Tribunal TJGO: Nada Consta

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

The description discloses key behaviors: it opens a browser for login, returns a link when called with no args, and accepts a token for session-only login. It also mentions the token is a JWT. Annotations indicate idempotentHint=true and destructiveHint=false, which align with the description (no destructive actions, repeated calls are safe). The description adds context about the permanent vs session-only distinction, which is beyond the annotations. However, it doesn't mention any side effects like rate limits or auth requirements for the tool itself.

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 with the tool's purpose. It uses a colon to separate the main purpose from usage details. The two sentences are information-dense but not overly long. It could be slightly more structured (e.g., bullet points for the two modes), but it's efficient and readable.

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 (one optional param, no output schema), the description is fairly complete. It covers the two usage modes, the recommended permanent setup, and the session-only alternative. It doesn't explain what happens after successful authentication (e.g., what the tool returns), but that's not critical for a simple auth tool. The sibling tools are diverse, and this description is sufficient for an agent to decide when to use it.

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 one optional parameter 'token' with no description. The description explains that 'token' is a JWT to be pasted for session-only login, and that calling with no args returns the login link. This adds significant meaning beyond the bare schema. Since schema coverage is 0%, the description fully compensates for the parameter's purpose and usage.

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 IDE agent by logging in via browser and obtaining an access token. It distinguishes between two modes (permanent config vs session-only) and mentions the target audience (MCP.AI for IDE agents). However, it doesn't explicitly contrast with sibling tools like 'connect', which might also relate to authentication, so it's not fully differentiated.

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 (to log in and get a token), how to use it (with or without a token argument), and recommends the best practice (adding to config for permanent connection). It also implies when not to use it (if you already have a token, you can just add it to config). This is clear and actionable.

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 disclose readOnly, idempotent, non-destructive behavior, and the description adds useful behavioral context beyond that: conditional return states, the authenticated flag, pending array, and URL field semantics. It does not contradict the annotations, and it provides a meaningful picture of what changes are not made and what outcomes can be expected.

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 concise sentences that immediately state the core purpose and then explain the key conditional outputs. Every clause adds meaningful detail, and there is no filler or repetition of the tool name.

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?

Without an output schema, the description carries the burden of explaining return values, and it covers the main success state and the missing-credentials state, including URL fields and authenticated flags. It is reasonably complete for a zero-parameter status/checking tool, though it could mention partial credential states or error conditions explicitly for full completeness.

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 input schema is empty and there is no parameter complexity to clarify. Per the baseline for zero-parameter tools, a score of 4 is appropriate since the description does not need to explain nonexistent parameters and the schema fully covers this axis.

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 the tool returns connection status and URLs, using the specific verb 'Returns' with a defined resource. It differentiates itself from sibling tools like authenticate or marketplace by focusing on status discovery, not performing authentication or marketplace 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: it describes what happens in different connection states, such as returning authenticated:true when all providers are connected and connect_url when credentials are missing. However, it does not explicitly say when to choose this tool over alternatives like authenticate or toolkit_info, nor does it state exclusions or prerequisites.

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 correctly flag with readOnlyHint=false that this tool writes, which the description acknowledges. It then substantially exceeds baseline by detailing: the one-off nature of invoke (runs 'pontualmente' without adding to the toolkit), the connect link for auth requirements, the checkout/top-up link for empty wallet scenarios with a retry suggestion, and the admin/owner permission requirement for writes. Also names specific flags like installed_in_toolkit vs installed_in_workspace that the agent will see in search results.

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, front-loaded, and information-dense. However, at this length a single-paragraph format is strongly felt — there are no bullets or line breaks for the prompt actions, no bold for action names, and the prose style obscures what could be skimmable distinctions (two sentences explain the pricing behavior, which is critical but buried).

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 14 distinct actions and zero output schema, this description is remarkably complete: it covers capability discovery, installation semantics, auth, payment, permissions, list state, the prompt library, and even edge handling for installed vs. not-installed MCPs, plus a robust single example of the billing retry loop.

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 zero schema description coverage, this dimension bears the full documentation burden, and the -described flow does not map any of the 23 parameters to actions. An agent reading this description would not know that 'limit' is the pagination control, that 'arguments' contains a JSON string to pass to invoke, or that 'message' is destructured based on the current action. The description repeatedly refers to parameters that are never explicitly enumerated (e.g., 'search_prompts finds one, get_prompt returns its full text') without explaining how those are encoded in 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 opens by identifying 'mcp.ai marketplace' as a catalog plus execution environment, then illustrates concrete query types ('find an MCP that does X', 'consulta um CPF'). The three-step core flow (search -> describe -> invoke) makes the tool's aggregate purpose unambiguous. Minor point off: the description covers multiple sub-capabilities (prompt library, billing) under one tool name, so the singular purpose is slightly diffused.

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?

Explicitly states when to use 'invoke' vs 'install': 'prefer invoke for single/occasional use' versus 'use install only to make an MCP PERMANENT'. Also names the alternative for capability discovery ('list_tools lists what is callable right now') and explicitly defines the search-then-describe-then-invoke sequence, which directly prevents misuse.

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 the tool as idempotent and non-destructive, so the description does not need to restate those. It adds the useful context that conversation messages are needed for reproduction, but does not disclose what happens after submission or whether any confirmation is returned.

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 purpose, followed by a single actionable instruction. No filler or redundant restatement of the tool name.

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/report tool with no output schema, the description covers the core purpose and the key reproduction input. It is slightly incomplete in not describing expected response or confirmation behavior, but overall adequate.

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 only clarifies the conversation parameter (calling it an 'array' even though the schema types it as a string), leaving the required 'message' and optional 'context' parameters unexplained.

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 ('Report') with explicit object types ('bug, missing feature, or send feedback'), making the tool's purpose immediately clear. It is also distinct from the unrelated 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 clearly states when to use the tool (bug, missing feature, feedback) and gives a concrete instruction to include the conversation for reproduction. It does not mention alternatives or exclusions, but no competing sibling tool exists.

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, covering the safety profile. The description adds only the 'current' qualifier, indicating a state read, but no additional behavioral context such as return format or 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?

The description is a single, front-loaded sentence with no filler. Every word contributes to the tool's purpose, making it maximally 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?

For a simple version-check tool with no parameters and no output schema, the description fully covers the tool's purpose. No additional context is necessary for an agent to select and invoke it 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 tool has zero parameters and an empty input schema, so there is nothing for the description to explain. The baseline for 0 params is 4, and the description does not need to compensate for any schema gaps.

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 a clear resource ('current MCP platform and adapter versions'), making the tool's function unambiguous. It distinguishes itself from siblings like 'toolkit_info' by focusing specifically on version 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?

No explicit when-to-use or alternative guidance is provided. However, the tool's purpose is self-evident from the name and description, so usage is implied rather than absent.

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. The description adds valuable context about the exact information returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the bare annotations. No contradictions exist; it reinforces the read-only nature without redundancy.

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 action. Every element is informative: the verb, the subject, and the enumerated contents. There is no fluff, repetition, or unnecessary detail.

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) and the rich annotations, the description fully covers what the tool does and what it returns. It explicitly lists the four key components of the state, which is sufficient for an agent to understand the tool's role without an output schema.

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 carries no parameter burden. According to the rubric, the baseline for 0 params is 4. The description correctly omits parameter details, and there is nothing to add beyond what the empty schema already shows.

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 exact purpose: returning the toolkit state with specific details (installed MCPs, connection status, accounts, catalog tool counts). It uses a specific verb ('Returns') and resource ('current toolkit state'), distinguishing it from 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 clear context on what the tool outputs (a state summary), implying it is used to inspect the toolkit's current configuration and connectivity. It doesn't explicitly compare to alternatives, but the nature of the tool makes its usage obvious, and it avoids misleading cues. No alternatives are named, but the context is sufficient.

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?

Beyond the read-only and idempotent hints, the description discloses additional behavioral aspects: it is hosted by the platform, requires no platform credentials, involves paid queries, and clarifies data sensitivity (non-confidential) and LGPD compliance. This goes 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?

The description is moderately concise, containing multiple sentences with legal jargon. It is not overly verbose but could be streamlined. The structure is clear, starting with the purpose and then adding details, but it is not a model of conciseness.

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 gives useful context about the source and payment model, but lacks details on how to specify the query (parameter usage) and what the response looks like. Given the schema's simplicity, some gaps remain, but the description is not entirely inadequate.

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 provides no explanation of the parameters (cpf, cnpj, nome, etc.) or how they are used. With zero schema coverage, the description completely fails to compensate, leaving parameter semantics entirely undefined.

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 'Nada Consta' query from the TJGO court, specifying it is an official source consultation. This is a specific and unambiguous purpose that distinguishes it from the 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 provides context about payment (prepaid credits) and the official nature of the data, but does not explicitly mention when to use this tool versus alternatives or when not to use it. 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.