MPT GO: Certidão Negativa de Feitos

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

Annotations indicate idempotentHint=true and destructiveHint=false, which are already disclosed. The description adds valuable behavioral context: it explains that the tool does not require the token to be passed every time (config option for permanent connection), that it can be called with no args to get a link, and clarifies the session vs permanent distinction. This goes beyond the annotations' basic 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 a single, moderately long paragraph but is front-loaded with purpose and includes actionable instructions. It is slightly dense but every sentence adds value, explaining the flow and both usage modes. No redundancy, though it could be split into bullet points for readability.

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 (multiple authentication flows), the description covers all needed aspects: how to log in, obtain token, and use it for permanent or session-based access, including the no-arg call for the link. There is no output schema to worry about, and the description is sufficient for an agent to call 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?

The schema defines only one property (token) with no description, and schema coverage is 0%. The description compensates by explaining the token parameter: it should be a JWT string pasted by the user for session-only login, and that omitting it triggers a different behavior (getting a login link). This adds significant meaning beyond the 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's purpose: to authenticate an MCP.AI IDE agent by logging in and obtaining an access token, with two methods of use. It distinguishes itself from siblings by focusing on login/authentication, while siblings like 'connect' and 'marketplace' serve different functions, though no explicit sibling differentiation is provided.

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 explicit usage guidance: best practice is to add token to config for permanent connection, or paste token for session-only login, and instructions for calling with or without arguments. It also tells users when to use each approach, clearly differentiating between permanent and session-based 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds behavioral detail beyond annotations by specifying return values (authenticated:true, empty pending[], and connect_url variants). This gives agents insight into what to expect without side effects.

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. Every sentence adds value: the first explains what is returned, the second details conditional outputs. No fluff or repetition.

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 tool with no output schema, the description covers the two primary states (connected and missing credentials) adequately. It explains the key response fields (authenticated, pending, connect_url, per-install URLs) and is complete for the tool's 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 0 parameters, so baseline is 4. The description does not need to compensate for undocumented parameters, and it appropriately focuses on the tool's outcome rather than any inputs.

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. It distinguishes itself from siblings like 'authenticate' by focusing on status reporting rather than performing authentication. The verb 'Returns' with a specific resource 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?

Provides clear context on when results differ (all connected vs credentials missing) and what the response includes in each scenario. While it doesn't explicitly name alternatives or exclusions, the read-only nature and return details imply it should be used for status checking. No explicit when-not-to-use guidance, but the context is sufficient for typical agents.

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 important behaviors beyond annotations: invoke runs tools one-off even when not installed, credential/payment gaps return connect/checkout links, writes require workspace owner/admin, and prompt links open without login. These details add substantial context and do 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 long, but it is dense and well-structured: it front-loads the core flow, then covers key edge cases, permissions, and the prompt library. A few clauses could be tightened, but the length is largely justified by the tool's multi-action complexity.

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 complex 23-parameter dispatcher with no output schema, the description is remarkably complete. It covers the search→describe→invoke flow, install vs invoke semantics, auth/billing behaviors, prompt-library usage, and fallback actions, leaving the agent well-equipped to select and invoke the correct action.

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 compensates by explaining the action parameter's enum values and the roles of mcp_id, tool_id, arguments, prompt_slug, and prompt_vars. It does not define every one of the 23 parameters, but the core flow and prompt-library sections give enough semantic grounding for most fields.

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 resource (the mcp.ai marketplace) and its dual role as a catalog and execution layer. It explicitly names the core actions (search, describe, invoke) and distinguishes the tool from siblings by framing it as the in-platform way to discover and run MCPs.

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: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and 'list_tools lists what is callable right now'. It also directs users to request_mcp when nothing fits and separates the prompt-library actions from MCP actions.

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, destructiveHint=false, so the tool is a safe read operation. The description adds that it's hosted by the platform, requires pre-paid credit per query, and that it doesn't require platform credentials. It also mentions LGPD compliance. There's no contradiction. It doesn't detail return format or error handling, but given the annotations, the description adds some value beyond them.

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 about three sentences, but it's somewhat verbose with legal and compliance details that might be necessary but could be condensed. It's front-loaded with the main purpose, but the LGPD mention and controller clarification add bulk. It's not overly long, but it could be more concise.

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 2 parameters and no output schema. The description gives background on legal aspects and payment, but it doesn't explain what the result looks like or whether both parameters are alternatives. It doesn't specify that you must provide one identifier. Given the complexity, it's adequate but has gaps in parameter explanation. The lack of output schema means the description could have described the return format, but it's not mandatory if the result is obvious.

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. The description does not explicitly explain these parameters; it mentions consulta (consultation) but doesn't say that you need to provide either CPF or CNPJ. With 0% schema description coverage, the description should compensate by explaining parameter usage, but it doesn't. It's not completely absent, as the context of consulting official records implies you need an identifier, but it's insufficient.

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 that this tool performs a consultation of a negative certificate of records (Certidão Negativa de Feitos) from official sources. It distinguishes it from potential siblings by specifying it's for MPT GO and that it's a query, not a modification. However, it doesn't explicitly contrast with other similar query tools, but given the sibling list includes generic tools like authenticate, it's clear enough.

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 explains that the tool is for consulting official Brazilian sources, available to citizens, and that it's not confidential data. It also clarifies payment with pre-paid credit and that the client is data controller under LGPD. It doesn't explicitly say when NOT to use it, but it sets clear context. The phrase 'Consulta informação de fontes e órgãos oficiais brasileiros' implies use for official background checks. No explicit exclusions, but the context is adequate.

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=false, destructiveHint=false, and idempotentHint=true, so the safety profile is known. The description adds value by noting the need for conversation data, but it does not elaborate on side effects, response handling, or privacy concerns. With annotations present, the additional disclosure is adequate but minimal.

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 contains no extraneous words. Every sentence contributes meaning, and the structure is ideal for quick comprehension.

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 (3 parameters, no output schema), and the description, combined with annotations, provides a basic understanding. However, the lack of explanation for the 'context' parameter and no mention of what happens after submission leaves some gaps. Overall, it is minimally complete for a straightforward reporting tool but could be 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?

Schema description coverage is 0%, so the description must compensate for parameter meanings. It explicitly explains the 'conversation' parameter as an array with recent messages for reproduction, but does not explain 'message' (though its role as the report content is implied) or 'context' (which remains vague). Thus, only one of three parameters is clearly clarified, leaving 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 a specific verb ('Report') and resource ('a bug, missing feature, or feedback'), making the tool's purpose unambiguous. It distinguishes itself from siblings like authenticate or show_version, which serve entirely different functions.

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 explicit instruction to include the conversation array for reproduction, which is a concrete usage guideline. While it does not mention alternatives or exclusions, the sibling tools are clearly unrelated (auth, version, marketplace), so there is no ambiguity about when to use this tool.

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 establish read-only, idempotent, and non-destructive behavior. The description adds the specific scope (platform and adapter versions) but does not disclose additional behavioral traits such as output format, whether versions are returned as strings, or any error conditions. 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, front-loaded sentence with no wasted words. It immediately states the action and target 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?

This is a simple, no-parameter, read-only informational tool. The description fully covers the tool's purpose, and the annotations cover safety expectations. No output schema exists, but for a simple version query the description is 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 and the input schema is fully self-explanatory (100% coverage). With no parameters, the description does not need to add parameter semantics; baseline for zero-parameter tools is 4.

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 a concrete resource ('current MCP platform and adapter versions'). It clearly differentiates this from sibling tools like authenticate, connect, and report_bug, which serve different purposes.

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 use case is implied: invoke when the agent needs platform or adapter version information. However, no explicit guidance is given about when NOT to use it or how it compares to sibling tools like toolkit_info, which might also provide version-related context.

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 readOnlyHint, idempotentHint, and destructiveHint, covering side effects. The description adds value by specifying what information is returned, making the behavior transparent. While it doesn't explicitly say 'does not modify state,' the 'returns' phrasing combined with annotations provides sufficient transparency. Minor credit for not over-explaining.

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 front-loads the action ('Returns') and clearly enumerates the key elements. There is no fluff, redundancy, or excessive detail. It is well-structured and easy to parse, making it ideal for quick understanding by an agent.

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 a good overview of the output content (installed MCPs, connection status, accounts, catalog tool counts) without an output schema. It is sufficient for an agent to understand what to expect. However, it does not specify the format (e.g., whether it's a list, nested objects, or a summary), but this is not critical for a simple read-only tool. Given the low complexity, the description is nearly 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 tool has no parameters, and the schema is empty, so there is nothing to explain. The description does not mention parameters because none exist. Since schema coverage is complete (100%), a baseline score of 3 is appropriate, and no additional parameter information 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 clearly states what the tool does: it returns the current toolkit state and lists the specific components included (installed MCPs, connection status, accounts, catalog tools). The verb 'Returns' is precise, and the resource is well defined. This distinguishes it from sibling tools like 'connect' 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?

The description does not explicitly state when to use this tool versus alternatives. It is a straightforward getter, but there is no guidance on scenarios (e.g., 'Use this to check status before connecting') or comparisons with sibling tools. The purpose is clear, but the usage context is implied rather than stated.

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