Tribunal TRT: Consulta Processual Unificada

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

Annotations already indicate non-read-only and non-destructive. The description adds the distinction between temporary session auth and permanent config auth, and mentions the token format (JWT). It does not disclose potential side effects like overwriting existing tokens, but given the tool's simple scope and annotation coverage, this is acceptable.

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 yet comprehensive, using two sentences to cover both invocation modes and the alternative config approach. No fluff, each clause adds value.

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 authentication tool with one optional parameter, the description covers all usage flows (no-arg link retrieval, token-based login, and config alternative). It fully prepares the agent for correct invocation without additional context.

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 fully explains the single parameter: token is optional and used for session login, with no args retrieving a link. This adds meaningful meaning beyond the schema's minimal token type.

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: authenticate/login for MCP.AI IDE agents. It explicitly distinguishes the two modes (config header vs session token) and directs users to alternative behavior (config for permanent, tool for session), which separates it from sibling tools like 'connect' or 'report_bug'.

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 explicit usage guidance: call with no args to get a login link, or with a token for session-based auth. It also contrasts the tool-based approach with a permanent config-based alternative, making the decision context explicit.

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, and the description adds useful behavioral details about conditional responses and returned URLs. This goes beyond the structured fields 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 two sentences long, front-loaded with the core purpose, and adds only meaningful conditional details. There is no filler or repetition of structured 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 status/URL tool with no parameters, no output schema, and rich safety annotations, the description covers the two relevant states and their corresponding outputs. It is sufficiently complete for an agent to select and invoke the tool 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 schema coverage is 100%, so there is nothing for the description to add about parameters. The absence of parameter information is acceptable given the empty input schema.

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 that the tool returns connection status and URLs, with specific output details such as authenticated:true and connect_url. It is distinct from sibling tools like authenticate, which perform authentication rather than reporting 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 gives clear conditional context: when all providers are connected the result is authenticated:true with empty pending[], and when credentials are missing it returns connect_url. It does not explicitly name alternatives or state when not to use the tool, but the intended usage is 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 annotations, the description discloses critical behavioral traits: invoke runs one-off without installing, returns connect/checkout links under credential/payment constraints, writes require workspace owner/admin, and install makes MCPs permanent. These details go far beyond the readOnly/destructive hints and prepare the agent for side effects.

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 lengthy but information-dense, covering a complex tool with many sub-actions and edge cases. Every sentence adds meaningful detail, but the single-paragraph structure could be improved with bullets or separated sections for readability. No fluff, but slightly overwhelming.

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), the description covers core flows, edge cases (credentials, wallet top-up), permissions, and the prompt library. It lacks explicit return formats for each action, but it provides enough context for an agent to navigate the marketplace. 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?

The description explains the meaning of action (search/describe/invoke) and touches on mcp_id/tool_id indirectly, but with 23 parameters and 0% schema description coverage, it leaves many parameters (limit, immediate, tier_slug, prompt_*) unexplained. It partially compensates by explaining the high-level workflow, but not enough for full parameter understanding.

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 by identifying the tool as 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then enumerates specific actions (search, describe, install, invoke, etc.) and explains the core flow. This clearly states what the tool does and distinguishes it from sibling tools by covering the full marketplace lifecycle.

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: 'Use install only to make an MCP PERMANENT in the active toolkit ... prefer invoke for a single/occasional use.' It also outlines the core flow (search → describe → invoke) and explains when to use list_tools. However, it does not clearly differentiate marketplace from siblings like authenticate/connect/report_bug, especially since report_bug exists both as a sibling and an action within marketplace.

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 idempotentHint=true and destructiveHint=false, covering the safety profile. The description adds minimal behavioral context (e.g., that conversation data is used for reproduction), but does not elaborate on side effects or post-submission actions. This is acceptable given the annotations, but not enriched.

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, first stating the purpose, second giving a key usage instruction. No redundant words or fluff.

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 three params and no output schema, the description provides the high-level purpose and a critical detail (conversation inclusion) but omits clarification of the 'message' and 'context' fields. It doesn't mention that 'message' is required or what 'context' represents, leaving gaps. Adequate but not fully 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?

Schema description coverage is 0%, so the description must compensate. It mentions the 'conversation array' and explains its purpose ('with recent messages for reproduction'), adding meaning beyond the schema's bare string type and default. However, it fails to explain the 'message' (required) or 'context' parameters, leaving them ambiguous. Partial coverage.

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) and identifies the target (bug/feedback), and none of the sibling tools serve this function, making it highly distinguishable.

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 implicitly indicates when to use this tool (for reporting bugs/features/feedback) and provides a specific instruction: 'Include the conversation array with recent messages for reproduction.' While it doesn't explicitly contrast with alternatives, it gives clear context for appropriate 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, non-mutating operation. The description adds the specific scope (platform and adapter versions) but does not disclose any additional behavioral traits such as output format or potential latency. With annotations covering the safety profile, a score of 3 is appropriate.

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 conveys the essential purpose without any fluff. It is front-loaded and every word earns its place.

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, and clear annotations), the description is complete enough. It clearly states what the tool does, and the annotations cover safety and idempotency. The only minor gap is not describing the return format, but that is not critical for a version-checking 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, and the schema description coverage is 100% (vacuously). The description adds meaning by specifying exactly what versions are shown (platform and adapter), which is useful context beyond the empty schema. Since there are no parameters to document, a baseline of 4 is justified.

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: showing the current MCP platform and adapter versions. It uses a specific verb ('show') and resource ('versions'), and it distinguishes itself from siblings like 'toolkit_info' by focusing on platform and adapter versions rather than general toolkit 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 implies when to use this tool (when you need version information), but it does not explicitly state when not to use it or mention alternatives. Given the sibling tools, there is no direct alternative for version checking, so the guidance is adequate but not explicit.

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 readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds value by detailing the exact kinds of state returned, which goes beyond what annotations tell the agent.

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 sentence that is front-loaded with the action 'Returns' and efficiently enumerates the content without wasted words. Every clause contributes clear information.

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 output schema, the description carries the full burden of explaining return values. It lists four components of toolkit state, providing sufficient detail for an agent to know what to expect, and covers all likely dimensions of the tool's output.

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 explain parameter semantics. The baseline of 4 applies because no parameters exist to describe.

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 the current toolkit state' and enumerates specific components (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from sibling tools like authenticate or connect by focusing on state inspection.

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 the tool is for checking toolkit state but does not explicitly state when to use it versus alternatives or any exclusion criteria. Sibling tools have distinct purposes, so an agent can infer usage, but explicit guidance is missing.

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 (readOnly, idempotent, non-destructive), the description discloses that the tool incurs prepaid credit charges, is hosted by the platform, returns only publicly available citizen-level data, and imposes LGPD compliance responsibility on the client. This adds meaningful operational and legal context, though it doesn't cover potential rate limits or error behavior.

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 short, with purpose front-loaded ('Consulta Processual Unificada'), and it packs relevant operational details into two sentences. It is structured but could be broken into clearer points; still, no extraneous wording.

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 query tool with two parameters and no output schema, the description covers key aspects like data source, payment, and legal standing, and it benefits from strong annotations. However, it omits parameter details and what the response contains, and it lacks guidance on process number formatting, making it incomplete for robust automated usage.

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 has two parameters (numero_processo required, grau optional) with no descriptions; schema coverage is 0% and the description offers no explanation of these parameters. The name 'numero_processo' is self-explanatory, but 'grau' (judicial level) is ambiguous and the description gives no format or usage hints, leaving the agent to guess.

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 unified process consultation for TRT from an official source, with the verb 'consulta' and the resource 'processo'. It distinguishes from sibling tools by being a domain-specific query rather than platform utilities like authenticate or connect, though it doesn't specify the exact data returned (e.g., status, parties).

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 contextual guidance: it mentions the official source, payment via prepaid credits, and that no platform credentials are needed, which helps the agent decide when to invoke it. However, it does not explicitly state when to use it over alternatives or exclude cases (e.g., when the process data is confidential), and no alternative tools are referenced.

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