Tribunal TRT5: Certidão Eletrônica de Ações Trabalhistas (CEAT)

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

Annotations already signal idempotentHint=true and non-destructive behavior. The description adds meaningful context about what happens with and without a token, explains permanent vs. session-only auth, and mentions the config header. It doesn't go deeper into error cases or side effects, but the empty bar is met well given 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 bit run-on and mixes server config advice with usage instructions, but every sentence adds actionable content. It could be tightened, but it remains concise overall and is front-loaded with the primary purpose.

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 an authentication tool with no output schema, the description covers the full user and agent workflow: browser login, token acquisition, permanent vs. session login, and argument handling. It lacks explicit error/edge-case behavior, but that is a minor gap for such a small-tool interface.

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 only lists a `token` string with zero description, so the description carries the weight. It clearly explains that `token` is a JWT pasted from the user and that omitting it triggers a link retrieval. This sufficiently compensates for the 0% schema_description_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 authentication as the operation, specifies the target (MCP.AI for IDE agents), and explains the login flow (browser login, copy token, provide token to the tool). It does not explicitly differentiate from sibling tools like 'connect' or 'marketplace', so it misses the full 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 highly explicit usage guidance: add the token as a config header for a permanent connection, paste token for session-only login, call with `token` after pasting, or call with no arguments to get the link. This clarifies the exact invocation scenarios without leaving the agent guessing.

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. The description adds valuable behavioral detail beyond annotations by specifying the conditional response shape: authenticated:true with empty pending[] when connected, and connect_url when credentials are missing.

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 each sentence adds conditional detail without redundancy. No wasted words.

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, the description sufficiently explains the expected return values and their conditional behavior. It is complete for a simple status-check tool and complements the sibling set without over-explaining.

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. There are no parameter semantics to add, and the description correctly focuses on behavior rather than inputs.

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 starts with a specific verb 'Returns' and clearly identifies the resource: connection status and URLs. It also differentiates from siblings like authenticate by describing status/URL reporting rather than auth initiation.

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 usage context: when all providers are connected vs when credentials are missing. It does not explicitly name alternatives among siblings, but the conditions imply when this status-check tool is appropriate.

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 reveals key behaviors beyond the sparse annotations: invoke works even without install, returns connect links for auth or checkout links for payment, and the one-off install behind invoke. It also discloses permission requirements and the prompt library's distinct behavior. This far exceeds what annotations provide (readOnlyHint=false, openWorldHint=true).

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 long single paragraph but extremely dense with essential information. It is front-loaded with the main purpose and covers critical workflows, permissions, and edge cases. While it could benefit from bullet points, every sentence adds value, and the length is justified by the tool's multi-action complexity.

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 optional parameters, 14 actions, minimal annotations, and no output schema, the description covers the major contexts: search/discovery, invoke vs install, auth/payment handling, permission requirements, and the prompt library. It does not detail every action-specific parameter (e.g., resume, cancel_reason), but the core use cases and edge cases are 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 must compensate. It explains the meaning of the 'action' parameter values (search, describe, invoke, install, etc.) and mentions tool_id and arguments in the core flow. However, most of the 23 parameters (prompt_*, cancel_reason, immediate, etc.) are not explicitly mapped, leaving gaps. Some parameters like 'query' and 'limit' are self-explanatory, so the description provides partial 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 defines the marketplace as both a catalog and execution platform, stating 'the in-platform catalog of every MCP/tool, AND the way to run them.' It explains the core flow (search → describe → invoke) and explicitly differentiates itself from siblings by covering distinct actions like 'report_bug' and 'request_mcp'. The purpose is concrete and well-differentiated.

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 usage guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT'. It explains when to use search/describe/invoke, mentions list_tools for callable tools, and notes 'Writes ... require workspace owner/admin'. This gives clear when-to-use and 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 indicate idempotentHint=true and destructiveHint=false, so the tool is safe and idempotent. The description adds that it includes a conversation array for reproduction, which is useful context. However, it doesn't disclose what happens after reporting (e.g., whether it creates a ticket, sends an email) or any side effects. With annotations covering safety, the description adds some value but not extensive behavioral 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 two sentences, concise and front-loaded. It states the purpose and the key requirement (include conversation array). No wasted words.

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 has 3 parameters, no output schema, and no nested objects. The description explains the purpose and mentions the conversation parameter, but doesn't clarify the 'context' parameter or what the response will be. Given the simplicity, it's adequate but could be more complete by explaining the 'context' parameter and expected outcome.

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. The description mentions 'conversation array' and 'recent messages', which adds meaning to the 'conversation' parameter. However, it doesn't explain 'context' or 'message' beyond what the schema provides. The description partially compensates for the lack of schema descriptions but not fully.

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 uses a specific verb ('report') and resource ('bug'), and distinguishes from siblings by covering feedback and feature requests. However, it doesn't explicitly differentiate from sibling tools like 'marketplace' or 'toolkit_info', but the purpose is clear enough.

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 bugs, missing features, or feedback) but does not provide explicit guidance on when not to use it or alternatives. It mentions including the conversation array for reproduction, which gives some context, but lacks exclusions or comparisons to sibling tools.

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, destructiveHint=false, and idempotentHint=true. The description adds the specific behavior of returning MCP platform and adapter versions, which is beyond the annotations. It does not contradict annotations and provides useful context about what the tool reports.

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 fully conveys the purpose. No fluff, perfectly 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 simplicity (no parameters, no output schema, clear read-only operation), the description is complete. It states exactly what the tool does and is consistent with annotations. 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 0 parametersamentations, so the schema covers 100% (there is nothing to describe). Baseline is 4 for 0 parameters. The description does not need to add parameter semantics since none exist.

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 names the exact resource ('current MCP platform and adapter versions'). It clearly distinguishes this tool from siblings like authenticate or connect by focusing on version information. 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 implies usage for checking version info, but does not explicitly state when to prefer it over alternatives or any exclusions. For a simple version tool, this is clear enough context; no need for deeper 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 establish read-only, idempotent, and non-destructive behavior. The description adds value beyond those flags by specifying what the read includes—installed MCPs, connection status, accounts, and catalog counts—providing useful behavioral context about the scope of the snapshot.

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 sentence that is front-loaded with the action and resource, and every clause adds meaningful detail. 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 tool with no output schema, the description adequately covers the returned information: installed MCPs, connection status, connected accounts, and catalog tool counts. It could specify the exact structure or whether status is live vs cached, but the current detail is sufficient for a straightforward info 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 input schema has zero parameters, so there is nothing to disambiguate. The description appropriately focuses on return semantics rather than inputs, which is the correct trade-off for a parameterless 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 the specific verb 'Returns' and identifies a clear resource ('current toolkit state') with enumerated content (installed MCPs, connection status, accounts, catalog tool counts). This fully distinguishes it from siblings like show_version, authenticate, or connect.

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 clearly implies the tool is for inspecting overall toolkit state by listing exactly what it returns. It does not explicitly name alternatives or exclusions, but the context makes it obvious this is the overview tool rather than an action-oriented sibling.

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 readOnly and non-destructive behavior. The description adds meaningful behavioral context: no platform credentials needed, pay-per-query with prepaid credit, data is not confidential, and LGPD responsibilities. This goes beyond what annotations provide, offering valuable operational and legal 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 concise, with three sentences. It front-loads the main purpose and includes necessary operational details (payment, credentials, LGPD) without unnecessary verbosity. Slightly more structure could improve readability, but it is efficiently written.

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 good context about the source, payment, and legal implications. However, it does not explain the parameters or what the output will be (no output schema exists). For a simple tool with two parameters, missing input guidance and return expectations leaves the definition 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 input schema has two parameters (cpf, cnpj) with no descriptions, and the description does not mention them at all. With 0% schema coverage, the description should compensate by explaining that either CPF or CNPJ is required, but it does not. The parameter names are self-explanatory, but the lack of context on usage or mutual exclusivity is a significant gap.

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 a 'consulta' (consultation) of CEAT (Certidão Eletrônica de Ações Trabalhistas) from TRT5, in an official source. It uses a specific verb and resource, and it is easily distinguishable from sibling tools which are general platform utilities (authenticate, connect, etc.).

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 CEAT queries but does not explicitly state when to use vs alternatives or provide exclusions. It gives context about the payment model (prepaid credit) and official source, which are prerequisites, but lacks explicit guidance on selection among tools.

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