Tribunal TRF2: Processo

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

The description goes beyond annotations by explaining the key behavioral difference between permanent config-based auth and session-only token-based auth, and by specifying that no-args calls return a login link. It does not describe possible failure modes or token validation behavior, but the main runtime behavior is adequately transparent.

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 and information-dense, with each sentence contributing a distinct mode or constraint. Minor awkward phrasing like 'log in in the browser' and the relatively long semicolon-heavy final sentence prevent it from being perfectly polished.

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 single-optional-parameter authentication tool, the description covers the main invocation paths and the permanent-vs-session distinction well. It does not state what response or side effect follows a token-backed call, but its simplicity and the no-args 'get the link' behavior make the tool 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 input schema only declares an optional string token with no description (0% schema coverage), so the description carries the full burden. The description fully compensates by explaining the token is a JWT/access token, when to pass it, and that omitting it will return the login link.

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 authentication/login tool: log in in the browser, copy the access token, and provide it via configuration or a token parameter. It does not explicitly contrast with a sibling tool, so it falls just short of the highest bar for purpose 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 gives explicit usage modes: add the token to server config for a permanent non-expiring connection, or paste the token into this tool for a session-only login, or call with no arguments to get the login link. It also tells the agent when to call with token vs. no args, which is strong practical 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by describing the two output states (connected vs. missing credentials) and the URLs returned, which goes beyond the structured 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?

Two sentences, front-loaded with the core purpose and then concise state-dependent behavior. No filler 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?

The description covers the main behavioral outcomes (connected vs. missing credentials) and mentions return components (authenticated, pending[], connect_url, per-install URLs). While it doesn't mention edge cases like partial connection, the tool is simple enough that this is adequate without a dedicated output schema.

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 per the baseline rule, a score of 4 is appropriate. The description does not need to explain parameters since there are none.

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 resource ('connection status and URLs'), clearly distinguishing it from siblings like authenticate and show_version. It also adds state-dependent details, reinforcing its purpose.

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 on what the tool returns (status and URLs) and implies it should be used to check connection state, not to perform authentication. However, it does not explicitly state when to use this tool over alternatives like authenticate, so it lacks 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?

Discloses many behaviors beyond annotations: invoke works even when the MCP is not installed, returns a connect link for credential needs, returns a checkout/top-up link for paid MCPs, and requires retry after user action. It also clarifies that install is permanent while invoke is one-off, and that prompt library is about text prompts, not MCPs.

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 dense paragraph that mixes multiple domains: MCP discovery, execution flow, billing, admin rules, and prompt library. Every sentence adds value, but the lack of structure makes it hard to scan. Bullets or section breaks would improve readability.

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 23 parameters and no output schema, the description is remarkably complete: it covers the core flow, one-off invoke behavior, auth/top-up edge cases, admin requirements, and the prompt library. Gaps remain for actions like resume, the immediate parameter, and specific return shapes for some actions.

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 carries the burden. It explains key parameters like action, query, mcp_id, tool_id, arguments through the search/describe/invoke flow, and prompt-related parameters via search_prompts/get_prompt/publish_prompt. However, some parameters (immediate, resume, conversation, cancel_reason) are not explicitly addressed.

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 is the official mcp.ai marketplace — the catalog of every MCP/tool and the way to run them. It uses specific verbs and resources (search, describe, invoke, install) and distinguishes from sibling tools like authenticate/connect by focusing on discovery and execution.

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 guidance on when to use each action: core flow (search → describe → invoke), prefer invoke over install for one-off use, use install for permanent toolkit additions, list_tools to see what's callable, request_mcp when nothing fits. Also notes that writes require 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 provide safety flags (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds no extra behavioral context beyond that, so it neither contradicts nor significantly enhances transparency.

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, consisting of two short sentences with no unnecessary fluff. It directly communicates the purpose and a key usage hint.

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, the description covers the essential action and a key input (conversation). It does not explain return values or post-report behavior, but given the lack of an output schema and 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?

Schema coverage is 0%, so the description must compensate. It explains the 'conversation' parameter by suggesting it holds recent messages for reproduction, but does not clarify 'context' or 'message'. Parameter names are self-explanatory, but the description adds only partial value.

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 is distinct from sibling tools like authenticate or connect, so it stands out.

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 the tool (when reporting issues) but does not explicitly state usage context or contrast with alternatives. It gives a hint about including conversation for reproduction, but lacks explicit guidance on when to prefer this tool over others.

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 is consistent with the read-only and idempotent annotations, but it does not add any extra behavioral context such as permissions, side effects, or rate limits. Since annotations already cover the main behavioral traits, the description adds minimal value.

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, clear sentence with no unnecessary words or redundancy. It is optimally 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 description sufficiently indicates what the tool returns (platform and adapter versions), but it could be slightly more explicit about the output format or structure. However, given the simplicity of the tool, it is largely 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 tool has no parameters, and the description correctly implies that none are needed. The schema is empty, so no additional parameter meaning is required.

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 with the verb 'Show' and specifies the resource ('current MCP platform and adapter versions'), effectively distinguishing it from 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 does not explicitly state when to use this tool versus alternatives or when not to use it. It lacks usage context or prerequisites.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds the behavioral detail that this tool takes a snapshot of toolkit state and reports it, which enriches what a caller can expect.

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 one tight sentence that starts with the action 'Returns' and then delivers a structured list of the returned information. There is no filler or redundant repetition of the tool name.

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 responsibility for explaining the response shape, and it does so by naming installed MCPs, connection status, accounts, and per-tool catalog counts. This fully covers the simple state-summary nature 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?

The tool takes zero parameters and the schema contains no properties, so there is no parameter semantics to explain. Baseline 4 is appropriate because the description gives a complete picture of what the no-input tool returns.

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 names a specific verb-resource pair: 'Returns the current toolkit state' and then enumerates the exact contents. This clearly differentiates toolkit_info from action-oriented siblings like authenticate, connect, and marketplace, and even from 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 implies a clear context for use: when an agent needs an overview of installed MCPs, their connection status, connected accounts, or catalog tool counts. It does not explicitly name alternatives or exclusions, but the purpose is distinctive enough that 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?

Annotations already declare readOnlyHint=true and destructiveHint=false; the description adds complementary behavioral context: no platform credentials, prepaid credit billing, official public data, non-confidential scope, and LGPD data-controller responsibility. This meaningfully enhances what annotations provide.

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 moderate length with a front-loaded purpose statement followed by payment, data-source, and LGPD context. Each sentence adds relevant information, though the LGPD sentence is somewhat boilerplate and could be tightened.

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?

There is no output schema and no mention of return values or result format, while the five-parameter input schema has no descriptions. The description covers legal and commercial context but is incomplete for an agent to know how to structure a valid consultation.

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% and the description does not mention any of the five parameters (cpf, oab, cnpj, nome_parte, numero_processo), their formats, optionality, or required combinations. With no schema descriptions, the description carries the full burden and completely fails to compensate.

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 states a specific action: 'Processo, consulta em fonte oficial' for Tribunal TRF2, which clearly identifies the resource and operation. It is distinguishable from unrelated siblings such as authenticate and marketplace, though 'Processo' remains somewhat generic without saying it returns case/legal proceeding details.

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 useful context: it is hosted by the platform, requires no platform credentials, and charges prepaid credits per consultation. However, it does not explicitly state when to prefer this tool over alternatives or when not to use it, leaving usage guidance implied rather than explicit.

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