Tribunal TRT13: Consulta Processual

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

The description adds useful behavioral context beyond the annotations: a token call creates a session-only login, no-args returns a link, and config-based header auth gives a non-expiring connection. It does not describe error cases or response details, but the annotations already cover the basic safety profile.

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 dense single passage mixing user instructions, config advice, and tool-call syntax. It is informative but not tightly structured; the 'Best:' configuration guidance could be separated or trimmed to make the actual tool invocation pattern stand out more clearly.

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 one-parameter auth tool with no output schema, the description covers both invocation modes and the recommended permanent alternative. It does not explicitly state what the tool returns, but that is acceptable given the absence of an output schema and the simplicity of the 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?

Schema coverage is 0%, and the description fully compensates by explaining that the optional token is a JWT/access token obtained via browser login. It also clarifies the no-args mode, which is essential for the agent to use the tool correctly.

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 an authentication flow for MCP.AI: browser login, token exchange, and login-link generation. It specifies the resource (MCP.AI) and the action (log in/authenticate), and it is distinguishable from sibling tools like connect or marketplace.

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 contrasts permanent config-based auth ('Best: add it to this server's config as a header') with session-only token calls, and instructs calling with no args to obtain the login link. It does not explicitly reference sibling tools, but the guidance is clear enough for choosing between no-arg and token-arg invocation.

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, and non-destructive hints, but the description adds valuable behavioral detail: the exact output format (authenticated:true and empty pending[]) and what happens when credentials are missing (connect_url and per-install URLs). This goes beyond the annotations and provides actionable expectations without 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 description is two sentences, front-loaded with the primary action ('Returns connection status and URLs'), and every sentence adds information about behavior. There is no fluff or redundancy, making it extremely concise and effective.

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), the description is complete. It explains the two possible outcomes and the URLs involved, which is sufficient for an agent to understand what to expect and when to call it. No additional context is needed.

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 is 4 because there is nothing to explain. The schema coverage is 100% (trivially), and the description does not need to elaborate on parameters. No additional semantic value is required beyond what the schema provides, which is nothing.

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 explicitly describes two key scenarios (all providers connected vs. missing credentials). It distinguishes from siblings like authenticate by focusing on status rather than authentication actions, making its purpose unambiguous.

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 it (to check connection status) and provides context about what happens in different states, but it does not explicitly mention alternatives or exclusions. The behavior is clear enough for an agent to decide when to call this tool, though it lacks a direct 'use this instead of X' statement.

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 (readOnlyHint=false, openWorldHint=true), the description richly discloses behavior: invoke works even when the MCP is not installed and does a one-off run without bloating the tool list; missing credentials trigger a connect link; a paid MCP with empty wallet triggers a checkout/top-up link followed by retry; and writes require workspace owner/admin. It also flags installed_in_toolkit vs installed_in_workspace and that publish_prompt links work without login. This is genuinely valuable behavioral context.

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 fairly long, but nearly every sentence carries distinct information: the install-vs-invoke distinction, one-off run behavior, credential/checkout links, owner/admin requirements, and the prompt library. The long run-on sentences could be better structured, but the front-loaded opening is effective and there is little redundant 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?

Given the tool's complexity (23 parameters, 0 required, no output schema), the description covers the important behavioral edge cases: one-off invoke, connect and checkout links, write permissions, and prompt-library flows. The main completeness gap is that parameters are not mapped systematically to operations, and the sibling tool boundaries (report_bug/connect/authenticate) are left ambiguous — but the description is still far above average for such a multi-action 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?

Schema description coverage is 0% across 23 parameters, so the description must compensate. It does explain the central `action` enum meanings (search, describe, install, invoke, subscribe/cancel, prompt ops) and mentions the tool_id/cost/auth workflow. But most parameters (cancel_reason, conversation, prompt_package, report_context, arguments, tier_slug, prompt_vars, etc.) are never mapped to any semantic workflow, leaving a large burden unresolved.

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 this as the mcp.ai marketplace — 'the in-platform catalog of every MCP/tool, AND the way to run them' — and lays out the core search → describe → invoke flow. It distinguishes this from MCPs themselves and from sibling tools, but it is a mega-tool covering 10+ sub-operations (report_bug, subscribe, prompt library, install, etc.), so the singular purpose is broad.

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 valuable decision guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', plus how list_tools, subscribe/cancel, report_bug, and request_mcp fit. However, it doesn't address overlaps with siblings (e.g., an actual sibling report_bug tool exists, and connect/authenticate siblings are relevant when invoke returns a connect link).

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, destructiveHint=false, and idempotentHint=true. The description adds the key behavioral context that the conversation array is needed for reproduction, which is useful beyond annotations. However, it does not explain side effects (e.g., whether a ticket is created) or any auth requirements, so it doesn't go beyond a minimum viable level.

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 the second sentence adds a critical usage detail. Every word earns its place; no fluff or redundancy.

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 report tool with 3 params and no output schema, the description covers the core purpose and the most important parameter (conversation). But given zero schema descriptions, the 'context' parameter is left unexplained, and there is no indication of what happens after submission (e.g., confirmation, response). This is adequate but with 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%, so the description must compensate. It provides some meaning for the 'conversation' parameter ('Include the conversation array with recent messages for reproduction.') and implied meaning for 'message' as the bug text. However, it does not explain the 'context' parameter at all, leaving a meaningful gap given the lack of schema 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 function: 'Report a bug, missing feature, or send feedback.' The verb 'report' plus the specific resource (bug/feature/feedback) makes the purpose explicit. This also distinguishes it from sibling tools like authenticate, show_version, and tribunal process consultation.

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 direct usage guidance: 'Include the conversation array with recent messages for reproduction.' This tells the agent what to do when invoking the tool. It does not explicitly mention when not to use it or alternatives, but the context is clear for a feedback/reporting operation.

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 establish read-only, idempotent, non-destructive behavior. The description adds that the output contains the current MCP platform and adapter versions, but it does not describe any additional runtime behavior, such as whether authentication is required or how the version data is sourced.

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 packs the entire purpose into one line with no filler or repetition. 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?

For a zero-parameter utility that reports versions, the description is complete: it states what the tool does and what information will be shown. Supporting annotations eliminate any ambiguity about safety, and no output schema is necessary for this simple case.

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, so the schema already defines everything needed. No description-level parameter detail is necessary, matching the baseline for a no-parameter tool.

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'), making the tool's purpose immediately obvious and distinguishing it 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 implies usage: call this when the user needs version information for the MCP platform or adapters. However, it provides no explicit guidance about when to prefer another tool or any alternatives/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=true, idempotentHint=true, and destructiveHint=false, so the safe non-mutating behavior is covered. The description adds value by detailing exactly what state is returned, which is useful contextual information beyond the annotations. It does not overstate behavior or introduce 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 a single, polished sentence that lists exactly what is returned without fluff. Every clause provides substantive detail, making it highly efficient and easy for an agent to parse quickly.

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, no output schema, and only reads the toolkit state, the description fully specifies the information returned. The simple scope of the tool means that no additional behavior, error handling, or prerequisites need to be documented.

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 and the schema coverage for parameters is 100% (none exist). The description correctly implies this is a fixed-state query with no inputs. The baseline for a no-parameter tool is 4, and the description adequately aligns with that.

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 defines the resource as the current toolkit state, enumerating exactly what is included: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it well from sibling tools like authenticate, connect, and marketplace.

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?

No explicit guidance is given for when to use this tool versus alternatives. While the read-only nature is implied by the description, there is no mention of when not to use it or a recommended alternative for different needs, such as show_version for version info.

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 context beyond annotations by stating it is hosted by the platform, does not require platform credentials, and that data is not confidential. It also notes the client's responsibility under LGPD, but lacks details on side effects or rate limits.

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 has some redundancy (e.g., mentioning 'consulta em fonte oficial' twice) and could be more concise, but it is not overly verbose.

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?

It provides context about prepaid credits and data privacy, but lacks information about expected output and parameters, leaving the tool's full usage incomplete.

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 parameters grau and numero_processo are not explained at all in the description. Since schema coverage is 0%, the description should compensate but does not.

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 procedural consultation tool for TRT13 court, using official sources. It distinguishes from sibling tools (authenticate, connect, etc.) by naming the specific action and object.

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 mentions the need for prepaid credit and that it uses official sources, but does not explicitly say when to use this vs alternatives or provide conditions for use.

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