Tribunal TRT4: Consulta Processual

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

The description adds useful context beyond annotations: no-args calls return a link, token calls authenticate a session, and config-header auth is permanent/non-expiring. Annotations already provide idempotent=true and destructive=false, so the description's extra flow information is valuable. It does not cover failure/error behavior, which keeps it short of a 5.

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 compact and front-loaded with purpose, followed by two useful usage paths. There is no filler, but minor phrasing like 'log in in the browser' and the informal 'Best:' construction prevent a perfect structure score.

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 tool with strong annotations, the description covers the key flows: permanent header-based auth, session-only token auth, and no-args link retrieval. Since there is no output schema, it could say what happens after token submission, but the core use cases are sufficiently explained.

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 token string with 0% description coverage, so the description must compensate. It does: the token is a JWT pasted by the user, it is optional, and omitting it triggers link retrieval. This is solid for a single optional parameter, though it could explicitly state that token absence is valid.

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 an MCP.AI authentication tool: 'log in in the browser, copy the access token' and then use it for a session or permanent connection. It is specific enough to be usable, but it does not explicitly distinguish itself from the sibling 'connect' 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?

It gives practical when-to-use guidance: prefer adding the token as a server config header for a permanent connection, or paste it for a session-only login. It also explains call modes ('call with { token }' vs 'no args to get the link'), though it does not name alternative tools or state explicit when-not-to-use conditions.

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 valuable behavioral detail by explaining the two possible outcomes: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing. This goes beyond annotations and helps the agent understand response states.

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 extremely concise, consisting of two short sentences that convey the essential behavior. It is front-loaded with the main purpose and then provides conditional details. No unnecessary words or repetitive information, achieving maximum clarity with minimal length.

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 main outcomes and provides enough context for an agent to understand what to expect. It explains both the fully connected and missing-credentials states. However, it does not address partial connection scenarios, which could be a minor gap, but for a status-checking tool, the description is sufficiently complete for effective use.

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 does not need to add parameter semantics. According to the rubric, a baseline of 4 applies for 0-parameter tools. The description correctly omits parameter details since there are none, and it does not introduce any false 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 function: 'Returns connection status and URLs.' This is a specific verb+resource pattern that distinguishes it from siblings like 'authenticate' and 'marketplace', focusing on status retrieval rather than actions. It also mentions key return values (authenticated:true and pending[]), 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 no explicit guidance on when to use this tool versus alternatives. It does not state 'use this to check connection status before authenticating' or mention any exclusions. While the read-only nature implies safe usage, there is no clear context about when it should be invoked, leaving the agent to infer usage.

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?

It discloses crucial behaviors well beyond the sparse annotations: 'invoke works even when the MCP is NOT installed', credential-needed returns a connect link, paid-and-empty-wallet returns a checkout/top-up link, and writes require workspace owner/admin. The annotations (readOnlyHint=false, destructiveHint=false) are not contradicted.

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 densely packed and front-loaded: it opens with identity, then the core flow, then edge cases (uninstalled MCPs, auth, payment), then supporting actions, then the separate prompt library. Every sentence adds operational value and the logical flow makes the length justified.

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 (14 actions, 23 params, no output schema), the description covers the full decision surface: search/describe flow, one-off invoke behavior, installation permanence, permissions, billing/auth failure modes, prompt library, and even the return shape for describe/get_prompt/publish_prompt. It is comprehensive enough to select and invoke 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?

With 23 parameters and 0% schema description coverage, the description must compensate, and it does for the most important ones: it explains the action enum in prose, ties mcp_id/tool_id to the discover/describe/invoke workflow, and mentions prompt_slug, prompt_body, and publish_prompt. However, many remaining parameters (arguments, prompt_vars, conversation, tier_slug, request_details, cancel_reason, etc.) are not individually described, leaving some inference to the agent.

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 immediately identifies the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' then lays out the core flow: search → describe → invoke. This is a specific, resource-anchored purpose that clearly differentiates it from sibling tools like authenticate, connect, and toolkit_info.

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 explicit when-to-use guidance for each major action: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', 'list_tools lists what is callable right now', and 'request_mcp asks us to build a NEW MCP when nothing fits'. This makes alternates and exclusions clear.

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=false, destructiveHint=false, and idempotentHint=true, so the safety profile is clear. The description adds that the conversation array aids reproduction, which is useful context. However, it does not disclose potential side effects like data being sent to developers or the exact behavior of the operation beyond reporting.

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, with the core purpose front-loaded. Every sentence adds value, and there is no unnecessary 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?

The tool is simple with three parameters and no output schema. The description gives a clear purpose but leaves gaps in parameter semantics and behavioral details, making it only partially complete for an agent to use correctly without additional assumptions.

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 by explaining parameters. It only mentions the conversation array and implies the message is the report content, but does not clarify the 'context' parameter or the relationship between 'message' and 'conversation'. This is insufficient for correctly filling parameters.

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 specifies the tool's purpose: reporting bugs, missing features, or feedback. It uses a specific verb ('Report') and identifies the resource (bugs/missing features/feedback), distinguishing it from unrelated siblings.

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 the tool (to submit a bug report or feedback) and provides a practical guideline ('Include the conversation array with recent messages for reproduction'). It does not explicitly mention alternatives or exclusions, but no sibling tool is similar, so clear context suffices.

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 adds specificity beyond the annotations (which already declare readOnlyHint=true, idempotentHint=true) by specifying the exact version types shown. It is consistent with the read-only, non-destructive nature and provides sufficient context for a simple version query.

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 immediately states the tool's purpose. It contains no filler, redundant qualifiers, or repetition of the 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 parameterless, read-only tool with strong annotations and no output schema, the description provides complete information. It clearly states what the tool does and what it returns conceptually, making it self-sufficient for an agent.

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 vacuously covered by the description. There is no need for parameter explanations, and the description correctly focuses on behavior rather than nonexistent parameters.

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 action ('Show') and the specific resource ('current MCP platform and adapter versions'). It distinguishes itself from siblings like toolkit_info by explicitly naming the version target, 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 clear context: use this tool when you need to know current MCP platform and adapter versions. It doesn't explicitly mention alternatives or exclusions, but the tool's simplicity and name make its usage obvious.

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, and the description adds value by detailing the kind of data returned (e.g., 'how many catalog tools each exposes'). It does not contradict annotations and provides enough context for an agent to understand the read-only nature, though it doesn't mention any potential latency or cached data concerns.

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, grammatically complete sentence front-loads the action and resource, followed by a concise list of returned information. Every word contributes to understanding the tool's output, with no padding.

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 parameter-less, read-only tool with no output schema, the description sufficiently enumerates all returned data categories. It covers who/what is reported (MCPs, statuses, accounts, tool counts), making it entirely clear what the agent will receive. No output format is needed for such a simple 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 accepts zero parameters and schema coverage is 100% (vacuously). Per rubric, a baseline of 4 applies, and the description doesn't need to explain parameters. No additional semantics are required.

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 'Returns' with a clear resource 'toolkit state' and enumerates distinct data points (installed MCPs, connection status, accounts, catalog tool counts). This clearly differentiates it from siblings like show_version or connect, 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 clearly implies when to call this tool (whenever current toolkit/connection state is needed) by listing exactly what it returns. However, it lacks explicit exclusions or naming of alternatives (e.g., 'use show_version for version info'), so it doesn't fully meet the 5-level standard.

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 annotations, it discloses cost implications (prepaid credits), data sensitivity (not confidential), and legal responsibility under LGPD. These are significant behavioral aspects not covered by 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 concise, using a few sentences to convey essential information. Each sentence adds relevant context (official source, cost, data sensitivity) without excessive 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?

The description covers key operational aspects: official source, cost model, data confidentiality, and legal compliance. It does not mention response format, but given the absence of an output schema, this is acceptable.

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 for the parameters 'grau' or 'numero_processo'. It does not clarify their meaning, format, or acceptable values, leaving users without guidance on how to construct a request.

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 is for procedural consultation at TRT4, using official sources. It distinguishes from sibling tools like authentication or marketplace by specifying the domain and function.

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 implies usage when needing to query a TRT4 process and mentions the requirement of prepaid credits, which serves as a usage guideline. However, it does not explicitly contrast with alternative tools or provide detailed scenarios.

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