Tribunal TRT6: Consulta Processual

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

Beyond the sparse annotations (idempotent only), the description reveals the browser-based flow, permanent vs session-only login behavior, and the no-args link generation. It doesn't disclose what a successful token call returns or error/failure behavior, but the provided behavioral context is meaningful.

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?

Three brief sentences front-load the purpose and then pack the necessary configuration and invocation details. Every clause adds actionable information, and the inline code formatting improves scanability.

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 one-parameter auth tool, the description covers the two invocation modes and how to obtain a token, which is sufficient for an agent to invoke it. It lacks explicit return/error semantics and has no output schema, leaving a small completeness 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?

The schema only lists an optional `token` string with zero description coverage, so the description carries the entire semantic burden. It defines `token` as a JWT for session-only login and explains the no-args case, fully compensating for the schema's silence.

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 this as the MCP.AI authentication tool for IDE agents and gives concrete actions: browser login, token capture, and optional token submission. This sets it apart from sibling utilities like connect/report_bug and makes the tool's function unmistakable.

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?

It explicitly contrasts the recommended permanent header configuration with the session-only token call, and states exactly when to pass a token versus call with no arguments to get a link. It doesn't name sibling alternatives or explicit when-not conditions, 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well-covered. The description adds valuable behavioral details about the return states (authenticated:true, empty pending[], connect_url presence) and explains the difference between missing credentials scenarios (toolkit-level vs per-install URLs). These details go beyond the annotations and help set expectations.

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-loaded with the core purpose. Every word adds value, no repetition or 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?

Given the tool's simplicity (no parameters, no output schema), the description covers the essential behavioral aspects: the two possible return states and the distinction between connect URLs. It lacks explicit details about the structure of the 'pending' array or the format of URLs, but that is likely minor for a status-check tool. Annotations cover safety.

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)Skip, so there are no parameters to document. The description is not required to add parameter semantics, but it does clarify what the output will contain based on the connection state, which is helpful for an agent interpreting the results. Baseline of 4 is appropriate for no-parameter 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: returning connection status and URLs. It specifies the exact conditions for different return states (all providers connected vs. missing credentials), which distinguishes it from siblings like authenticate, that initiates connections, or toolkit_info, that provides general toolkit 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?

The description implies when to use this tool: when you need to check connection status or obtain connect URLs. It does not explicitly state when not to use it or mention alternatives, but the context is clear enough that an agent would know to use it for status checks rather than for initiating connections (sibling authenticate).

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 only indicate non-readonly, open-world, non-idempotent, non-destructive. The description adds rich behavioral context: invoke runs one-off without installing, returns a connect link when credentials are needed, returns a checkout/top-up link when wallet is empty (then retry), and notes that writes require workspace owner/admin. It also clarifies that search/describe flag installed status and that prompt library is separate from MCPs. 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 long (≈300 words) but every sentence earns its place. It is structured with a clear opening definition, a core-flow breakdown, a 'KEY' highlight for the most important nuance, and a separate prompt-library section. For a tool with 14 actions and 23 params, this is appropriately dense and front-loaded.

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 complexity (14 actions, no output schema, no param descriptions), the description covers the main workflows and edge cases (auth, payment, administrator rights). However, it omits some details: the 'resume' action is not mentioned, and parameters like 'immediate', 'tier_slug', 'conversation', and 'cancel_reason' are not explained. It is still remarkably complete for such a broad 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?

Schema has 23 params with 0% description coverage, so the description carries the burden. It explains the meaning of key parameters: 'action' values (search, describe, invoke, install, etc.), 'tool_id' (picked after describe returns the profile), 'prompt_vars' (fills {{variables}}), and 'mcp_id' (identifies an MCP). However, it does not cover all params (limit, immediate, tier_slug, cancel_reason, etc.), so it is not fully comprehensive but 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 dual purpose: it is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It explicitly covers capability requests and differentiates from siblings like 'list_tools' (which only lists callable tools) and 'toolkit_info' (which is not mentioned but implied as different). The verb+resource is specific 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?

The description provides explicit usage guidance: it explains the core flow (search → describe → invoke), distinguishes 'invoke' from 'install' with clear recommendations ('prefer invoke for a single/occasional use'), and names alternatives like 'list_tools' for currently callable tools. It also details when to use prompt-library actions (search_prompts, get_prompt, publish_prompt). This is textbook when-to-use guidance.

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 cover basic traits (not read-only, not destructive, idempotent). The description adds that the conversation is included for reproduction, which gives useful insight into how the tool behaves. 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 concise, consisting of two clear sentences with no redundant or vague phrasing. It avoids unnecessary details and stays focused on the essential points.

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 a good overview but lacks details about the context parameter and does not explain the exact format or expected content of the message. While it mentions the conversation for reproduction, it does not fully cover all aspects of the tool's usage. Given the simplicity, it is adequate but not 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 schema has three parameters (message, context, conversation) but the description only mentions conversation (as an array of recent messages). It does not explain the message or context parameters, leaving most of the input ambiguous. Since schema coverage is low and the description does not sufficiently compensate, it earns a low score.

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 report a bug, missing feature, or send feedback. It is specific and readily distinguishes this tool from siblings like authenticate, connect, or marketplace.

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 the tool (when reporting issues or feedback) and even gives a usage hint (including the conversation array for reproduction). However, it does not explicitly contrast with alternatives or mention when not to use it, so it falls short of a perfect score.

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 and idempotentHint=true. The description adds that both platform and adapter versions are shown, which is extra context beyond the annotations. No contradictions.

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?

Single sentence, perfectly concise, front-loaded with the action and object. No filler 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?

Tool is trivial with no parameters, no output schema, and complete annotations. The description fully explains the tool's purpose and behavior in this context.

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 is fully covered (100%). The description adds no param info because none is needed, and the baseline for 0 params 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?

Description is specific: 'Show the current MCP platform and adapter versions.' Clearly identifies the action (show) and the target (versions), and none of the sibling tools serve this purpose, so it distinguishes well.

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?

Context is clear (informational read of versions) but no explicit when/when-not guidance is provided. However, given the tool's simplicity and the lack of overlapping siblings, the usage context is self-evident.

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 and destructiveHint false. The description adds meaningful context about what state is surfaced (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations. No contradictions.

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, information-dense sentence with no fluff. Every element adds value, and it is appropriately front-loaded.

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 informational tool, the description fully conveys the scope and content of the response. No output schema exists, but the description enumerates the components of the tool state, making it complete for the agent's purposes.

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 parameters and schema coverage at 100%, the baseline is 4. The description does not need to elaborate on parameter semantics, and it adds value by explaining what information is returned.

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 specifies exactly what the tool returns: installed MCPs, connection status, accounts, and catalog tool counts. This clearly differentiates it from siblings like connect, marketplace, and show_version, which address other 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 implies usage for checking toolkit state but does not explicitly state when to prefer this over alternatives. Given its read-only nature and distinct output, the context is clear enough, though there is no explicit when/when-not guidance.

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 and destructiveHint=false, but the description adds valuable context: no platform credentials needed, pay-per-use with prepaid credit, data is not confidential, and LGPD responsibilities. This goes beyond annotations and clarifies the operational and legal 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 reasonably concise, opening with a clear 'TRT6: Consulta Processual' statement. It includes necessary context about cost and data control, though the LGPD sentence could be tightened. Overall, it earns its place without being 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?

For a simple read-only query tool with two parameters and clear annotations, the description covers key aspects: official source, cost, credentials, and data sensitivity. It does not describe return format, but given the absence of an output schema and the straightforward nature of a consult operation, this 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?

With 0% schema coverage, the description does not explain the parameters. It does not elaborate on 'numero_processo' (though implied by the tool name) or 'grau', leaving the optional 'grau' parameter ambiguous. The description fails to compensate for the schema's lack of documentation.

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 performs a 'Consulta Processual' at 'Tribunal TRT6', specifying the verb and resource. It distinguishes itself from sibling tools like authenticate or connect by focusing on process consultation in official Brazilian sources.

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 that it queries official sources without platform credentials and costs prepaid credit, but it does not explicitly state when to use this tool versus alternatives or mention any exclusions. Usage is implied for consulting TRT6 process data, but no comparative guidance is given.

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