Tribunal TRT19: Consulta Processual

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

Annotations already indicate idempotentHint=true and destructiveHint=false, and the description adds meaningful behavioral context: it discloses that calling with no arguments returns a link, that pasting a token enables a session-only login, and that configuring a header creates a permanent non-expiring connection. This goes beyond what annotations state, though it does not describe error cases or the exact response format.

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 three sentences, dense but not overly long. Every sentence adds value: the first introduces the tool, the second explains the permanent config method, and the third explains the session-based alternative. It is slightly verbose but well-structured 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?

For a simple auth tool with one optional param and no output schema, the description covers the essential workflows: permanent config header and session token. It also hints at the return behavior (getting a link). It lacks details about error conditions or what the response object looks like, but given the tool's simplicity, it is reasonably 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?

With 0% schema description coverage, the description fully compensates by explaining the 'token' parameter: it is optional, a JWT, used for session-only login, and omitting it returns a link. This is significant meaning beyond the schema's bare property definition.

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 authenticate an IDE agent by obtaining an access token, either through a browser login or pasting a JWT. It specifies the resource (MCP.AI access token) and provides distinct usage paths, which makes it specific. However, it does not explicitly differentiate itself from sibling tools like 'connect' or 'marketplace', so it misses the full marks for sibling differentiation.

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 when-to-use guidance: it instructs the agent to add the token to the server config for a permanent connection or paste it for a session-only login. It explains the trade-offs (permanent vs. session-only). However, it does not explicitly state when not to use this tool or name alternative sibling tools, 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?

The description adds conditional return behavior (authenticated:true vs connect_url) beyond the annotations, which only indicate read-only and idempotent. This enriches understanding of the tool's output without contradicting 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 main action, and covers key behavioral outcomes with no redundant 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 no-parameter status tool, the description adequately covers both success and missing-credential scenarios. It doesn't explain every edge case, but annotations and the read-only nature reduce the need for more detail.

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 covers everything. The baseline for zero parameters is 4, and the description doesn't need to add parameter detail.

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 specific verb and resource. It distinguishes itself by focusing on connection state rather than authentication actions, but doesn't explicitly name alternatives.

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 by describing what happens under different connection states, but it doesn't explicitly state when to use this tool versus alternatives like 'authenticate'. No exclusions or alternative tool mentions.

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?

Rich behavioral context far beyond the annotations: invoke runs one-off 'without adding the MCP to the toolkit and without bloating the tool list', returns a connect link for missing credentials and a checkout/top-up link for empty wallet (with retry instruction), and requires workspace owner/admin for writes. It even discloses the installed_in_toolkit vs installed_in_workspace flags. No contradiction with annotations exists.

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?

Every sentence earns its place — zero fluff — but the entire ~370-word description is one continuous wall of text with no line breaks, bullet points, or section separation. The 'KEY:' prefix on the most important nuance is a good touch, and the core flow is front-loaded, but the density hurts scannability for an agent needing quick signal.

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 of this staggering complexity (23 params, 16+ actions, no output schema), the description covers an impressive surface: the full user journey, edge cases (uninstalled MCPs, missing credentials, empty wallet), permission model, and the entire parallel prompt-library sub-domain. Gaps remain for return/response shapes of individual actions and several operator-facing params, but the coverage is more than adequate for an agent to act.

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 and 23 params, the description carries the full burden. It adds meaning for action values (search/describe/invoke/install, etc.), the flow explains tool_id and arguments, and the prompt-* params are inferable from the prompt library flow. However, many params (cancel_reason, cancel_comment, report_context, request_details, prompt_targets, immediate, tier_slug, limit) receive no explanation and must be inferred from names/enums.

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 what the tool does with specific verbs and resources: 'the in-platform catalog of every MCP/tool, AND the way to run them,' and enumerates the action flow (search → describe → invoke). It differentiates behaviors between invoke and install, which distinguishes it from simpler siblings. However, the tool is a broad dispatcher covering ~16 sub-actions plus a prompt library, which dilutes a single crisp purpose despite the quality of the prose.

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?

Exceptionally explicit guidance: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use' names the alternative and when-not-to-use. It also differentiates list_tools, request_mcp, subscribe/cancel, and search_prompts/get_prompt vs search/describe. This explicitly answers when to use and when not to use each path.

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 cover idempotency and non-destructive nature. The description adds a behavioral requirement to include the conversation array, which is useful. However, it does not discuss potential side effects (e.g., how feedback is processed) beyond the immediate 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 concise and directly relevant, consisting of two sentences with no fluff. It efficiently communicates the core purpose and a key usage detail.

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 is complete for understanding the action and the key requirement about conversation. It does not explain the return value (no output schema) or the context/message parameters, but given the tool's simplicity, it is adequately complete for most use cases.

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?

Only one of three parameters (conversation) is mentioned in the description. Context and message are not explained, leaving their purpose unclear. Since schema coverage is low (33%), the description should compensate, but it fails to do so, resulting in ambiguity for two 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 purpose: report a bug, missing feature, or send feedback. It also specifies including the conversation array, which distinguishes it from sibling tools that handle authentication, connection, marketplace, version, toolkit info, and legal processes.

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 (reporting issues) but does not explicitly state when not to use or reference alternatives. It provides a specific instruction to include the conversation array, giving practical usage guidance, though not explicit exclusions.

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, idempotentHint, and destructiveHint false. The description adds the specific scope (MCP platform and adapter), which is useful context. No contradiction emerges.

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?

Exactly one sentence, no filler, directly states the function with minimal 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?

For a parameterless, read-only tool with complete annotations fact, the description sufficiently conveys the tool's core purpose. It does not mention output format, but that is acceptable given the lack of an output schema and the straightforward nature of the operation.

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 takes zero parameters)Skip baseline of 4 for no parameters. The description imposes no additional parameter semantics beyond the schema, which is already fully covered.

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 'Show the current MCP platform and adapter versions' uses a clear verb ('Show') and specific resource ('MCP platform and adapter versions'), distinguishing it from siblings that handle connections, authentication, or bug reporting.

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 basic version-check use case but provides no explicit guidance on when to use it vs alternatives (e.g., when checking compatibility or troubleshooting). It neither states prerequisites nor exclusions.

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 cover readOnlyHint=true and idempotentHint=true. The description adds useful behavioral content by specifying the nature of the returned state, including per-MCP connection details and account information, which goes beyond what the annotations alone convey.

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?

One dense sentence front-loads the main verb and resource, then uses a colon to efficiently list the exact data returned. There is no redundant phrasing 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 description fully covers the returned state, including the main categories an agent needs to decide whether to call this tool. With no output schema and the tool being strictly read-only, nothing critical 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?

With zero parameters, schema coverage is trivially complete and no parameter documentation is needed. The description appropriately omits parameter details and the baseline for zero-parameter tools 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?

The description uses a specific verb ('Returns') and a precise resource ('current toolkit state') and then explicitly enumerates what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like 'connect' or 'show_version'.

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 that this tool is used to inspect the overall toolkit state, including integrations and catalog exports. However, it does not explicitly say when to prefer this tool over alternatives like 'marketplace' or 'show_version'.

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 known. The description adds valuable behavioral context: it requires prepaid credits, is hosted by the platform without platform credentials, and notes the client's responsibilities under LGPD. This goes beyond annotations and clarifies operational requirements.

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 relatively compact, consisting of four sentences that front-load the core purpose. It includes necessary operational details (payment, hosting) and LGPD considerations without excessive verbosity. It is well-structured but could be slightly more concise by merging some legal/privacy notes, yet it remains efficient.

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 has two parameters and no output schema, the description is expected to clarify the meaning of the parameters and possibly the return format. It does neither. 'grau' is unexplained, and there is no hint of what the response contains. The description also fails to mention that 'numero_processo' is required, leaving the agent to rely solely on the schema. This incomplete guidance makes the tool hard to use effectively.

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%, meaning the description provides zero explanation of the parameters 'grau' and 'numero_processo'. The only clue is the parameter names, which may be self-explanatory for a Portuguese-speaking user, but the description fails to compensate for the lack of schema documentation. This is a significant gap for a tool with two parameters, especially since 'grau' is ambiguous.

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 a 'Consulta Processual' (procedural consultation) for TRT19, indicating a read-only retrieval of case information from an official source. It also clarifies that it consults public data from Brazilian official bodies, distinguishing it from potential confidential tools. However, it lacks explicit details on what specific case information is returned, so it stops short of a 5.

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 about when to use the tool by mentioning it consults official Brazilian sources and is pay-per-use, implying it's for legitimate case lookups. It does not explicitly state alternatives or when not to use it, though sibling tools are unrelated. This gives basic usage context but lacks clear explicit guidance.

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