Tribunal TRT8: Consulta Processual

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

Annotations indicate the tool is not read-only, so the description appropriately explains that it sets up an authenticated connection, and it adds meaningful context about permanent vs. session-only auth and the need for a bearer token. This goes beyond what the annotations alone provide, though it does not mention potential failure modes or side effects in detail.

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 information-dense, covering setup, permanent config, session-only login, and the no-args flow in a short span. It is slightly dense and mixes config advice with tool-call instructions, but every sentence contributes useful 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?

For a one-optional-parameter tool with no output schema, this description is largely complete: it explains how to start, how to authenticate with a pasted token, and the permanent alternative. It could improve by clarifying expected outcomes or error cases, but the current content is enough for an agent to invoke the tool correctly in the common flows.

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 description coverage, the description carries the entire burden for the optional token parameter. It clearly shows how to invoke it with a JSON snippet: 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' This makes the parameter semantics clear even though not every detail is enumerated.

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 authentication as the tool's function: 'MCP.AI for IDE agents... log in in the browser, copy the access token.' It conveys both the resource (secure connection/access token) and the action, and differentiates itself from sibling tools like connect or report_bug by focusing on authentication flows.

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 usage branches: add the token to config for a permanent connection, pass a token in-call for session-only login, or call with no arguments to obtain the link. It does not explicitly name alternatives among sibling tools, but it clearly covers when each mode is appropriate.

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 this as read-only and idempotent, but the description adds behavioral detail beyond those hints: it explains the `authenticated:true` and `pending[]` condition, and the `connect_url` returned when credentials are missing. This is useful context not inferable from annotations alone.

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 long, front-loads the primary purpose, and adds only essential conditional details. Every sentence contributes meaning without redundancy 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?

For a zero-parameter, read-only status tool with supportive annotations, the description sufficiently covers both outcome states and the meaning of returned fields. No output schema is needed, and the provided detail is adequate.

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 fully covers the parameter surface. The description does not need to explain parameters, and no additional semantic burden falls on it.

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 opens with a specific verb and object: 'Returns connection status and URLs.' This clearly names the tool's function and distinguishes it from sibling tools like authenticate by focusing on status reporting rather than credential exchange.

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 about when different output states occur (all providers connected vs. credentials missing), but it does not explicitly say when to choose this tool over alternatives like authenticate or how it relates to them. Usage is implied rather than directly stated.

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 well beyond the sparse annotations (readOnlyHint=false, openWorldHint=true, etc.). It discloses the one-off execution behavior of invoke ('works even when the MCP is NOT installed'), the credential/payment flow ('if the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link'), and the library publishing behavior ('returns a shareable mcp.ai/p/<slug> link that opens without login'). It also clarifies permission requirements not visible in 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 dense and information-packed, with every sentence adding substantive detail. However, it is a single monolithic paragraph with no structural aids (bullets, bolded terms) to help an agent parse the multiple distinct capabilities. Given the complexity of 14 actions and the prompt library, the length is justified, but a structured layout would have improved scannability and earned a 5.

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 23 parameters, no output schema, and no parameter descriptions, the description is exceptionally complete. It covers the entire discovery-to-execution workflow, permission requirements, authentication and billing contingencies, the distinction between one-off and permanent installation, and the prompt library sub-system. An agent can select actions and understand consequences without out-of-band information.

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 description coverage, the description carries the full burden of explaining parameters. It effectively maps the action enum values to their semantics (search, describe, install, invoke, subscribe, cancel, report_bug, request_mcp, list_tools, search_prompts, get_prompt, publish_prompt) and explains the roles of mcp_id, tool_id, arguments, and prompt-related fields. However, some parameters like limit, immediate, tier_slug, conversation, prompt_targets, and report_context are not explicitly addressed, leaving a meaningful gap despite the overall richness.

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 role as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It goes far beyond a simple verb+resource, detailing the core search→describe→invoke flow and categorizing the prompt library functionality. It clearly distinguishes itself from the narrower sibling tools by defining the marketplace as the hub for discovery, execution, installation, billing, and prompt management.

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 direct guidance: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also explains when to use request_mcp ('when nothing fits'), subscribe/cancel for billing, and list_tools ('lists what is callable right now'). It additionally surfaces critical access constraints: 'Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin.' This is exemplary 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?

Annotations already indicate this is non-read-only, non-destructive, and idempotent. The description adds the instruction to include conversation history for reproduction, but it does not explain what happens after submission or add meaningful behavioral context beyond the obvious 'report' action.

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 short sentences with no wasted words. It front-loads the core purpose and then gives one important usage hint about conversation data.

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 bug-reporting tool, the description explains the primary purpose and reproduction guidance, but it does not describe how 'message' and 'context' should be used, nor does an output schema compensate for that. It is functional but has clear 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%, and the description only clarifies the conversation parameter. The required 'message' field and optional 'context' field remain unexplained, so the description compensates very little for the missing schema-level descriptions.

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: reporting bugs, missing features, or feedback. This verb+resource framing makes it distinct from sibling tools like authenticate, marketplace, 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?

It explicitly identifies the situations to use the tool: bug reports, missing features, and feedback. It does not mention exclusions or alternative tools, but the use cases are clear and direct.

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 covered. The description adds the 'current' version aspect but does not disclose output format, pagination, or other behavioral details; this is acceptable for a trivial read-only tool but adds modest value 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, concise sentence that fully states the tool's function. Every word is meaningful, with no redundancy 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?

For a no-parameter, read-only version query with no output schema, the description is complete enough. It tells the agent exactly what information will be returned (platform and adapter versions) and requires no additional context to be invoked 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 tool has zero parameters and the schema is fully covered by an empty properties object. Since there are no parameters to explain, the description does not need to add parameter semantics, and the baseline of 4 applies.

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 a clear resource ('current MCP platform and adapter versions'), which directly distinguishes it from sibling tools like authenticate, connect, and toolkit_info. The purpose is unambiguous and immediately actionable.

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 the tool is used to retrieve version information, but it does not explicitly state when to use it versus alternatives such as toolkit_info. There is no exclusion or alternative mention, but the simple version-query intent is 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?

The annotations already establish read-only, idempotent, and non-destructive behavior. The description adds useful behavioral detail about what the returned state contains, specifically connection status, connected accounts, and exposed catalog tool counts, which goes beyond the annotation summary.

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 one information-dense sentence that leads with the main action and then breaks the result set into clear, useful components. No wasted words; every clause contributes to understanding the tool's output and scope.

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 information tool, the description sufficiently explains what will be returned: installed MCPs, connection status, connected accounts, and catalog tool counts. No output schema is present, so the enumeration doubles as return-value documentation, and nothing expected from such a simple query tool is omitted.

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 is no parameter semantics burden to compensate for. The schema coverage is effectively 100% and each additional descriptive phrase is about output content rather than 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 tool's exact function ('Returns the current toolkit state') and enumerates the specific facets returned: installed MCPs, connection status, connected accounts, and catalog tool counts. It is a specific verb+resource combination and is visually distinct from the sibling tools.

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 use this tool: any time a caller needs the current toolkit state or connectivity/account overview. It does not explicitly mention when not to use it or name alternatives, but the zero-parameter informational nature pairs well with the described purpose, making the use case 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?

Beyond the annotations (read-only, non-destructive), the description adds transparency about the data being non-confidential and publicly available, and mentions LGPD compliance and data controller responsibilities. This provides additional behavioral insight.

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 a few sentences that convey the essential purpose and key usage conditions without unnecessary detail. It is well-structured and to the point.

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 the tool's purpose, payment, credentials, and data sensitivity, but it does not explain what 'grau' means or what the output will look like (no output schema is present). This leaves some gaps for a new user, but the core context is provided.

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 no descriptions for the parameters 'numero_processo' and 'grau'. The description does not explain these fields either, leaving their meaning and valid values unclear. Even though the names are somewhat intuitive, there is no explicit guidance.

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 is for consulting court processes ('Consulta Processual') from an official source. It is distinct from the sibling tools like authenticate or connect, which have different 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 provides some usage context (requires prepaid credit, no platform credentials) but does not explicitly compare to alternatives or specify when to prefer this tool over others. It implies a pay-per-query model but lacks direct guidance.

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