Certidão de Débitos PJ

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

Beyond annotations (idempotentHint=true, readOnlyHint=false), the description explains the two possible behaviors: adding a permanent header to config or using a session-only token. It also clarifies that calling with no args returns a link. This adds useful context about side effects and modes of 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 somewhat verbose and run-on, with a confusing opening 'MCP.AI for IDE agents' that does not add clear value. However, each subsequent clause carries useful information, and the overall length is manageable.

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 optional-token authentication tool with no output schema, the description covers the essential flow: how to authenticate permanently, how to use a session token, and how to obtain the login link. It lacks explicit mention of return values, but the link is implied in 'get the link'.

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 coverage at 0%, the description compensates by explaining the 'token' parameter: it is an optional JWT for session login, while omitting it yields a login link. This gives the agent enough meaning to invoke correctly, though it could explicitly state that 'token' is a string.

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: to authenticate by logging in and obtaining an access token, with a primary audience of IDE agents. The verb 'log in' is specific, and the resource (this server's config) is mentioned. It does not explicitly differentiate from sibling 'connect', but the purpose is evident.

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 guidance on when to use each mode: permanent config via header vs session-only via token parameter, and when to call with no args to get the login link. It gives concrete scenarios and steps, though it does not mention explicit alternatives or exclusions.

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. The description adds valuable context beyond these: the tool is hosted by the platform, requires no credentials, has a prepaid credit cost model, and accesses only public official data. It also notes that the client is responsible for legitimate use under LGPD, which is extra behavioral/legal guidance.

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 with the core purpose front-loaded in the first sentence. The second sentence adds necessary operational and legal context. It is concise and every sentence earns its place, though the LGPD wording is slightly lengthy.

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 with one required and one optional parameter, and no output schema. The description covers purpose, payment model, and data access rules, but the undefined 'completo' parameter is a notable gap that prevents full agent understanding. Overall, it is adequate but not 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?

The input schema has two parameters (Cnpj required, completo optional) with no descriptions. The description only mentions CNPJ implicitly as the input ('a partir do CNPJ') and does not explain the 'completo' boolean parameter at all. Since schema coverage is 0%, the description fails to compensate for the missing parameter semantics.

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: 'Emite a certidão conjunta de débitos federais de uma empresa a partir do CNPJ' (issues the joint federal debt certificate for a company based on CNPJ). It specifies the verb, resource, and primary input, and is distinct from all sibling tools, which are generic platform operations.

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 operational context for when to use it: 'sem credenciais' (no credentials) and 'pague por consulta com crédito pré-pago' (pay per query with prepaid credit). It also clarifies the data is public and LGPD-compliant. However, it does not explicitly name alternatives or exclusion conditions, but sibling tools are unrelated.

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 and idempotentHint. The description adds specific behavioral context about response shape ('authenticated:true', 'empty pending[]', 'connect_url', and per-install URLs) without contradicting 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 sentences, front-loaded with the core purpose, and no filler. Every word earns its place.

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 strong annotations, the description covers both main states and the URLs returned. It doesn't detail error cases or the contents of pending[], but this is adequate given the simplicity.

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; the empty schema provides 100% coverage, so there is nothing to compensate for. Baseline of 4 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 'Returns connection status and URLs' and explains the two outcome states (connected vs missing credentials), which distinguishes it from sibling tools 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 description implies use for checking connection status and obtaining URLs when credentials are missing, but does not explicitly provide when-not-to-use guidance or name alternatives like 'authenticate'.

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 only state readOnlyHint=false and openWorldHint=true, but the description adds substantial behavioral detail: invoke runs tools one-off without installing or bloating the toolkit; if credentials are needed it "returns a connect link"; if paid and wallet empty it returns a checkout link and instructs the agent to retry after user action; writes require workspace owner/admin. This far exceeds the annotation baseline and clarifies side-effect and auth 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 long but well-structured, using labeled segments like "Core flow:" and "KEY:" to front-load critical behavior. There is minor redundancy (the point about not adding to the toolkit appears twice), but given the tool's 23 parameters and multiple sub-flows, every sentence earns its place and the structure aids scanning.

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 the main marketplace flow, the prompt library subsystem, permission requirements, and payment/auth edge cases — impressive for a tool with no output schema or param descriptions. It omits the 'resume' action and doesn't detail return formats, but for the described use cases it provides enough context to invoke the tool effectively.

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 by explaining the main action parameter values (search, describe, install, invoke, etc.) and the roles of mcp_id, tool_id, prompt_slug, prompt_vars, and arguments within the flow. It does not document every one of the 23 parameters (e.g., limit, message, request_details are not explained), but the high-level semantic mapping of the core parameters is clear and useful.

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 establishes the tool as the mcp.ai marketplace: "the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them." It goes beyond a simple verb+resource by outlining the core flow (search → describe → invoke) and explicitly differentiating from sibling tools like authenticate and connect by describing the marketplace's meta-tool role.

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 when-to-use guidance: "Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use." It also contrasts list_tools as "what is callable right now" and explains when each action (search, describe, invoke, install, subscribe, cancel, report_bug, request_mcp) is appropriate, providing clear decision paths over 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 declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true, so the agent knows this is a side-effect-free, repeatable operation. The description adds the useful context of requiring the conversation array for reproduction, but it does not disclose any other behavioral aspects (e.g., whether feedback is stored publicly, rate limits, or response 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 sentence with two clear clauses. It is front-loaded with the main purpose and provides the key usage instruction. It is concise, though the ambiguity around the conversation array type slightly reduces 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?

For a tool with 3 parameters, no output schema, and no per-parameter descriptions, the description is incomplete. It covers the purpose and the important conversation parameter, but leaves 'context' unexplained and fails to hint at what the tool returns or how success/failure is communicated. It is minimally adequate but has clear gaps.

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 carry parameter meaning. It only mentions the 'conversation array', but the schema types it as a string, which is contradictory and could confuse. The 'context' parameter is not explained at all, and 'message' is only implied by the verb 'Report'. The description fails to clarify the required format or purpose of 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: 'Report a bug, missing feature, or send feedback.' This specifies a verb ('Report') and a resource category (bug/feature/feedback), and it is distinct from all sibling tools (auth, consultation, marketplace, etc.).

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 there is a bug, missing feature, or feedback) and provides a clear instruction: 'Include the conversation array with recent messages for reproduction.' It does not explicitly mention alternatives, but the sibling tools are so different that no exclusion is necessary.

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 cover read-only, idempotent, and non-destructive behavior. The description adds the useful context that the tool returns both MCP platform and adapter versions, clarifying what the user will see beyond the annotation flags.

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 is direct and free of filler. Every word contributes meaning.

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 version-query tool with no parameters and no output schema, the description fully communicates the result (platform and adapter versions). Sibling conflicts are minimal, and annotations cover safety.

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 does not need to elaborate. The schema trivially covers all parameters, and the baseline of 4 applies for parameter-less tools.

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 the specific verb 'Show' with a clear resource ('current MCP platform and adapter versions'). It precisely states what the tool does and distinguishes it from the sibling toolkit_info by focusing on version details.

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 intended usage (when you need version information) is implied by the description but not explicitly stated. There is no mention of alternatives or exclusions, though the sibling toolkit_info could be considered related.

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 and idempotentHint=true, so the safety profile is known. The description adds value by specifying the exact data returned (MCPs, status, accounts, catalog tool counts), which gives the agent a concrete expectation of the output. No hidden side effects are suggested, and the description aligns 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 purpose ('Returns the current toolkit state') and then lists specific components. Every word contributes meaning; there is no fluff or repetition of annotations.

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 (zero parameters, no output schema), the description provides a complete picture. It lists every category of information returned, so the agent knows exactly what to expect. No additional behavioral or output details are necessary for such an introspection 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 are no parameter semantics to clarify. The description correctly omits any parameter details, and the schema already covers everything with 100% coverage. The baseline of 4 is appropriate because no additional parameter context is 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 states a specific verb ('Returns') and resource ('current toolkit state'), and enumerates the exact contents (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like authenticate or connect, which perform actions rather than report 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?

The description implies when to use this tool: whenever an agent needs an overview of the toolkit's current state. It does not explicitly exclude alternatives, but the sibling tools are all action-oriented, so the context is clear. No explicit exclusions are needed for this introspection tool.

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