid credit. It also mentions the official source and LGPD compliance. However, it does not explicitly state when not to use it or suggest alternatives, but given the generic siblings, the use case 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 false, destructiveHint false, and idempotentHint true, covering the safety profile. The description adds the behavioral requirement of including conversation data for reproduction, but does not disclose any side effects or outcome of the report.

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 and front-loaded, using two short sentences to convey purpose and a key usage requirement with no 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?

The tool is relatively simple with three parameters and no output schema. The description covers the essential action and the conversation parameter, but it does not explain the required 'message' parameter or set expectations for the response, leaving a notable gap.

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 explains the 'conversation' parameter as an array of recent messages for reproduction, but does not clarify the meaning of the required 'message' parameter or the optional 'context' parameter, leaving ambiguity.

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 with a specific verb and resource: 'Report a bug, missing feature, or send feedback.' It is distinct from sibling tools, which are unrelated to reporting.

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 for when to use the tool (to report issues) and even gives a directive to include the conversation array for reproduction. It does not explicitly exclude alternatives, but there are no similar 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?

The annotations already declare readOnly, idempotent, and non-destructive behavior, which covers the safety profile. The description adds no new behavioral insights beyond what the annotations state (e.g., side effects, error handling). It only specifies the informational content of the output, which is not behavioral transparency, so the score is moderate.

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, succinct sentence that directly states the tool's function without redundancy or extraneous details. It is perfectly concise and well-structured for a trivial tool.

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 the tool has no parameters and no output schema, the description sufficiently indicates what the tool returns (the versions). This is enough for a complete understanding of the tool's purpose and output, especially in the context of sibling tools and typical usage.

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 no parameters, so the input schema fully describes them trivially. The description does not need to add any parameter-related meaning, and none is missing. This dimension is fully satisfied.

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 with a specific verb ('Show') and a specific object ('current MCP platform and adapter versions'). It distinguishes itself from sibling tools like 'authenticate' or 'connect' by focusing solely on version display, leaving no ambiguity about its purpose.

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 usage (when you need version info) but does not explicitly state when to use it versus alternatives or when not to use it. Given the simple nature of the tool and the absence of competing version-related tools, the guidance is adequate but not explicit, earning a mid-range score.

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 readOnly and non-destructive behavior, so the bar for transparency is lower. The description adds useful context about what the tool returns (installed MCPs, connection status, accounts, catalog counts), which goes beyond the annotations. 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, concise sentence that conveys all necessary information without unnecessary words. It is well-structured and front-loaded with the primary action 'Returns'.

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 simplicity (no parameters, simple return), the description is complete. It lists all the key aspects of the returned state, and no additional context is needed.

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 no parameters, so there is nothing to explain. The schema covers this implicitly, and the description does not omit any parameter-related information. Perfect score as the coverage is complete.

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: returning the current toolkit state, including installed MCPs, connection status, accounts, and catalog tool counts. It is a specific verb+resource combination and is distinct from sibling tools like 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 you need an overview of the toolkit state), but it does not explicitly mention alternatives or when not to use it. However, given the tool's simplicity and uniqueness among siblings, the guidance is sufficient.

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