Tribunal TRT11: Consulta Processual

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

The description discloses the tool's behavior beyond the annotations: it explains that calling with a token authenticates for a session, while calling with no args returns a link. It also mentions that a permanent config approach results in a non-expiring connection, implying a persistent side effect. The description does not explicitly state error handling or rate limits, but it provides sufficient behavioral detail for an authentication tool, and it is consistent with the annotations (idempotentHint true).

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 fairly concise, consisting of three sentences that clearly separate the main steps and options. It avoids unnecessary fluff but contains some redundancy (e.g., explaining both methods in detail). It is well-structured with clear phrases like 'Best:' and 'Or paste it here,' making it easy to follow despite being a bit 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?

Given the tool's simplicity (one optional parameter) and lack of output schema, the description provides adequate context: it mentions the target environment (IDE agents), the authentication flow, and how to use the parameter. It does not elaborate on return values or error states, but those are not specified in the schema and are not critical for an authentication tool. The description is complete enough for an agent to 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 sole parameter 'token' is described in detail: it is optional, and the description explains that providing it performs a session-only login, while omitting it returns a link. This adds substantial meaning beyond the schema's basic 'string, not required' definition, fully covering the parameter's semantics 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: authenticating a user for IDE agents. It explains both options for login (permanent via config header or session-only via token) and distinguishes itself from sibling tools like 'connect' and 'marketplace' by focusing on authentication. The verb 'authenticate' is expanded with concrete instructions, making the purpose 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?

The description provides explicit usage instructions, contrasting the two authentication methods and when to use each: adding the token to the server config for a permanent connection versus passing the token as an argument for a session-only login. It also explains how to obtain the token (call with no args to get a link). This gives clear guidance on when and how to invoke the tool, effectively covering the 'when to use vs. alternatives' aspect.

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, idempotentHint, and destructiveHint, so the description's main contribution is explaining response behavior: authenticated:true with empty pending[], plus connect_url for the toolkit and per-install URLs when credentials are missing. This adds useful context beyond the annotations, though partial connection states are not explicitly addressed.

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 compact sentences, front-loads the return intent, and contains 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 zero-parameter status tool with no output schema, the description covers the main success case and the missing-credentials case, including URL details. It is slightly incomplete because it does not describe partially connected states or explicit error/edge-case behavior.

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 schema, so the baseline of 4 applies. There is no parameter semantics burden for the description to carry.

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, providing a specific verb and resource. It also distinguishes itself from sibling tools like authenticate by describing a status-checking behavior rather than an action that changes authentication 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 gives clear contextual guidance by explaining what happens when all providers are connected versus when credentials are missing, implying this is the tool for inspecting connection state. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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 goes far beyond annotations by disclosing key behaviors: invoke runs one-off even if MCP not installed, returns connect/checkout links when needed, and writes require owner/admin. It also explains the prompt library feature. No contradiction with annotations 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 long but well-structured: it starts with purpose, then core flow, key nuances, individual actions, and prompt library. Every sentence adds value; the length is justified by the tool's complexity. It could be slightly tighter but remains focused.

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 actions and 23 parameters, the description covers all major aspects: core flow, install vs. invoke, auth requirements, payment flows, installed status flags, and the prompt library. It addresses edge cases (connect link, checkout link) and provides enough detail to operate 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 coverage, the description compensates heavily by explaining the `action` enum and the purpose of key parameters (mcp_id, tool_id, arguments, prompt fields). It doesn't exhaustively detail every parameter, but it provides enough context to infer usage for the main flow.

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 tool as the official mcp.ai marketplace, explaining it is both the catalog and the runtime for MCPs. It immediately outlines the core flow (search → describe → invoke) and differentiates its roles from sibling tools, leaving no ambiguity about its purpose.

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?

Explicit guidance is provided: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', and specific actions (list_tools, subscribe/cancel, report_bug, request_mcp) are clearly scoped. It also notes auth requirements for writes, giving clear when-to-use and when-not-to-use instructions.

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 provide readOnly=false, destructive=false, and idempotent=true, but the description adds no behavioral context beyond the reproduction angle. It does not explain what happens after reporting, whether a ticket is created, or any side effects. There is no contradiction with annotations, but no meaningful extra disclosure.

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 words. It is concise and readable, though it could have been slightly more structured by separating the purpose from the instruction. Overall, it 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?

With no output schema and only 3 simple parameters, the tool is not highly complex. However, the description omits what the caller should expect after reporting (e.g., confirmation, ticket ID) and does not clarify how to format the conversation array. It covers the basic purpose but leaves important context 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 compensate. It explains the 'conversation' parameter as an array of recent messages, but the schema declares it as a string (default '[]'), which is ambiguous. It provides no guidance for the required 'message' parameter or the 'context' parameter, leaving the most important fields underspecified.

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 as a bug/feedback reporting tool and the main action (report). It distinguishes itself from sibling tools like authenticate or marketplace, but the title from annotations also provides clarity. It does not explicitly contrast with another feedback tool, but the purpose 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?

The description states when to use the tool ('Report a bug, missing feature, or send feedback') and gives a specific usage instruction ('Include the conversation array with recent messages for reproduction'). It does not mention when not to use it or produce alternative tools, so it falls short of a 5.

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 safety behavior. The description adds no extra behavioral context beyond what annotations provide, but it remains consistent with 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 a single sentence, efficient, and front-loaded. There is no wasted wording or redundant 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?

For a trivial version-info tool, the description is complete. It states exactly what it returns (platform and adapter versions) and requires no further context. No output schema exists, but the return value is obvious from the description.

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 schema coverage is 100% (trivially). The description adds no parameter information, but with no parameters, the 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 'Show the current MCP platform and adapter versions' with a specific verb and resource. It is distinct 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 description does not provide explicit guidance on when to use this tool or when to prefer alternatives. Usage is implied (checking version info) but not stated, so it falls into the 'implied usage' category.

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 description does not need to repeat safety properties. It adds useful context about what data is returned, but it does not disclose any additional behavioral traits like rate limits, system side effects, or the format of the response. Given the annotations cover the main expectations, this is adequate but not rich.

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 leads with the action and then enumerates the key components of the returned state. There is zero wasted wording, and the information is front-loaded. It perfectly balances brevity with informativeness.

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, no output schema, read-only), the description covers all essential aspects: what it returns and the granularity of the information. It does not include details on pagination, error handling, or unavailable data, but these are not critical for a status/state retrieval tool. The coverage is complete enough for an agent to invoke it correctly and understand the response.

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 parameters, the schema coverage is 100% vacuously, and the description successfully focuses on the output semantics. It describes what the tool returns in enough detail that an agent can infer the shape of the data (installed MCPs, their status, connected accounts, catalog tool counts) without needing an output schema. This exceeds the baseline for parameterless 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 returns the current toolkit state with explicit details (installed MCPs, connection status, accounts, catalog tool counts). The verb 'returns' and resource 'current toolkit state' are specific, and it distinguishes itself from sibling action tools like authenticate/connect and even show_version by listing the exact data returned.

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?

There is no guidance on when to use this tool versus alternatives like show_version or how it fits into a workflow. While its purpose is clear, the description does not mention when it is appropriate to call or any prerequisites. This is a notable gap given the presence of multiple information-oriented 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context about the LGPD data controller role, the public nature of the data, and the payment requirement—useful behavioral disclosures 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 a single paragraph containing several pieces of information: the tool's purpose, the payment model, and LGPD compliance details. It's fairly concise but the structure mixes purpose with contractual notes, which could be separated for clarity. No waste, but order could be improved.

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 (process consultation), and annotations cover safety aspects, so the description needn't explain those. However, given that no output schema exists, the description doesn't mention what the response looks like or what data fields are returned. Still, it provides enough for a simple query tool with good annotations.

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%: the description doesn't explain how to use 'numero_processo' or 'grau' parameters. Since there are only 2 parameters and detailed format guidance is essential for a Brazilian legal process number, the lack of parameter info is 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 that this tool consults procedural information from the TRT11 tribunal, and names it a 'Consulta Processual'. While it doesn't detail the specific resource (e.g., list vs. detail), it distinguishes itself from sibling tools that cover authentication, connection, marketplace, and general toolkit 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 includes usage context: it's paid per query with prepaid credit, hosted by the platform without platform credentials, and does not provide confidential data. However, it doesn't explicitly state when to use this tool over alternatives or mention the 'grau' parameter for filtering, leaving some ambiguity about when to invoke this vs. other consultation tools.

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