Tribunal TSE: Certidão de Quitação Eleitoral

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

The description adds meaningful behavioral context beyond annotations by explaining the two authentication modes, the non-expiring nature of the config header, and the session-only nature of pasted tokens. It does not contradict the annotations and provides useful operational details.

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, then expands into usage modes. It is slightly dense but every sentence contributes useful information, with 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?

For a tool with one optional parameter and no output schema, the description covers the invocation modes, prerequisites, and the distinction between permanent and session-based authentication. It is sufficiently complete for an agent to select and invoke the tool correctly.

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 optional 'token' parameter as a JWT for session-only login and clarifying that calling with no arguments returns the login link. It adds the necessary meaning the schema lacks.

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: authenticating to MCP.AI via browser login and access token. It specifies the resource and action, but does not explicitly differentiate from the sibling tool '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 gives clear usage context: it explains the recommended permanent config-header approach versus the session-only token approach, and describes the no-args behavior. However, it does not provide explicit when-not-to-use guidance or mention alternative 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, idempotentHint=true, and destructiveHint=false. The description adds specific behavioral context about response contents (authenticated, pending[], connect_url) and conditional behavior based on credential state, going beyond simple annotation repetition.

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 only two sentences and conveys all necessary information without redundancy. It is front-loaded with the core action and then adds conditional details.

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 parameterless tool, the description explains the two primary states and what fields to expect. It does not explicitly cover intermediate states or confirm return format, but it is largely complete for its 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?

The tool has zero parameters, so schema coverage is trivially 100%. The description does not need to explain parameter semantics; the baseline of 4 applies.

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 a specific action: 'Returns connection status and URLs.' It distinguishes this from sibling tools like 'authenticate' by focusing on status reporting, not performing authentication.

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 on when the tool is relevant by describing different states: when all providers are connected vs. when credentials are missing. It implies this is the tool to check connection status before authenticating, but does not explicitly exclude alternatives or provide 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 only say openWorldHint true and readOnlyHint false, but the description adds crucial behavioral context: invoke runs one-off without installing, writes require owner/admin, invoke returns connect or checkout links for credential/payment gaps, and search/describe flag installation status. This goes well beyond the sparse annotations and discloses side effects clearly, with no 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 long (a dense paragraph) but every sentence carries operational information—core flow, invoke vs install, permissions, credential/payment behavior, prompt library. It is front-loaded with the main purpose and avoids fluff, though it could benefit from structured formatting (bullets) to improve scannability. Still appropriately sized for the tool's 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?

Given the tool has 14 actions, 23 parameters, no output schema, and sparse annotations, the description supplies essential context: how to discover MCPs, how to run them one-off, when to install permanently, permission requirements, and prompt library usage. It does not detail every parameter or action, but covers the main decision paths and edge cases (credentials, payment). Adequate for a complex tool, though some gaps remain.

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 has 23 parameters with 0% description coverage, so the description must compensate. It explains the action parameter's role and implies how mcp_id, tool_id, and arguments are used for invoke, and mentions prompt_vars for prompt filling. However, many parameters like limit, immediate, conversation, prompt_targets, and cancel_reason remain unexplained, leaving the agent guessing at their semantics. Partial compensation, not complete.

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 marketplace as the official catalog and execution layer for MCPs and prompt library, and outlines the core flow (search → describe → invoke). It distinguishes from sibling tools like authenticate, connect, and report_bug by positioning itself as the central discovery/run hub, so the agent understands its unique role.

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?

Explicit guidance is provided on when to use invoke vs install ('prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT'), when to use list_tools, subscribe/cancel, report_bug, and request_mcp. It also notes permission requirements for writes and behavior when credentials/payment are missing, giving clear decision-making criteria.

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, idempotentHint=true, and destructiveHint=false, covering basic safety. The description adds useful context about including the conversation array for reproduction, which is not in annotations. However, it doesn't disclose what happens after reporting (e.g., side effects or network calls), so the transparency is moderate.

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, consisting of two short sentences that front-load the purpose and then add a critical usage instruction. No word is wasted, and the structure is optimal for quick comprehension.

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 three parameters and no output schema, the description is only partially complete. It clearly conveys the intended use but fails to document the content of 'message' or the function of 'context'. Given the simplicity of the tool, a bit more parameter guidance would make it fully self-contained.

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 only explains the 'conversation' parameter by saying to include it for reproduction, but it does not clarify the meaning of the required 'message' parameter or the optional 'context' parameter. This is a significant gap for an agent to correctly fill all 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 clearly states the verb 'report' and the resources 'bug, missing feature, or feedback', making the tool's purpose immediately obvious. It also distinguishes itself from sibling tools by its explicit reporting function, which none of the siblings share.

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: whenever a bug, missing feature, or feedback needs to be sent. It doesn't explicitly mention when not to use it or alternatives, but the sibling tools are clearly unrelated, providing enough context. The instruction to include the conversation array adds a practical usage note.

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, so no contradiction. The description adds that it reports both platform and adapter versions, providing minor context beyond annotations, but does not disclose other behavioral details like output format or connectivity requirements.

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 tool's function with no wasted words. It is front-loaded and clear.

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, and no output schema, the description is complete. It states exactly what versions are shown. Annotations already cover safety. 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 parametersarguments, and the schema has no properties. Per the rubric, a 4 is baseline for no parameters. The description adequately conveys the tool's purpose without needing to describe 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 clearly states the tool shows MCP platform and adapter versions with a specific verb ('show') and resource ('versions'). It is distinct from sibling tools like authenticate or connect, though it does not explicitly differentiate from any similar version-checking tool.

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 the tool is used to check current versions, but it does not explicitly state when to use it or contrast with alternatives. Given the sibling set, it is clear enough for a version query, but no explicit usage guidance is provided.

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, covering safety and idempotency. The description adds detail about returned content but does not disclose additional behavioral traits beyond what annotations already provide, so the baseline 3 applies.

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 front-loads the primary purpose ('Returns the current toolkit state') and then efficiently lists the specific components returned, with 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?

Without an output schema, the description sufficiently lists what is returned (installed MCPs, connection status, accounts, catalog tool counts). This is complete for a query tool with no inputs, and the sibling context clearly positions it as the information retrieval 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?

With zero parameters, the schema coverage is 100% vacuously. Per guidelines, a baseline of 4 is appropriate since no parameter explanation is needed and the description adds no irrelevant 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 explicitly states the tool returns the current toolkit state, listing specific details (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like connect, authenticate, and marketplace, which are action-oriented.

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 it is for querying toolkit state but does not explicitly specify when to use it over alternatives. It lacks guidance on exclusions or when not to use, though the context of read-only info tool 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 the tool as read-only and idempotent. The description adds valuable behavioral context: it is hosted by the platform, requires no platform credentials, costs per query, and respects LGPD with the client as data controller. This goes beyond annotations 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 concise (three sentences) and front-loaded with purpose, then covers hosting, billing, and legal aspects without unnecessary fluff. It earns a strong score for density of information, though it could be slightly more scannable.

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 query tool with no output schema, the description provides decent context: purpose, cost model, and data privacy responsibilities. However, it omits details about return values, error scenarios, or any rate limits, and the lack of parameter semantics makes it incomplete for an agent to use effectively without additional assumptions.

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 does not compensate by explaining any parameter usage. While parameter names are self-explanatory (cpf, name, birthdate), the description omits any guidance on required vs. optional fields, formats, or how parameters relate to the query. This is a significant 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 identifies the tool as a query for 'Certidão de Quitação Eleitoral' from Tribunal TSE, using specific verb+resource ('consulta em fonte oficial'). It distinguishes itself from sibling tools (which are unrelated) by stating its exact function and official data source.

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 when to use the tool: to consult official Brazilian public data for electoral clearance, highlighting that no platform credentials are needed and that it is a paid service with prepaid credits. Though it does not explicitly mention alternatives or exclusions, the context is sufficient for an agent to infer appropriate usage.

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