Tribunal TRT1: Consulta Processual

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

Beyond the annotations (idempotent, non-destructive), the description discloses meaningful behavior: it can establish a permanent non-expiring connection via config header or a session-only login. This adds valuable context that annotations alone do not provide.

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 long but well-structured: it starts with the core purpose and then presents two usage options. Every sentence adds necessary information, though it could be slightly tightened without losing clarity.

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 authentication tool with no output schema, the description is self-contained. It explains the entire flow—browser login, token retrieval, config vs. session modes, and no-args behavior—so an agent has enough context 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 schema only lists an optional string token with no description. The description fully compensates by explaining the token is a JWT from the browser and noting that calling with no arguments returns the login link, giving complete parameter meaning.

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 explicitly states the tool's function: authenticate IDE agents via browser login and token copy. It uses a specific verb ('log in') and resource ('access token'), making the purpose unmistakable and distinct from vague tool names.

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 two clear usage paths (permanent config header vs. session-only token) and specifies the intended audience (IDE agents like Cursor). It gives clear context but does not explicitly compare with sibling tools like 'connect', 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?

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds valuable return-state details (authenticated:true with empty pending[] when all connected, and connect_url when credentials missing), which enriches understanding beyond the annotations without contradicting 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 two sentences: the first states the core function, and the second covers conditional outputs. No fluff, front-loaded with the main action, and every word 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?

For a zero-parameter, read-only status tool, the description fully covers observable behavior, including both success and partial-failure states. Since there is no output schema, explaining the return values is essential and done well.

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 baseline of 4 is used. The description correctly focuses on behavior rather than parameters, 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 the tool 'Returns connection status and URLs' with a specific verb and resource, and the conditional behaviors (authenticated:true vs connect_url) distinguish it from sibling tools like 'authenticate' or 'toolkit_info'. This is a specific, unambiguous 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?

The description implies this is for checking connection status and handling missing credentials, but it does not explicitly state when to use this over alternatives or mention any exclusions. There is no direct comparison to siblings like 'authenticate', so usage context is only implied.

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?

Goes well beyond the basic annotations. Discloses that invoke works even without installation, returns connect/checkout links, requires owner/admin for writes, and covers the prompt library interactions. Adds rich behavioral context (one-off execution, billing flows) that the annotations (readOnlyHint false, destructiveHint false) do not capture. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is a single, dense paragraph—very long. It is front-loaded with the core flow, but the length makes it hard to scan. It could benefit from structured bullets for each action. While every sentence adds value, the overall organization is not ideal for agent parsing.

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 (23 params, no output schema), the description covers discovery, invocation, installation, billing, auth, and the prompt library. However, it does not explicitly describe return values or error handling (e.g., what search returns, how describe structures the MCP profile, pagination for list_tools). This is a notable gap given no output schema, but the core functionality is well-covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It explains the core parameters (action, query, mcp_id, tool_id, arguments) through the action flow, and also mentions tier_slug, prompt_* parameters, and cancel fields implicitly. Not every one of the 23 parameters is individually described, but the major ones are contextualized. Lacks explicit parameter-by-parameter detail but covers most semantics through action explanations.

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 this is the official mcp.ai marketplace for cataloging and running MCPs, differentiating it from sibling tools like authenticate and connect. It specifies the exact resource (marketplace) and the actions it supports (search, describe, invoke, etc.), making it distinct and 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 explicit guidance on when to use each action: prefer invoke for one-off runs vs install for permanent additions, handles edge cases like missing credentials and empty wallet, and explicitly mentions alternatives (list_tools for what's callable now, request_mcp for new builds). This gives the agent clear decision rules.

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 mentions needing the conversation for reproduction but does not disclose behavior such as side effects, permissions required, or what actions the tool takes (e.g., creating a report, sending feedback). The annotations (readOnlyHint, destructiveHint) are default and not contradicted, but the description adds little transparency about the tool's execution or consequences.

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, consisting of two sentences, with no redundant information. It directly states the action and provides a key instruction, making it easy to read and understand without unnecessary verbosity.

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 schema and the description, important context is missing. The description only covers one of three parameters, and that explanation conflicts with the schema type. There is no mention of return values, expected outcomes, or any additional behavioral context. The tool feels incomplete for a user to effectively use without further clarification.

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 three parameters (context, message, conversation) but the description only explains conversation, and even then incorrectly calls it an 'array' while the schema type is 'string'. There is no guidance on the purpose or format of 'context' or 'message', and the type contradiction undermines clarity. This is a significant gap that could lead to misuse.

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 uses a specific verb ('report') and clearly distinguishes the resource from sibling tools like authenticate or connect, making it easy to identify when this tool is appropriate.

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 a direct usage instruction ('Include the conversation array with recent messages for reproduction') but does not explicitly state when to use this tool versus alternatives. However, since none of the sibling tools handle bug reporting, the context is somewhat implied. The instruction itself is helpful but lacks broader usage 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?

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds the detail that it returns platform and adapter versions, which is consistent with the annotations. It doesn't add extra context like rate limits, but given the triviality and annotation coverage, this is sufficient.

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, clear, and front-loaded sentence with no unnecessary words. Perfectly concise and well-structured for its purpose.

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 no parameters, strong annotations, and a simple output of version information, the description fully covers what the tool does. There are no gaps that need filling.

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 baseline is 4 as per the rubric. No parameter descriptions are needed, and the schema coverage is 100% vacuously.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Show') and clearly identifies the resource ('current MCP platform and adapter versions'). It unambiguously distinguishes itself from sibling tools like 'toolkit_info' by focusing on version information only.

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 guidance on when to use this tool instead of alternatives, but the purpose is so self-evident that usage is implied. A 3 is appropriate because the description provides no context on when to prefer this over siblings like 'toolkit_info' or when not to use it.

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 read-only and idempotent behavior. The description adds details about the returned content but does not disclose any additional behavioral traits (e.g., error conditions, authentication requirements). It is accurate and does not contradict 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, concise sentence with no redundant wording. It efficiently conveys the tool's purpose and output content.

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?

Since no output schema is provided, the description adequately explains what the return value contains. It covers the key aspects without being overly verbose, making it sufficient for a simple informational 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?

The tool has no parameters, and the schema reflects an empty object. The description does not need to elaborate on parameters; baseline for zero params is high, and this is satisfied.

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 it returns the toolkit state and enumerates specific components (installed MCPs, connection status, accounts, catalog tool counts). This is specific and distinguishes it from sibling tools like 'show_version' or 'authenticate'.

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 (to inspect current toolkit state) but does not explicitly state when to prefer this tool over alternatives. No guidance on context or prerequisites is given.

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 read-only, idempotent, non-destructive behavior. The description adds relevant context beyond annotations: the paid-per-query nature, the lack of required platform credentials, the official-source nature, non-confidential status, and LGPD responsibilities. This is useful behavioral and commercial context.

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 sized and front-loaded with 'Consulta Processual'. It contains some redundant mentions of 'official source', but the extra details about cost, credentials, and LGPD all serve a purpose. It is concise enough for a tool description.

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 two-parameter tool, the description lack essential detail about the query parameter 'grau' and what the output will look like. It gives adequate context about source, legality, and billing, but without parameter guidance or an output schema description, the overall completeness is only average.

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 adds no information about either parameter. Though 'numero_processo' is traceable to a typical court case number, its format is not described, and 'grau' remains unexplained. The agent is left without any parameter-level guidance for invocation.

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 states a clear action: "Consulta Processual" in the specific official source "Tribunal TRT1". It distinguishes itself from the generic sibling tools (authenticate, marketplace, etc.) by naming the court and the query type.

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 some usage context: it is a paid query using prepaid credits, without platform credentials, and accesses official public data. However, it does not explicitly say when to use this tool versus alternatives, nor are there any exclusions or conditions for when to avoid it.

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