MPT RS: Certidão Negativa de Feitos

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

Annotations indicate idempotentHint=true but no destructive or read-only hints, which is neutral. The description adds context on how the authentication can be made permanent (config header) or session-only, and mentions that the token is a JWT, providing extra behavioral detail. However, it doesn't explicitly state that calling the tool opens a browser or that the token has expiration, but it does imply a flow. Given the annotations are sparse, the description provides additional value but could elaborate on the login link 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 concise—two sentences—and front-loads the essential purpose. Every sentence earns its place: it gives context for IDE agents, explains the permanent and session options, and specifies the call patterns. No fluff 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?

Given the tool's complexity (an authentication flow with two modes), the description adequately covers the necessary steps for an agent to guide the user. The schema is minimal with no output schema, but the description sufficiently explains the process, including the need to copy the token and the distinction between permanent and session (URL indication). This is complete for practical use.

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 only one optional parameter and schema description coverage at 0%, the description compensates by explaining that the 'token' parameter should be a JWT pasted by the user, and that calling with no args returns a link. This adds meaning beyond the bare schema, which only defines the property as a string. The description clarifies the parameter's role, so a high score is justified.

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 IDE agents by logging in through the browser and obtaining an access token. It specifies the verb 'authenticate' and the resource (the AI service), and it distinguishes itself from siblings by focusing on the login process, whereas siblings like 'connect' and 'marketplace' suggest different concerns.

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: it explains when to use the tool (for login via browser), and offers two distinct usage modes—permanent configuration via header in config, or session-only login by pasting the token. It also instructs calling with no args to get the link, making the when-to-use crystal 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=true, idempotentHint=true, and destructiveHint=false, so the tool is safe and non-mutating. The description adds behavioral context by explaining the two possible states (all providers connected vs. missing credentials) and what the response includes (authenticated, pending[], connect_url, per-install URLs). This goes 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?

The description is two sentences, front-loaded with the primary purpose, and provides essential detail about the two states without any fluff. Every sentence 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?

Given the tool has no parameters and no output schema, the description is complete enough. It explains the return values in both scenarios, which is sufficient for an agent to understand what to expect. It could mention that it's a read-only check, but annotations already cover that.

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 doesn't need to explain parameter semantics. The schema coverage is 100% (vacuously), and the description focuses on the output behavior, which is appropriate. Baseline 4 for zero-param 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 clearly states the tool's purpose: 'Returns connection status and URLs.' It specifies the resource (connection status) and the action (returns), and distinguishes itself from siblings like 'authenticate' and 'toolkit_info' by focusing on connection status and URLs.

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 when to use this tool: to check connection status and get URLs. It implies usage for verifying connectivity, but does not explicitly state when not to use it or mention alternatives. However, given the sibling tools, the purpose is distinct enough.

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?

Given the annotations are minimal (readOnlyHint:false, openWorldHint:true, no details on destruction or idempotency), the description carries full weight and delivers: it explains what happens when credentials are missing (connect link), what happens with a zero wallet (checkout link, user opens, then retry), which operations are writes requiring owner/admin, and clarifies that invoke runs the tool one-off 'without adding the MCP to the toolkit and without bloating the tool list'.

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?

It's a single dense wall of text, but every 3-10 word chunk earns its place: 'pontualmente (one-off)', 'the user opens it, then you retry', 'which is about ready-made prompt TEXT rather than MCPs'. Some structure (bullets, dashes) would improve quick scanning, and 'pontualmente' could confuse non-Portuguese readers (though it's arguably intentional given the 'consulta um CPF' example hints at a PT-BR user base). That said, the density is information-rich rather than bloated — hard for a description covering 14+ actions.

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 fair assessment — the schema is massive (23 params, no required params, no enum hints beyond action), there's no output schema, and no nested objects. The description covers the full lifecycle while remaining actionable about what the agent must NOT know: how to handle non-install edge cases, retry semantics, which actions need mcp_id being contextualized into core ('describe returns one MCP's full profile'), and permission scoping (installed vs owner/admin). It's a complete operational manual for an unusually complex 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?

With schema description coverage at 0%, the description is the sole interpreter of the 23-parameter schema, and it more than compensates. It introduces the `action` property semantics that aren't self-evident from the schema alone (list of 14 actions, each with its own required fields: mcp_id for search/describe/invoke, tool_id+arguments for invoke, prompt_* fields for the prompt library, cancel_reason/comment for cancel). The description explains the actual error-handling flow (invoke without install tricks the static schema would never reveal). The agent can meaningfully map parameters to workflows from the description alone.

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 specific verb-action pairs ('search discovers MCPs by intent', 'invoke RUNS that tool', 'install only to make an MCP PERMANENT') and grounds them with concrete examples ('find an MCP that does X', 'consulta um CPF'). It clearly distinguishes the two ecosystems (marketplace actions vs prompt library) and differentiates the main flows from siblings via explicit naming (`report_bug`, `toolkit_info`). It would earn a 5 except the overloaded 'marketplace' name is never directly defined in a single clause, and the tool is so broad it's more of a hub than a single-purpose tool.

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 usage guidance is exemplary: it explicitly contrasts 'prefer invoke for a single/occasional use' with 'Use install only to make an MCP PERMANENT', explains when NOT to use it ('only if the MCP needs a credential... invoke returns a connect link'), and covers the auth/payment retry flow. It also tells the agent when to fall back to `request_mcp` ('asks us to build a NEW MCP when nothing fits'). This is when-to-use vs alternative guidance done at the highest standard.

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 safety profile is clear. The description adds valuable behavioral context: it's hosted by the platform, requires no platform credentials, charges per query with prepaid credits, and clarifies data privacy (client is data controller, LGPD compliance). This goes beyond annotations and is useful for the agent.

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, reasonably concise, and front-loaded with the main purpose. It includes necessary legal and payment context. It could be slightly more structured, but it's not verbose. Every sentence adds 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 has no output schema and no parameter documentation, the description should provide more detail on what the query returns and how to use the parameters. It explains the source and legal aspects but lacks operational details like input format (e.g., CPF/CNPJ format) or output structure. For a tool with 2 parameters and no output schema, this is a moderate 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%, and the description does not explain the parameters 'cpf' and 'cnpj' at all. The schema only shows they are strings, with no format or meaning. The description mentions the certificate but doesn't clarify that cpf/cnpj are the identifiers to query. This is a significant gap; the description should compensate for the lack of schema documentation but doesn't.

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: it queries the MPT RS (Ministério Público do Trabalho do Rio Grande do Sul) for a 'Certidão Negativa de Feitos' (negative certificate of court records) from an official source. It specifies the resource (certidão) and the action (consultar/query). It distinguishes from siblings by being the only tool related to MPT RS queries, though it doesn't explicitly name alternatives.

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 when to use the tool: to consult official Brazilian sources for information available to citizens, not confidential data. It also mentions payment via prepaid credits. However, it does not explicitly state when NOT to use it or mention alternative tools, though the sibling list shows no similar tools. The guidance is implicit rather than 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 indicate the tool is idempotent and non-destructive. The description adds that the conversation array should be included for reproduction, which is useful input context, but it does not explain what happens after submission or any other behavioral details.

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 purpose, and includes a practical instruction about the conversation array. Every sentence adds value 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 simple feedback tool, the description is acceptable but not rich. It omits clarification for the `context` parameter and does not mention expected outcomes, but annotations cover safety and the purpose is clear enough given the low complexity.

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 the conversation array for reproduction but does not clarify the semantics of `message` or `context`. This is only partial compensation for three undocumented 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 purpose: 'Report a bug, missing feature, or send feedback.' It is more specific than the title because it expands the scope beyond bugs. It is clearly differentiated from the unrelated sibling tools, though it does not explicitly name alternatives.

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 usage context is implied: use this tool when the user wants to report a bug, missing feature, or provide feedback. However, there is no explicit guidance on when not to use it or what alternatives might be better.

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 specificity by naming the exact contents ('MCP platform and adapter versions'), but does not introduce any contradictory information. It complements the annotations sufficiently.

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 directly conveys the tool's purpose without extraneous words or complexity. It is perfectly structured for a trivial operation.

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 and lack of output schema, the description fully covers its purpose and expected result. It states what will be shown (versions) without needing to elaborate on return types or side effects.

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 schema coverage is effectively 100%. The description adds no parameter details because none exist; there is nothing to misinterpret or require clarification.

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: showing the current MCP platform and adapter versions. It uses a specific verb ('show') and resource ('versions'), making it unambiguous and distinct from other 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 implicitly indicates when to use the tool—when version information is needed. It does not explicitly mention alternatives or exclusions, but the trivial nature of the operation makes the usage context obvious. A slightly higher score would require an explicit alternative comparison.

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 and idempotentHint=true, so the safety profile is known. The description adds value by specifying exactly what state is returned (connection status, accounts, catalog tools), which is useful behavioral context beyond 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?

A single, front-loaded sentence that packs meaningful details without fluff. It clearly states the action and the returned content, with 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?

Given no output schema and no parameters, the description must convey the return shape. It does so thoroughly, detailing the components of the toolkit state (installed MCPs, connection status, accounts, catalog tool counts), making the tool's behavior and outputs clear.

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?

There are no parameters, so the schema is trivially covered. The description doesn't need to explain parameters. Baseline for 0 params is 4, and no additional information is required.

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, enumerating specific elements (installed MCPs, connection status, accounts, catalog tool counts). This verb+resource structure distinguishes it from siblings like connect or authenticate, which handle different actions.

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 to inspect the toolkit state, which is distinct from other siblings. It doesn't explicitly mention when not to use it or name alternatives, but the context is evident given the sibling names and the read-only nature.

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