Título e Local de Votação (TSE)

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

The description explains behavioral details beyond annotations: calling with no args returns a link, calling with the token establishes a session, and the config approach yields a permanent non-expiring connection. It aligns with the idempotentHint annotation (repeated calls with same token have same effect) and does not contradict any 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 two sentences but somewhat dense, packing instructions for both config and session approaches. It is well-structured (purpose, best practice, alternative) and every sentence carries useful information, though it could be tightened slightly without losing meaning.

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 param) and no output schema, the description covers the main behaviors: how to get the link, how to use the token, and the difference between permanent and session auth. It does not specify exact return values for the token-call path or error cases, but it is sufficiently complete for a single-parameter authentication 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 one optional 'token' property with zero description (0% coverage). The description fully compensates by explaining that the token is a JWT pasted from the browser, used for session-only login, and that omitting it returns the login link. This adds crucial meaning beyond the raw 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 states the tool's purpose: authentication for MCP.AI IDE agents via browser login and token usage. It distinguishes itself from siblings like 'connect' or 'marketplace' by focusing on the login/token flow. The verb 'log in' and resource 'access token' make the function 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 provides clear usage context: it explains the recommended permanent config method versus a session-only token approach, and indicates when to call with or without arguments. It does not explicitly compare itself to alternate tools like 'connect', but the usage scenarios are well-defined so an agent can decide when to invoke it.

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, which cover safety. The description adds valuable behavioral detail beyond these: it specifies the response fields (authenticated, pending, connect_url) and conditional output based on connection state, which is useful and non-contradictory.

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 focused sentences. The first states the main purpose, and the second adds the key conditional behaviors. No redundant or filler content.

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 that there are no parameters and no output schema, the description covers the essential cases: all connected vs. missing credentials. It explains both the successful and fallback states, making it sufficiently complete for a status-checking 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 has zero parameters, so the schema provides complete coverage. The description does not need to explain parameters but instead focuses on return behavior, which is appropriate. Baseline for zero params is 4.

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 begins with 'Returns connection status and URLs', using a specific verb and resource. It further explains the two distinct result states (authenticated:true vs. connect_url), which clearly sets it apart from siblings like authenticate and toolkit_info.

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?

It provides clear contextual guidance by describing what happens when providers are connected vs. credentials missing, implying when this tool should be called (e.g., to obtain a connect_url). However, it does not explicitly contrast with sibling tools like 'authenticate', so it falls short of an explicit when/not-to-use guide.

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?

Beyond the annotations (readOnlyHint=false, openWorldHint=true), the description discloses critical behaviors: invoke runs one-off without adding to the toolkit, returns connect/checkout links when credentials or payment are needed, writes require workspace owner/admin, and the prompt library stores text prompts rather than MCPs. This complements the annotations without contradiction.

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 dense, run-on block of text without visual structure (no bullet points or sections), though every sentence is relevant. Given the tool's 14 actions and 23 parameters, the length is justifiable, but it could be better organized to improve scannability.

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 highly complex tool with 14 actions, 23 parameters, and no output schema, the description covers nearly every aspect: the decision flow, auth/billing behaviors, ownership requirements, and the separate prompt library. It even describes expected outputs (connect/checkout links, full MCP profiles), making it remarkably 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?

With 0% schema description coverage, the description carries the burden and does explain core parameters via the action flow: `action`, `query`, `mcp_id`, `tool_id`, `arguments`. However, several parameters like `immediate`, `tier_slug`, `conversation`, `report_context`, and `prompt_body` are not explained, leaving some ambiguity for those actions.

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 opens with a specific definition: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates the action enum and explains its role in capability requests, installation, billing, and prompt library, clearly distinguishing it from sibling tools like connect or report_bug.

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 when-to-use guidance for key actions: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', and notes 'invoke works even when the MCP is NOT installed'. It also explains the core search→describe→invoke flow and when to use list_tools, request_mcp, and subscribe/cancel.

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 readOnlyHint=false and destructiveHint=false. The description adds the context of including the conversation array, but does not disclose side effects such as ticket creation or rate limits, so it provides some value but not rich 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, front-loaded with the tool's purpose, and contains no unnecessary words 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?

With 3 parameters and no output schema, the description is adequate but not complete. It covers the tool's purpose and gives a key hint about the conversation parameter, but lacks detail on message and context parameters.

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 compensate fully. It adds meaning to the 'conversation' parameter by calling for recent messages, but the required 'message' and 'context' parameters remain unexplained.

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 reports bugs, missing features, or feedback, with a specific verb and resource. It naturally distinguishes itself from sibling tools like connect or marketplace.

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 say when to use this tool vs alternatives, but the purpose is clear. It instructs including the conversation array for reproduction, which is a usage hint, though no exclusions or alternative mentions are made.

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 this operation as read-only (readOnlyHint) and idempotent (idempotentHint), and the description adds the specific detail that it displays platform and adapter versions. This additional context clarifies the exact output scope beyond the generic safety hints, and there is no contradiction between descriptions and 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, tightly written sentence that front-loads the action and immediately identifies the resource being reported. Every word adds value, avoiding any filler or redundant phrasing.

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 that this is a simple, read-only, parameterless version-checking tool, the description fully covers what it does and why it might be invoked. The annotations cover the safety profile, and the description clarifies the exact data presented, making it complete for the tool's low complexity.

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 defined in the input schema, the description needs to convey no parameter-specific information. The tool's functionality is fully explained without referencing any inputs, so the description comfortably satisfies the baseline for a no-parameter 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 action verb 'Show' paired with the specific resource 'the current MCP platform and adapter versions,' clearly defining the tool's function. This distinct purpose sets it apart from sibling tools like authenticate or connect, which serve different operational needs. The description is unambiguous and directly aligns with the tool 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 description establishes a clear context for use—whenever an agent needs to know the current platform or adapter versions—with no ambiguity about the tool's applicability. However, it does not explicitly mention alternative tools (e.g., toolkit_info) or specify when not to use this tool, so the guidance is clear but lacks 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?

Beyond the annotations (read-only, idempotent, non-destructive), the description adds meaningful operational behavior: payment is required per query, no credentials are needed, and the data is public access. It also clarifies the client's responsibility under LGPD, which is useful context that annotations do not convey.

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 concise sentences. The first sentence front-loads the purpose, and the second adds operational and legal context. Every sentence earns its place without unnecessary verbosity.

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 6-parameter tool with no output schema, the description covers purpose, key inputs, access model, and legal responsibility. It indicates the result (título and local de votação) but does not explain the exact return structure or error cases, which are minor gaps for this type of query 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 0% description coverage, so the description must fully compensate. It mentions name, CPF, title, and birth date, covering 4 of 6 parameters, but omits required parameter NomeMae and optional 'completo'. The schema itself provides no descriptions, leaving these parameters unexplained.

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 queries voter registration and voting location from TSE using name, CPF, title, and birth date. This is a specific verb and resource, and it is distinct from the related sibling tools which are generic platform utilities.

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: it is hosted on the platform, requires no credentials, and is paid via prepaid credit. It does not explicitly mention when not to use it or name alternatives, but the sibling tools are unrelated, so the guidance 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context by enumerating exactly what state information is returned (MCPs, connections, accounts, catalog tools), which is not apparent from annotations alone.

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?

A single, compact sentence that front-loads the verb and key object. Every element contributes meaning, with no filler or repetition of the tool name or title.

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 parameterless tool with rich annotations and no output schema, the description fully specifies the return content (installed MCPs, connection status, accounts, catalog tool counts). It is complete for the tool's simplicity and provides sufficient context for agent 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 coverage is 100%, so there are no parameter semantics to clarify. Baseline of 4 is appropriate since nothing is missing; the description need not compensate for 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 uses a specific verb 'Returns' and clearly identifies the resource ('current toolkit state') with detailed contents: installed MCPs, connection status, accounts, and catalog tool counts. This unambiguously distinguishes it from siblings like 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 implies usage for checking toolkit status but does not explicitly state when to use it versus alternatives, nor any exclusions. Sibling tools like connect or marketplace clearly serve different purposes, but no direct comparison is made.

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