Tribunal TRT10: Consulta Processual

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

The description goes beyond the annotations by explaining session-only vs. permanent connection behavior, the no-args link flow, and what happens if a token is pasted. It is consistent with the idempotentHint annotation since logging in repeatedly is the intended, repeatable operation.

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 informative but somewhat cluttered with phrases like 'MCP.AI for IDE agents (Cursor, etc.)' and the parenthetical that is not strictly necessary. Still, every behavioral instruction has a purpose, so it is near-optimal despite its density.

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 one optional parameter, no output schema, and annotations already in place, the description is complete enough: it explains all invocation paths and the auth/token context. No important behavior 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 input schema only identifies 'token' as an optional string with 0% description coverage. The description compensates fully by explaining '<jwt>' and that the token results from pasting a user-provided access token, as well as clarifying the no-argument variant.

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 indicates that this tool is for authenticating an IDE agent by either returning a login link or accepting a pasted JWT access token. It distinguishes the authentication flow from general connection/marketplace tools, though it doesn't explicitly contrast alternatives like 'connect'.

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 guidance on when to use each mode: permanent config via Authorization header is the best option, session-only login is done by passing the token, and calling with no args returns the login link. It also states how to invoke each choice clearly.

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 a safe, idempotent read operation. The description adds value by disclosing conditional return behavior (authenticated state, pending[], connect_url), going beyond what annotations provide. No contradiction 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?

Two sentences front-load the purpose and then provide precise conditional details. Every word earns its place, 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?

Given the tool has no parameters, rich annotations, and no output schema, the description sufficiently covers the two relevant states (connected and missing credentials) and their return values. It is complete for the tool's simplicity.

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 baseline of 4 applies. There are no parameter semantics to clarify, and the description appropriately focuses on behavior rather than inputs.

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 resource: 'Returns connection status and URLs.' It clearly describes the tool's output scope and distinguishes it conceptually from siblings like authenticate, which likely initiates rather than reports status.

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 conditional guidance: when all providers are connected it returns authenticated:true and empty pending[], and when credentials are missing it returns connect_url. This implies it is used for status checks, though it does not explicitly name sibling tools or state when not to use it.

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 discloses significant behavioral traits beyond the annotations: writes require workspace owner/admin; invoke runs uninstalled MCPs without adding them to the toolkit; credential and payment failures return connect/checkout links and require a retry; search/describe expose installation status. This adds critical context about side effects, permissions, and failure modes that annotations alone do not 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?

The description is long but well-structured, using explicit markers like 'Core flow:', 'KEY:', and 'Use install only...' to segment ideas. It is dense with necessary information for a complex tool and avoids redundancy. It could be slightly more scannable, but every sentence contributes to understanding.

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 (23 params, no output schema, no schema descriptions), the description covers the overall architecture, core flow, permission requirements, and edge cases (connect/checkout links). It explains what describe and get_prompt return. It stops short of detailing output formats, parameter syntax, or error handling, but provides enough for an agent to execute primary flows 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 description thoroughly explains the 'action' parameter by narrating each action value (search, describe, install, invoke, etc.) within the flow. However, supporting parameters like query, limit, arguments, and the prompt_* fields are not explicitly mapped to actions, leaving the schema's bare names as the only reference. With 0% schema coverage, the description partially compensates but does not fully document all 23 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 defines the tool as the official mcp.ai marketplace—the in-platform catalog and execution layer for MCPs/tools, plus a prompt library. It states a specific purpose with actionable verbs (search, describe, invoke) and distinguishes it from sibling tools by explaining its unique role, such as running uninstalled MCPs on a one-off basis.

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 guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', contrasts with list_tools ('lists what is callable right now'), and explains when to use subscribe/cancel, report_bug, request_mcp, and the prompt library actions. This is exemplary when-to-use and when-not-to-use guidance, including precedence between alternatives.

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?

With annotations indicating idempotentHint=true and destructiveHint=false, the safety profile is already clear. The description adds useful context by specifying that the conversation array is needed for reproduction, but it doesn't disclose other behavioral details (e.g., where the report goes, confirmation behavior). It does not contradict 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 concise sentences: the first defines the scope, the second provides a necessary instruction. There is no padding or redundancy; every word contributes to the tool's usability.

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 reporting tool with three parameters and no output schema, the description covers the main purpose and provides key usage instructions. It lacks details about the context parameter and doesn't describe consequences of reporting, but given the tool's simplicity and the annotations, it is nearly 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 0% description coverage, so the description must compensate. It does explain the conversation parameter as 'recent messages for reproduction' and implies message is the report text. However, the context parameter is left completely unexplained, leaving a gap in semantic 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 the tool's purpose with a specific verb and resource: 'Report a bug, missing feature, or send feedback.' This distinguishes it from sibling tools like authenticate or marketplace, which are unrelated to reporting issues.

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 usage context by listing the three use cases (bug, missing feature, feedback) and gives a specific instruction: 'Include the conversation array with recent messages for reproduction.' While it doesn't explicitly exclude alternatives, no sibling tools serve a similar reporting function, so the guidance is adequate.

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 value by indicating what is surfaced ('current MCP platform and adapter versions'), but does not describe return format or any additional behavioral details.

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, front-loaded sentence that conveys the tool's entire purpose with no filler or redundancy. It earns its place completely.

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 minimal complexity, zero parameters, and straightforward read-only nature, the description is sufficiently complete. It clearly states what the tool returns, though the absence of an output schema means slightly more detail about the return shape could be helpful.

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 empty, so there is no parameter semantics to clarify. The baseline for no-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 ('show') and names the exact resources ('MCP platform and adapter versions'), making the purpose immediately clear. This also distinguishes it from siblings like toolkit_info, which likely covers broader tooling 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 provides clear context for when to use this tool: whenever the current platform or adapter versions are needed. It does not explicitly name alternatives or exclusions, but for a simple read-only version tool this is sufficient.

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 useful behavioral context by detailing what the returned state includes, which is especially valuable since no output schema is present.

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 action and resource, then uses a colon followed by a compact enumeration. Every element earns its place 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 zero-parameter, read-only info tool with rich annotations, the description is complete. It clearly states what the tool returns despite lacking an output schema, and no additional behavioral or error details are essential for this simple 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 input schema is empty and there are zero parameters, so the baseline of 4 applies. The description correctly needs no parameter explanations because no parameters exist.

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 clearly identifies the resource ('current toolkit state') while enumerating the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from siblings like show_version, which is version-focused.

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 this tool is for inspecting overall toolkit state, which provides enough context for when to call it. It does not explicitly state when not to use it or name alternatives, but the context is clear and no exclusions are needed.

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. The description adds valuable behavioral context: it is hosted by the platform ('Hospedado pela plataforma'), requires no platform credentials, incurs a per-query cost ('pague por consulta com crédito pré-pago'), and deals only with non-confidential public data ('não é dado sigiloso'). It also clarifies data controller responsibilities under LGPD. This extends beyond annotations without contradicting them.

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 paragraph in Portuguese, with the core purpose front-loaded in the first clause. Each additional sentence adds relevant context (hosting, billing, data source, legal compliance). It is slightly verbose with legal boilerplate but not excessive. No fluff or repetition.

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 lookup with two parameters and no output schema, the description covers purpose, data source, billing implications, and legal responsibilities. However, it omits parameter semantics and any detail about the response format. Given the tool's simplicity, the description is adequate but leaves the agent without crucial usage guidance like parameter formats and return expectations.

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%, so the description should compensate for the bare parameter names and types. It does not mention 'numero_processo' or 'grau' at all, nor their format or optionality. While the parameter names are self-explanatory to a human, the description fails to clarify, for example, what 'grau' means or acceptable formats for the process number. The burden is not met.

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 'Consulta Processual' (procedural consultation) and specifies 'consulta em fonte oficial' (query in official source), identifying the resource (court cases) and action (query). It distinguishes the tool from sibling tools, which are unrelated (authenticate, marketplace, etc.). However, it does not explicitly describe what information is returned, so it stops short of full specificity.

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 guidance on when to use this tool versus alternatives. It does not mention conditions like 'use for case status' or 'do not use for sealed records'. The additional context about hosting, payment, and LGPD compliance does not address selection criteria. There is no explicit usage direction beyond the tool's existence.

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