Tribunal TRT24: Consulta Processual

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

Annotations already indicate readOnlyHint=false and idempotentHint=true. The description adds valuable behavioral context: it explains that using config results in a non-expiring connection while pasting a token gives a session-only login. It also describes the interaction flow (browser login, copying token). This goes beyond the annotations by clarifying the permanence and session semantics, without contradicting any annotation.

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 (about 80 words) and front-loaded with the target audience ('MCP.AI for IDE agents'). It efficiently structures the two authentication modes and invocation calls. A minor structure issue is that it reads as a single long sentence with multiple clauses, which slightly reduces readability, but it remains appropriately sized for the 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?

For a simple tool with one optional parameter and no output schema, the description covers the essential scenarios: how to authenticate permanently via config, how to authenticate for a session via token, and how to request the login link. It does not mention error cases or what happens after a token is provided, but given the low complexity and existing annotations, it is adequately complete for an agent to use 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?

Schema has a single optional 'token' property with no description and 0% coverage, so the description must compensate. It explicitly explains the token parameter: it is a JWT to paste from the user, and when omitted, the tool returns the login link. This fully clarifies the parameter's meaning and usage, exceeding the schema's minimal information.

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: authentication for IDE agents, specifically obtaining an access token via browser login. It distinguishes itself from siblings like 'connect' by focusing on token-based authentication for MCP.AI, with explicit mention of two authentication flows (permanent config vs session token). The verb 'log in' and resource 'access token' are specific.

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 recommends adding the token to config for permanent connection, or pasting a token for session-only login. It also instructs how to invoke the tool (with token or no args to get the link). However, it does not explicitly mention when not to use this tool versus alternatives like 'connect', though the context makes it clear this is for authentication.

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 readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds meaningful behavioral context by detailing the response shape for both success (authenticated:true, empty pending[]) and failure (connect_url, per-install URLs) cases, which is valuable 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 two sentences, front-loaded with the core purpose, and each sentence adds essential information about conditional behavior. There is no wasted wording, and it is easy to parse.

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, lack of parameters, and lack of an output schema, the description provides sufficient detail about the two main scenarios. It covers the key return fields (authenticated, pending, connect_url, per-install URLs) and leaves no critical ambiguity for an agent selecting or invoking this 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 zero parameters, so the schema provides no constraints. The description correctly implies that no inputs are needed and focuses on output behavior. Baseline for 0 params is 4, and the description fully avoids needing parameter 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 a specific action: 'Returns connection status and URLs.' It also specifies the output under different conditions (all connected vs missing credentials), which makes the tool's purpose unambiguous and distinguishes it from siblings like 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 clearly implies usage as a connection status check by describing what it returns and when. It doesn't explicitly exclude alternatives, but the context (sibling tools like authenticate) makes it evident when to use this tool. No explicit exclusions are needed for such a straightforward read-only status tool.

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 only carry readOnlyHint=false with no safety detail, so the description carries full weight — and it delivers. It discloses the one-off invoke behavior ('runs the tool pontualmente... without adding the MCP to the toolkit'), the connect-link and checkout/top-up retry semantics for missing auth/empty wallet, and the owner/admin requirement for writes. All that goes well beyond the structured annotation block with 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?

A dense ~350-word single paragraph with no line breaks, bullets, or a crisp front-loaded summary. Nearly every sentence earns its place given the 14-action surface pinned to a single tool, so it is information-dense rather than padded, but the wall-of-text presentation seriously hurts scannability for an agent parsing it.

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 14-action router with no output schema, it covers the primary flows well: the search→describe→invoke pipeline, install vs invoke trade-offs, auth/payment edge cases (connect link, top-up link, retry), permission requirements, and the separate prompt library. It partially discloses return behavior (connect/checkout links, prompt text, shareable slug), though it never details what describe or list_tools return.

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 23 params at 0% schema coverage, the description must compensate heavily. It does explain the pivotal action enum and its values (search, describe, invoke, install, list_tools, prompt actions) and ties tool_id/arguments to the invoke flow. But individual parameter semantics — limit, immediate, tier_slug, cancel_reason, conversation, prompt_vars — remain undocumented, leaving gaps the schema does not fill.

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?

States its full role explicitly: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then enumerates all 14 dispatch actions, making the broad surface unambiguous. Clearly distinct from siblings like authenticate, connect, and tribunal_trt24_processo_consultar, so there is no confusion about when to reach for this 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?

Provides an explicit recommended flow: 'action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool.' Also gives a clear decision rule between the two overlapping actions — 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT' — and points to list_tools for what is callable right now.

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=false, destructiveHint=false, and idempotentHint=true, covering basic safety. The description adds no behavioral details beyond usage (e.g., what happens after submission, authentication needs, or side effects). It does not contradict annotations, but it also does not enrich the agent's understanding of the tool's runtime behavior. With annotations present, the bar is lower, yet the description is still thin.

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 consists of two clear sentences with no superfluous content. The first sentence states the action, the second gives a critical input instruction. It is front-loaded and highly efficient for an AI agent.

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, and the description covers the basic purpose and the most important parameter (conversation). However, it omits any explanation of the 'context' field, and the schema/description mismatch on conversation could mislead an agent. With no output schema, the description could clarify expectations after submission (e.g., confirmation or ticket ID), but it does not. Overall adequate but with notable 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 coverage is 0%, so the description must clarify parameters. It explicitly mentions the conversation parameter and instructs to include recent messages, which adds meaning. However, it defines conversation as an 'array' while the schema declares it as a string with default '[]', creating confusion. The 'message' parameter is implied as the report content, and 'context' is completely unexplained. Thus, partial compensation is provided, but significant gaps remain.

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/send) and resource (bug/feature/feedback), and it is distinct from sibling tools like authenticate or connect. No ambiguity.

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 conveys when to use the tool ('report a bug, missing feature, or send feedback') and gives explicit guidance to include the conversation array for reproduction. It does not mention alternatives or exclusions, but the context is clear enough for typical use. A higher score would require explicit when-not-to-use or alternative tool references.

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 declare readOnlyHint, idempotentHint, and destructiveHint, covering safety behavior. The description adds no additional behavioral context beyond stating what versions are shown, which is consistent with the annotations. No contradictions or missing side-effect disclosures.

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, focused sentence with no filler or redundancy. It is front-loaded with the action and resource, making it immediately understandable.

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 extreme simplicity (no parameters, no output schema, clear annotations), the description is fully complete. It covers the entire purpose without needing additional details.

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 schema coverage is trivially 100%. Per the rubric, baseline for 0 params is 4. The description does not need to add parameter details, and it does not attempt to.

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 the specific verb 'show' and names the precise resources ('current MCP platform and adapter versions'), making it clear what the tool does. It distinguishes itself from sibling tools like authenticate or marketplace, which are clearly unrelated operations.

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 version information, but it does not explicitly state when to use this tool versus alternatives or include any exclusions. Since the tool is simple and self-explanatory, the implied context is adequate but not fully spelled out.

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 need not restate safety. It adds value by specifying exactly what state is returned, including connection status and account details, but it does not disclose potential variability, latency, or whether the state snapshot is consistent across all MCPs.

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 purpose and then lists the specific data returned. Every phrase carries informational weight, with 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?

With no parameters and no output schema, the description carries the full burden of explaining the tool's return value. It does so comprehensively by naming all major categories of returned state: installed MCPs, connection status, accounts, and catalog tool counts, making the tool's output expectations 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?

The tool has zero parameters, so there are no parameter semantics to explain. Per the rubric, this warrants a baseline of 4, and no description-based clarification 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 identifies the tool as a status/inspection resource with a specific verb ('Returns') and enumerates its contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like connect or authenticate, which perform actions rather than report 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 implies a clear use case: checking the current toolkit state, especially before or after connecting/authenticating MCPs. It doesn't explicitly name alternatives or exclusions, but for a zero-parameter read-only info tool, the context is sufficiently clear and non-misleading.

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 provide read-only and idempotent hints. The description adds valuable behavioral context beyond annotations: hosted by the platform, no platform credentials required, pay-per-query with pre-paid credits, official/non-confidential data source, and LGPD data-controller responsibilities. 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 reasonably concise and front-loaded with the primary purpose. The additional sentences about payment, official sourcing, and LGPD add useful context, though some legal boilerplate could be trimmed without losing core invocation guidance.

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 has no output schema and the description does not explain return values or parameter semantics. While it covers data source, payment, and legal context, it fails to describe the 'grau' parameter or expected 'numero_processo' format, leaving a significant gap for correct invocation.

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 offers no explanation of the parameters 'grau' or 'numero_processo'. It does not compensate for the schema's lack of descriptions, leaving the agent without guidance on required formats or possible values.

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 performs procedural consultation for TRT24 from official sources, with a specific verb ('Consulta') and resource ('Processo'). It also differentiates itself from the sibling platform tools, which are generic utilities like authenticate and 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 gives clear context about when to use the tool: for consulting official Brazilian public court data, with pre-paid credits and no platform credentials needed. It does not explicitly name alternatives or exclusion conditions, but sibling tools are unrelated, making the intended use fairly unambiguous.

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