Tribunal TRF3: Processo

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

The description discloses behavioral traits beyond the annotations: it explains the permanent vs. session-only login distinction, the behavior when called with no args (returns a link), and the token-based flow. Annotations already indicate idempotency and non-destructiveness, and the description adds useful context about session persistence 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 compact and front-loaded with the core purpose. Three sentences cover the main flow, the recommended permanent setup, and the session-only alternative. It is slightly dense but every sentence contributes useful information without 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?

Given the simple schema (one optional string, no output schema), the description is reasonably complete: it explains both authentication modes, the parameter semantics, and the no-args behavior. It does not cover error cases or return values, but these are less critical for an auth tool with no 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?

With 0% schema description coverage, the description compensates by explaining the 'token' parameter as a JWT to paste, and clarifying that it is optional (no args gets the link). This adds meaning beyond the bare schema definition of a string property, though it could be more explicit about token format or validation.

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 to MCP.AI for IDE agents via browser login and token exchange. It specifies the exact actions ('log in in the browser, copy the access token', 'call with { token: ... }') and distinguishes itself from siblings by focusing on authentication rather than connection or marketplace functions.

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: the recommended permanent approach (config header) versus the session-only approach (passing a token), and the no-args behavior to get a link. It does not explicitly name alternatives or state when not to use the tool, but the two modes are clearly differentiated.

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, covering the safety profile. The description adds valuable context beyond annotations: return fields under different conditions (authenticated vs. missing credentials) and the presence of pending[] and connect_url. It does not mention any side effects or rate limits, but none are expected for a read-only status tool.

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 extremely concise: two sentences, each earning its place. The first sentence states the primary purpose, and the second clarifies conditional behavior. There is no filler 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 status tool with no params and no output schema, the description covers the main scenarios (all connected vs. missing credentials) and indicates the shape of the response. However, it does not explicitly describe partial connectivity states or the exact format of URLs, but these are not essential for correct invocation.

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 describes an empty object, so there is no parameter information to add. The baseline is 4 for a parameterless tool, and the description correctly focuses on behavior rather than invoking parameter details.

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 a specific verb ('returns') and resource ('connection status'). It implicitly distinguishes from the sibling 'authenticate' by focusing on status rather than action, and provides scenario-specific behavior.

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: to check the current connection state and obtain URLs when credentials are missing. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to decide without ambiguity.

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 key behavioral traits beyond annotations: invoke works on uninstalled MCPs without adding them to the toolkit, returns connect links for missing credentials, checkout links for empty wallets, and retry logic. Also clarifies that install makes MCPs permanent and that writes need workspace owner/admin. No contradiction with 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 long but every sentence adds distinct value: it opens with a clear scope statement, then efficiently covers the flow, key distinctions, permissions, and edge cases. No filler or repetition; the density is justified by the tool's 14 actions and 23 parameters.

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 high complexity and no output schema, the description covers the main flows, permissions, auth/payment edge cases, and the prompt library. It does not specify return formats for every action, but it gives enough behavioral context (e.g., invoke returns connect/checkout links, get_prompt returns text with variables filled) to be useful.

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 zero descriptions (0% coverage), so the text must compensate. It explains the meaning of action values (search, describe, invoke, install, etc.), tool_id (selected tool), arguments (passed to invoke), and prompt_slug/prompt_vars. Not every parameter is documented (e.g., limit, immediate, tier_slug), but the core parameters are given useful context.

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 the official marketplace for discovering and running MCPs, covering both catalog search and execution. It distinguishes itself from siblings by describing the full lifecycle (search, describe, install, invoke, subscribe) that other tools like toolkit_info or connect do not cover.

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 when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT'. It also explains the decision flow (search → describe → invoke) and separates the prompt library actions, plus 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?

The description does not disclose what happens after reporting (e.g., ticket creation, email notification) or any side effects. The annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds no context about the actual behavior beyond the action itself.

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 sentences that cover the purpose and a key usage instruction. It is well-structured and free of unnecessary detail.

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 provides the core purpose and a hint about parameter usage, but omits details about expected output, error handling, or post-action effects. Given the simple nature of the tool and the presence of annotations, it is minimally complete but lacks depth.

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 clarifies the purpose of the 'conversation' parameter (for reproduction), but leaves 'message' and 'context' undefined. Since the schema provides no descriptions for these fields, the description only partially compensates for the lack of parameter documentation.

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: reporting bugs, missing features, or feedback. The verb 'report' and resource specification make the action unambiguous, and it is distinct from the sibling tools listed.

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 a specific instruction to include the conversation array for reproduction, which is a direct usage guideline. It implicitly indicates when to use this tool (when reporting issues), though it does not explicitly exclude alternative tools. Given no obvious alternatives exist, this is acceptable.

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 annotations already indicate readOnly, idempotent, and non-destructive behavior, and the description aligns with these without adding extra context (e.g., authentication needs, rate limits). Since the operation is trivial and read-only, the description is transparent enough, but it does not go beyond the 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 a single, concise sentence that is directly to the point. It is front-loaded with the action and the target, making it easy to understand 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?

The description is complete for a simple show operation, as it implies the return of version information. However, it could be slightly more explicit about the output format (e.g., listing platform and adapter versions separately), but this is a minor gap given the 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?

There are no parameters defined for this tool, so there is nothing to explain. The description is sufficient and no parameter-specific details are 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 clearly states the tool's purpose: showing current MCP platform and adapter versions. It is specific about the action (show) and the resource (versions), leaving no ambiguity.

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 any guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or conditions. It simply states what the tool does without usage context.

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 useful output content context, though it does not disclose whether connection status is live/network-dependent or how fresh the returned state is.

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 enumerates concrete output fields without filler. Every segment adds value: 'installed MCPs', 'connection status', 'accounts connected', and 'how many catalog tools each exposes'.

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 informational tool with strong annotations, this description is complete. It states the purpose and lists all output categories. Although there is no output schema, the enumerated return contents sufficiently cover what the agent needs to know.

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 input schema is empty, so schema description coverage is trivially 100%. There is nothing to explain about parameters, and the description appropriately focuses on the output rather than parameter semantics.

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 names a concrete resource ('current toolkit state'), then enumerates exactly what that includes: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like authenticate, connect, and 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 usage for checking overall toolkit status but does not explicitly state when to use this tool versus alternatives such as show_version or connect. The intended context is reasonably inferable, but there is no explicit when-to-use or when-not-to-use 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 and idempotentHint: true, covering the safe read nature. The description adds behavioral context beyond annotations: it specifies the payment model ('pague por consulta com crédito pré-pago'), states that data is not confidential ('não é dado sigiloso'), and outlines the client's data controller responsibility under LGPD. This provides valuable additional 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, a single paragraph of roughly 40 words, with the purpose front-loaded. It includes essential legal and cost disclaimers without excessive verbosity. However, the structure is a bit flat, mixing purpose with compliance statements, but still efficient.

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 11 parameters, none required, and no output schema, the description is incomplete. It does not explain what data is returned, typical query patterns, or which parameters are needed for different scenarios. The legal and cost context is useful, but the lack of output and usage guidance leaves an agent without enough information to craft effective queries.

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 description coverage is 0%, and the description does not explain any of the 11 parameters. While parameter names like 'cpf', 'cnpj', 'numero_processo' are self-explanatory, there is no guidance on which parameters are required, how they combine, or expected formats. The description fails to compensate for the lack of schema documentation, offering no added semantic value for the 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 explicitly states 'Tribunal TRF3: Processo, consulta em fonte oficial' which clearly identifies the resource (TRF3 processes) and the action (consultation). It is distinct from sibling tools which are unrelated (authenticate, connect, marketplace, etc.), so the purpose is 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 gives context that the tool is for consulting official Brazilian sources, mentions prepaid credit and LGPD compliance, and implicitly indicates usage for TRF3 case lookup. While it does not explicitly state when not to use or name alternatives, there are no related sibling tools, so the context is adequate for an agent to infer when to use it.

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