JUCESP: Consulta Pública de Licenciamento

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

Annotations already cover idempotency and non-destructive hints; the description adds a valuable behavioral context: the token can be made permanent via a server header or session-only via pasted JWT, and calling with no args returns the login link. It does not contradict the annotations and offers meaningful extra insight.

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 information-dense; every sentence adds functional information. The opening 'MCP.AI for IDE agents (Cursor, etc.)' is slightly promotional and not strictly necessary, but the rest is well-structured and easy to follow.

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 small parameter set and abundant annotations, this is reasonably complete for an auth tool. It explains the full flow in prose, but it doesn't explicitly state what the tool returns after a successful token-based login (the output schema is empty). That minor gap prevents a perfect score.

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 provides only an unannotated 'token' string, so the description carries the full interpretive burden. It explains that the token is the JWT the user pastes, that it is optional, and that calling with no args triggers the 'get link' flow. This makes the parameter behavior unmistakable.

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 main purpose: it logs in to MCP.AI for IDE agents via a browser token flow. It gives concrete actions (log in, copy token, get link, session login) so an agent can identify when to use it, though it stops short of explicitly distinguishing it from sibling tools like 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?

It provides explicit guidance on when to choose the permanent config approach, when to use the session-only token paste, and when to call with no arguments. However, it does not explicitly say when not to use this tool or call out alternatives among the 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?

Despite lacking explicit annotations about side effects, the description discloses clear behavioral outcomes: returns authenticated:true with empty pending[] when all providers are connected, and connect_url when credentials are missing. This adds meaningful transparency beyond the readOnly and idempotent hints.

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, using only two sentences to convey the tool's purpose and key behavioral cases. No redundant or extraneous information is included.

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 two main scenarios but omits potential edge cases (e.g., partial provider connectivity or error states). Given the tool's simplicity and lack of output schema, this is mostly complete but could be slightly more thorough.

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, and the schema covers 100% of the interface. Since there are no parameters to explain, the description fully aligns with the schema and adds no unnecessary 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 clearly states the tool returns connection status and URLs, specifying the exact output in two distinct scenarios (all providers connected vs. missing credentials). The verb 'Returns' is explicit and the scope is well-defined.

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 does not provide any guidance on when to use this tool instead of siblings like 'authenticate' or 'marketplace'. It explains behavior but fails to indicate the appropriate context, such as checking status before authentication.

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 readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that consultation is paid per use with prepaid credits, hosted by the platform, and the data is public from official Brazilian sources. It also discloses data subject responsibilities under LGPD. This goes beyond annotations and explains cost implications and data control, though it could have detailed response format or rate limits.

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 paragraph that covers purpose, hosting, authentication, cost, data source, legal compliance, and data handling. Every sentence adds value without being overly verbose.

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 query with one parameter and minimal schema, the description covers usage context, cost model (prepaid credits), and legal compliance. It doesn't explain what to do if the CNPJ is invalid or the licensing information is not found, but given the simplicity of the tool, this may be 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?

Schema coverage is 0% in the description, but with only one parameter (cnpj), the description notes the format in the purpose ('pelo CNPJ'), which adds some semantic value. However, the description doesn't specify CNPJ mask requirements, length, or format. Since there is only one parameter and the description does mention it, this is adequate but not extensive.

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 performs a public license consultation for a company at JUCESP by CNPJ. It is specific about the resource (JUCESP licensing), the verb (consult), and differentiates from siblings by mentioning the specific Brazilian registry context.

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 context (public consultation via CNPJ) and notes it is hosted on the platform without credentials, but does not explicitly explain when to use this tool versus alternatives or mention sibling tools. Some guidance on legitimate use (LGPD) is given, but no direct comparison to 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?

Discloses many non-obvious behaviors: invoke works even when MCP is not installed (one-off, no toolkit bloat), returns connect/checkout links for auth/payment, and flags installed_in_toolkit vs installed_in_workspace. This goes far beyond the basic annotations and no contradiction exists.

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 every sentence carrying useful information. However, it is a single long paragraph with no paragraphs or bullet points, which hurts readability and scanning. It earns its length but could be better structured.

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 core flows, auth/payment handling, write permissions, and the prompt library. However, it does not describe the return value of successful invokes or search results, and the absence of an output schema increases the need for such details. Still, given the tool's complexity, coverage is strong.

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 and 23 parameters, the description explains the core parameters (action, query, mcp_id, tool_id, arguments) in context but fails to clarify critical formats (e.g., arguments/prompt_vars are JSON strings) and many secondary parameters (immediate, tier_slug, cancel_reason, prompt_targets) are not explained. Partial compensation at best.

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 clear statement that it is the official mcp.ai marketplace and the way to run MCPs. It explicitly lists capability requests like 'find an MCP that does X' and distinguishes itself from sibling tools by being the catalog and execution layer.

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 a concrete core flow (action=search → describe → invoke) and explicitly contrasts invoke vs install, noting when each is appropriate. It also states write operations require workspace owner/admin and clarifies when to use subscribe/cancel, report_bug, and request_mcp.

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 idempotentHint=true and destructiveHint=false. The description adds no extra behavioral context beyond the instruction to include a conversation array, which is more of a usage guideline than a transparency disclosure. There is no contradiction.

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 concise sentences. The main purpose is front-loaded, and the additional guidance about the conversation array is efficient. No filler or 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 simple bug-report tool with three parameters and no output schema, the description covers the essential usage. It could mention response behavior, but the annotations and simple nature make it reasonably 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?

With 0% schema coverage, the description must compensate. It explains the 'conversation' parameter as 'with recent messages,' but leaves 'message' and 'context' to be inferred from the tool's purpose. This is partially helpful but not comprehensive.

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 ('Report') and the target resources ('bug, missing feature, or send feedback'). It is immediately distinguishable from the unrelated sibling tools like authenticate or 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 gives clear context about when to use the tool (for reporting bugs, missing features, or feedback). It also provides a usage hint ('Include the conversation array with recent messages') but does not explicitly mention exclusions or alternatives, which is acceptable given the unrelated sibling set.

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-read behavior is covered. The description adds the 'current' qualifier and specifies the version scope, but does not add further behavioral context such as output format or caching 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 immediately states the tool's action and object. No wasted words.

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 version-inspection tool with strong safety annotations, the description is entirely sufficient. No output schema exists, but the expected information is clear from the description alone.

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. Baseline 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 uses a specific verb ('Show') and clearly identifies the resource ('current MCP platform and adapter versions'). This is unambiguous and distinct from sibling tools like authenticate, marketplace, or 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?

No guidance is provided on when to use this tool versus alternatives. While the purpose is obvious, the description does not state any context, exclusions, or relationship to 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 already declare this read-only, non-destructive, and idempotent. The description adds what the return value contains but does not disclose additional behavioral traits such as potential latency, whether it reflects live status, or any prerequisites beyond what annotations cover.

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 primary purpose and enumerates the return contents without extraneous detail. Every clause adds meaningful 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, parameterless info tool with no output schema, the description adequately covers what is returned and the scope of the toolkit state. It could arguably mention that the data reflects current live connections, but overall it is complete for 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 zero parameters, so the schema provides no semantic information beyond an empty object. Per the baseline for 0 params, the description does not need to compensate, and it focuses on return value rather than input 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 returns the current toolkit state, listing the specific contents (installed MCPs, connection status, accounts, and catalog tool counts). This distinguishes it from sibling tools like show_version by providing a detailed scope of information.

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 for checking toolkit state and what components are available, but does not explicitly mention when to prefer this over alternatives like show_version. It provides clear context but lacks exclusion guidance.

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