Tribunal TRF6: Processo

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

The description clarifies persistence behavior (permanent vs session-only) and that calling with no args retrieves the login link. This adds useful behavioral detail beyond the basic annotations, and there is no contradiction with readOnly/destructive/idempotent hints.

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 moderately verbose but every sentence carries meaningful guidance. The structure with 'Best' and 'Or' is clear, though the opening phrase 'MCP.AI for IDE agents (Cursor, etc.)' could be trimmed without loss.

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 main workflow, token handling, and both permanent and session-only modes. It does not specify the exact return value, but no output schema is provided and the expected behavior is sufficiently inferable for an authentication 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 schema provides no description for the token parameter, but the description explains that it is the JWT/bearer token obtained from the browser and that it should be passed as { token: "<jwt>" }. It also implicitly indicates the parameter is optional by describing a no-args call.

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: authenticating an MCP.AI user for IDE agents by obtaining and using an access token. It distinguishes between permanent configuration and session-only login, making the action unmistakable.

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 concrete usage instructions: add the token to server config for permanent access, or call with token for session-only login, or call with no args to get the login link. It does not explicitly compare to sibling tools, but the alternative modes are well explained.

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 behavioral detail beyond annotations by specifying the exact return shapes in two scenarios (authenticated:true with empty pending[] vs connect_url and per-install URLs). This enriches the agent's understanding of the tool's behavior 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-loads the purpose, and provides essential state-dependent behavior with zero waste. Every sentence earns its place, making it ideal for quick agent comprehension.

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, read-only with clear annotations), the description fully covers the behavior in both relevant states. No additional information is necessary for an agent to invoke it 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 100% schema coverage trivially. Per the rubric, a baseline of 4 is given for zero parameters. The description does not need to explain parameters, and it correctly focuses on the return values.

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, and explains the two possible outcomes (all connected vs missing credentials). It is specific about the verb (returns) and resource (connection status and URLs), but does not explicitly distinguish from sibling tools like authenticate, so it falls 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 does not provide guidance on when to use this tool versus alternatives. It implies usage for checking connection status but does not mention when not to use it or name any alternative tools. There is no explicit context like 'use this to verify connectivity before authenticating'.

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 beyond annotations by disclosing behavioral nuances: invoke runs one-off without adding to toolkit, requires auth via connect link or payment via checkout link, and has an implicit install behind it. It states permission requirements for writes (workspace owner/admin). It also clarifies that search/describe flag installed_in_toolkit vs installed_in_workspace. This adds substantial context beyond the annotations (readOnlyHint=false, openWorldHint=true, etc.) and contains no contradictions.

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 appropriately dense for the tool's complexity. It front-loads the purpose and core flow, then details key distinctions and lists actions. It uses dashes and semicolons to structure content, but remains a single paragraph. It could be broken into sections for readability, but every sentence adds value, and it is not padded with 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?

Given 23 parameters and no output schema, the description is largely complete: it explains all actions, the flow, auth/permission requirements, payment edge cases, and prompt library. It does not describe exact return formats, but it indicates outcomes (e.g., 'describe returns one MCP's full profile', 'invoke returns a connect link', 'publish_prompt returns a shareable link'). This is sufficient 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?

Schema coverage is 0%, so the description must compensate. It explains the role of key parameters such as action (with exhaustive enum list), mcp_id (used in describe), tool_id and arguments (invoke), and prompt_* params for the prompt library. However, it does not explicitly map every parameter (e.g., limit, query, immediate, tier_slug, prompt_vars, cancel_reason) to its role. It covers the main ones but leaves some ambiguity for less common actions. This is adequate for an agent to use the tool effectively, though not exhaustive.

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 role: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It differentiates from siblings by covering marketplace functions, search, invoke, and prompt library, which none of the sibling tools (authenticate, connect, report_bug, show_version, toolkit_info, tribunal_trf6_processo_consultar) address. The core flow (search→describe→invoke) is explicitly outlined.

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 guidance on when to use invoke vs install: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT in the active toolkit'. It also names alternatives for specific actions: 'subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP'. It clearly explains the conditions for invoke returning connect/checkout links and the need for retries, and notes that writes require workspace owner/admin.

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 (write operation), idempotentHint=true (safe to retry), and destructiveHint=false. The description adds the requirement to include a conversation array for reproduction, which is useful context. However, it does not describe what happens after reporting (e.g., sending data, acknowledgment), nor does it mention any prerequisites like authentication. The added value is modest, so a 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 two sentences, front-loaded with the purpose, and each sentence adds value. The instruction about conversation is directly useful. There is zero redundancy or fluff, making it highly concise.

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, so a short description could suffice. However, the parameter documentation gap and lack of details on expected message format or context usage means it is not fully complete for a first-time caller. A bit more detail on parameter interactions would elevate completeness.

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 only explains the 'conversation' parameter ('recent messages for reproduction'). No guidance is given for 'message' (required) or 'context' (default empty). This leaves two-thirds of the parameters semantically unexplained, failing to meet the need for compensation.

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 reports a bug, missing feature, or feedback, with a specific verb and resource. It distinguishes from all sibling tools, which are unrelated (connect, marketplace, etc.). This is a model of purpose clarity.

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: whenever a bug/feature/feedback needs to be reported. It does not explicitly state alternatives or exclusions, but there are no competing tools for reporting. The lack of explicit 'use when' is acceptable given the uniqueness of this tool among siblings.

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 safety. The description adds no extra behavioral context beyond the annotations, which is acceptable but doesn't enhance beyond structured data.

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 short sentence with no fluff or redundancy. Perfectly concise 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?

Given the extreme simplicity (no params, no output schema, annotations cover safety), this description is fully complete. It tells exactly what the tool does with no missing 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 tool has zero parameters, so schema coverage is effectively 100%. Per the rubric, the baseline for 0 params is 4. No additional parameter description is needed.

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 resource ('current MCP platform and adapter versions'), clearly distinguishing it from sibling tools like connect or marketplace. It's unambiguous and precise.

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 as a quick informational query, but provides no explicit guidance on when to use versus alternatives. No when-not or alternative mentions; for a trivial tool, this is adequate but not exemplary.

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 context about what data the tool returns, which is useful, but it doesn't describe any deeper behavioral traits such as freshness, permission requirements, or network implications.

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, tightly scoped sentence listing the return contents in a readable order. Every phrase adds information and there is 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?

This is a simple, zero-parameter, read-only inspection tool, and the description covers the essential return categories. It does not specify the exact output structure or possible error conditions, but for a toolkit status utility, the description is sufficiently complete to guide correct 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 and the schema supplies full coverage of that fact. With no parameters, the description's job is simply to frame what the tool returns, which it does clearly. Therefore, 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?

Description starts with 'Returns' and clearly identifies the resource ('current toolkit state') plus specific elements included: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a precise verb+resource statement and naturally distinguishes the tool from siblings like show_version or connect, which have narrower 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 implies usage through its content: if you need to inspect the toolkit state, this is the tool to call. However, it provides no explicit when-to-use vs alternatives or exclusions, so it stays at the 'implied usage' level rather than offering clear 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 declare readOnly, idempotent, non-destructive. The description adds substantial beyond-annotation context: hosted platform, credential-free access, prepaid payment requirement, official non-confidential data source, and LGPD controller responsibility. No contradiction.

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 text is brief and front-loaded with the core purpose, adding payment and legal context in a compact paragraph. It could be slightly more structured, but every sentence adds relevant 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?

Given no output schema and 5 optional-looking parameters with no descriptions, the description leaves important gaps: it does not state what inputs are valid, whether at least one is required, or what the response contains. It covers cost and legal aspects, but not invocation correctness.

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 5 properties with 0% description coverage, and the description does not explain any parameter, format, or combination rules. Although names like cpf and numero_processo are suggestive, the description adds no meaning beyond the schema property names, so it fails to compensate for low 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 identifies the tool as a TRF6 process consultation against an official source, with a specific verb ('consultar' in the name and 'consulta' in text). It differentiates it from unrelated siblings like authenticate or marketplace, though it could state 'consultar processo judicial' more explicitly.

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 useful context: official source, no platform credentials, prepaid credit per query, and LGPD data control. It implies this is for legitimate citizen-available queries but does not explicitly state when to use versus alternatives or when not to use.

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