Tribunal TRT18: Consulta Processual

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

The description adds meaningful behavioral context beyond annotations: it distinguishes a permanent, non-expiring connection via config header from a session-only login via token paste. Annotations only indicate idempotent and non-destructive, and the description does not contradict them. It does not cover failure cases or side effects like token storage, but it discloses the key persistence 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 front-loaded with the essential login flow and is information-dense without excessive padding. It is somewhat run-on with multiple clauses, but each component earns its place: browser login, config header, token paste, and no-arg behavior.

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 authentication tool with no output schema, the description is largely complete: it explains both invocation modes, the permanent vs session distinction, and how the login link is obtained. It does not mention errors, expiry details for pasted tokens, or what the tool returns beyond the implied link, but the core workflow is well covered.

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 carries the full burden and succeeds. It explains the optional 'token' parameter precisely as a JWT to paste, and clearly states that calling with no arguments returns the login link. This fully compensates for the bare 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 identifies the tool as an MCP.AI authentication/login flow: 'log in in the browser, copy the access token' and paste it or persist it via config. It avoids tautology and explains the core resource being authenticated. It does not explicitly contrast with sibling tools like 'connect', 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 provides concrete usage modes: call with no args to get the login link, or call with { token: '<jwt>' } for a session-only login. It also recommends the preferred permanent option ('Best: add it to this server's config'). However, it does not explicitly say when to choose this tool over its siblings, so it lacks full alternative 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 this as a safe, read-only, non-destructive idempotent operation. The description adds useful behavioral context beyond annotations by explaining the two possible return states and the presence of connect URLs, which is valuable for 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 two sentences, front-loaded with the core purpose, and every clause adds meaningful detail about conditional outputs. 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 zero-parameter status tool with no output schema, the description fully explains the key return fields (authenticated, pending, connect_url, per-install URLs) and their conditional presence. It is complete enough for an agent to understand what to expect without additional detail.

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 zero parameters and schema description coverage is 100%, so there is no parameter information to add. With 0 parameters, the baseline is 4, and the description correctly focuses on return behavior instead.

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, which is a specific verb+resource. It also differentiates from siblings like authenticate by focusing on status reporting rather than establishing connections.

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 conditional guidance for when all providers are connected versus when credentials are missing, helping the agent understand what to expect. It does not explicitly name alternatives like authenticate for resolving missing credentials, but the usage context is strongly implied.

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 gives critical behavioral context beyond the annotations: the tool's open-world nature ("openWorldHint: true") is well-supported by the detailed description of how invoke can run tools without installing them. It explicitly clarifies that "invoke works even when the MCP is NOT installed" and details the auth/payment flows: "invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link." It also notes that "Writes require workspace owner/admin," which is a key authentication/authorization detail.

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, with three long paragraphs covering many features and flows. While it is informationally rich, it lacks structure (no bullet points, tables, or clear sections), making it harder for an agent to parse quickly. It contains a lot of imperative guidance but is not organized for rapid consumption. Still, every sentence 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?

The description is exceptionally complete given the tool's high complexity: it covers the primary use case (searching/using MCPs), the alternative flows (installing vs. invoking), the prompt library feature, user roles/permissions, and handling of edge cases (auth, payments, missing credentials).

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 `action` parameter's workflow thoroughly (search/describe/install differences) and touches on undefined parameters through examples like `tool_id` and `arguments` in the invoke context. However, it does not document any of the 23 schema parameters (0% schema coverage) nor explain fields like `immediate`, `tier_slug`, or `prompt_vars`. Since it never explicitly references parameter names, the agent must infer semantics from the schema alone.

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 this is the "official mcp.ai marketplace" and the "in-platform catalog of every MCP/tool" with an explicit core flow (search → describe → invoke). It provides specific examples of capability requests ("find an MCP that does X", "consulta um CPF") and distinguishes itself from the sibling tools by defining its role as a catalog and executor.

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 when-to-use guidance: "prefer invoke for a single/occasional use" versus "Use install only to make an MCP PERMANENT in the active toolkit." It also gives concrete workflow context ("Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool").

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 indicate idempotentHint=true and destructiveHint=false, and the description does not contradict them. It adds a small amount of behavioral context by asking for the conversation array for reproduction, but it does not disclose what happens after reporting or any 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?

Two short, front-loaded sentences describe the purpose and include the key usage hint. Every sentence earns its place, with no redundant or vague 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?

For a simple report tool with 3 parameters and no output schema, this is near minimal viable. The description provides enough to understand the core intent, but the lack of parameter-level detail and the string-vs-array ambiguity leave gaps for an agent to guess formats.

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 carry the burden. It only explains the conversation parameter, and calls it an 'array' while the schema types it as string with default '[]'. The 'message' parameter is implied by tool name, and the 'context' parameter is not mentioned at all.

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 starts with 'Report a bug, missing feature, or send feedback,' giving a specific verb and resource. It distinguishes this tool from the sibling tools, none of which are about reporting or feedback.

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 states when to use the tool: when a bug, missing feature, or feedback arises. It does not explicitly call out alternatives or exclusions, but no sibling tool offers this functionality, so the context is sufficient.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, providing safety information. The description adds no additional behavioral context beyond stating what it shows. It does not contradict the annotations, but it also doesn't enrich them with extra details like return format or side effects. Given the annotation coverage, 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 front-loads the purpose. Every word is necessary, with no filler or redundancy. It perfectly adheres to the principle of minimal yet complete 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?

For a simple informational tool with no parameters and no output schema, the description adequately explains what the tool does. It doesn't need to elaborate on return values because 'Show' implies a simple display of versions. The tool's simplicity means the description is complete without adding superfluous detail.

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 schema fully covers parameter semantics (100% coverage). According to the rubric, a baseline of 4 is appropriate for zero-parameter tools. The description does not need to add parameter details since there are none, and it correctly implies the tool requires no input.

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 with a specific verb ('Show') and a clear resource ('current MCP platform and adapter versions'). It distinguishes itself from sibling tools like authenticate or connect, which serve different functions. The purpose is unambiguous and directly tied to the tool's name.

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 context is clear: this tool is for retrieving version information. It does not explicitly mention alternatives, but given its unique purpose among the siblings (authenticate, connect, etc.), there is no ambiguity about when to use it. No exclusions are needed, so the absence of when-not guidance 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?

Annotations already declare readOnlyHint and idempotentHint true, so the safety profile is known. The description adds specific details about what is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond annotations. It doesn't contradict 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?

Single sentence that efficiently enumerates the exact information returned. 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 read-only info tool with no parameters and no output schema, the description fully covers what the agent needs to know: what state is returned.

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?

No parameters are present, so the description doesn't need to explain parameter semantics. Baseline for zero parameters is 4, and there's nothing to add.

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, enumerating specific components (installed MCPs, connection status, accounts, catalog tool count). This is specific and distinguishes it from siblings like show_version (which likely shows version info) and connect (which performs actions).

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 by describing what information it provides, giving clear context. However, it does not explicitly mention when not to use it or name alternatives. Since there are no complex conditions, the context is clear enough for an agent to choose it for inspecting toolkit state.

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 significant behavioral details beyond the annotations, such as the pay-per-consultation cost, lack of platform credentials, and the guarantee that data is not confidential. It also clarifies the data source (official Brazilian bodies), but does not detail error handling or response format.

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 verbose and includes redundant legal disclaimers (LGPD) and repetitive phrases about official sources. It could be shortened significantly without losing essential information, making it less concise than ideal.

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 sparse schema (only two parameters and no output definition), the description does not sufficiently cover what the tool returns or how the parameters interact. While it provides context about the data being non-confidential, it lacks details on expected results or usage edge cases.

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 provides no explanation of the parameters 'grau' or 'numero_processo', and the schema includes no individual descriptions. There is no indication of what values are valid or how they affect the consultation.

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 performs 'Consulta Processual' (process consultation) for TRT18, indicating it retrieves official court process information. It also clarifies that it is a paid service via prepaid credits, making the core 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 does not provide explicit guidance on when to use this tool versus alternatives. It only mentions it works without platform credentials, but fails to specify appropriate contexts, prerequisites, or exclusions. No alternatives are referenced.

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