Situação Eleitoral (TSE)

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

Annotations declare idempotent and non-destructive hints, but the description adds valuable context about session vs. permanent login, the token format, and the behavior of calling with no arguments (returning a link). It does not contradict 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 informative but somewhat rambling with parentheses and semicolons. However, it is front-loaded with the key purpose and each sentence delivers useful guidance, so it is still concise for the amount of information provided.

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 (one optional parameter, no output schema), the description covers all necessary aspects: the configuration alternative, session token usage, and no-args behavior. It is 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?

The schema has only an optional 'token' property with no description (0% schema coverage). The description compensates fully by explaining that the token is a JWT to be passed for session-only login, and that omitting it triggers a link retrieval. This is comprehensive.

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 authentication workflow: log in through the browser, copy the access token, and either add it to the server config or pass it as a parameter. It clearly differentiates this from sibling tools by focusing on the authenticate action and its two modes.

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 for when to use this tool, including the 'Best' option for permanent config-based authentication and the alternative session-only token passing. It also notes the no-args behavior to get a link, but it does not explicitly compare to the sibling 'connect' tool or state 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?

Annotations already indicate readOnly, idempotent, and non-destructive. The description adds meaningful context by specifying exact return fields ('authenticated:true', 'empty pending[]', 'connect_url', per-install URLs) for each state. This enriches the behavioral model without contradicting 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?

Two concise sentences with front-loaded purpose. The conditional logic is compact and each clause delivers useful information without fluff.

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 read-only status tool with no output schema, the description covers all relevant behaviors: both states (connected/missing credentials) and the URLs returned. It is complete for an agent to decide when and what to expect.

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%. Baseline for 0 params is 4; the description does not need to compensate and doesn't mislead.

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' with a specific verb and resource. It also describes conditional outcomes (authenticated:true vs connect_url), making its purpose unmistakable and distinct from sibling tools like authenticate.

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: when needing connection status. It provides clear scenarios for both connected and missing credentials states. However, it does not explicitly distinguish from alternative tools like authenticate or say when not to use.

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, the description reveals key behaviors: invoke works even when the MCP is not installed and runs a one-off tool without adding it to the toolkit; missing credentials return a connect link; empty wallet returns a top-up link and instructs to retry; writes require workspace owner/admin. These are important behaviors not encoded in annotations, making the agent prepared for edge cases.

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?

Although long, the description is dense and structured: it flows from catalog definition to core flow to key behavior to install-vs-invoke to permissions to the prompt library. Every sentence adds new information; there is no fluff or repetition. It is organized as a single coherent guide.

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 complexity (23 parameters, no output schema, no schema description coverage), the description covers all major operational scenarios: discovery, detail retrieval, invocation, installation, uninstallation, billing, permissions, and prompt library usage. It even explains edge cases (missing credentials, empty wallet) and retry logic. This is a complete operational manual for the agent.

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%, but the description compensates by explaining the meaning of the main action parameter and the workflow: 'action=search discovers MCPs by intent → describe returns one MCP's full profile... so you pick the right tool_id → invoke RUNS that tool.' It also covers the prompt-related actions. However, many parameters (limit, immediate, tier_slug, cancel_reason, etc.) remain unexplained, leaving gaps for less central 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 opens with a clear statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then explains the core flow (search → describe → invoke) and distinguishes the marketplace's role from sibling tools like authenticate or toolkit_info. It is specific about the resource and the verbs involved.

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 explicitly contrasts invoke vs install: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also states when to use search/describe, when to use request_mcp, and clarifies that report_bug sends feedback. 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 already declare readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds no additional behavioral context (e.g., what happens after submission, rate limits, auth). It only adds usage detail about including the conversation, not about 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?

The description is only two sentences, front-loaded with the core purpose and a specific usage instruction. No redundant 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 bug reporting tool with no output schema, the description covers the main intent and one key parameter. It lacks explicit description of the context parameter and return behavior, but is not overly inadequate.

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 conversation parameter ('Include the conversation array with recent messages for reproduction') and implicitly defines message, but does not explain the context parameter. This partial compensation warrants a 3.

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 function: 'Report a bug, missing feature, or send feedback.' The verb 'Report' and resource (bug/feature/feedback) clearly distinguish it from sibling tools like show_version or authenticate.

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 for when to use this tool (reporting issues) and instructs to include the conversation array for reproduction. However, it does not explicitly mention alternatives or when-not-to-use conditions.

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 cover readOnlyHint, idempotentHint, and destructiveHint, so the description's burden is lower. It adds useful context about both platform and adapter versions, but says nothing about return format or any potential side effects. For a simple read-only operation, this is adequate but not rich.

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 of nine words, with zero filler. It states the action and resource clearly and efficiently.

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, read-only version query, the description fully captures the purpose and necessary context. The annotations provide safety information, and the lack of an output schema does not represent a significant gap for such a simple 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 description cannot add parameter-level meaning. With no parameters to document, the baseline of 4 applies since there is nothing to compensate for.

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 function: showing the current MCP platform and adapter versions. It uses the verb 'Show' and specifies the resource, distinguishing it from sibling tools like toolkit_info which likely provides broader toolkit information.

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 no explicit guidance on when to use this tool versus alternatives. It does not reference sibling tools like toolkit_info, nor does it mention any exclusions or context that would help an agent choose this tool over others.

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 readOnly, idempotent, non-destructive. The description adds value by clarifying no credentials are needed, payment is required, and that the data is public access, plus LGPD obligations. This enriches beyond the structured 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?

Three sentences front-load the core action, then add payment model and legal context. Each sentence contributes distinct information, with no filler. Slightly longer than necessary but well organized.

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 read-only query tool with strong annotations, the description covers purpose, inputs, access type, and legal responsibilities. It doesn't specify response format or parameter formats, but given the tool's simplicity and lack of output schema, it is reasonably 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?

The description lists the four required inputs matching the schema, but doesn't explain formats, the optional 'completo' parameter, or provide any details beyond the schema names. With 0% schema coverage, it partially compensates but leaves gaps.

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 consults electoral status at TSE using specific inputs (name, birth date, CPF, voter ID). It names the resource and source, making it distinct from the unrelated sibling tools.

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: hosted by the platform, no credentials required, pay-per-use with prepaid credit. It also notes the data is public access and LGPD compliance is the client's responsibility, giving conditions for appropriate use, though it doesn't mention explicit alternatives or when-not-to-use cases.

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 mark the tool as read-only, idempotent, and non-destructive. The description adds behavioral context by detailing exactly what the returned state contains (installed MCPs, connections, accounts, tool counts). No contradictions with annotations exist.

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 immediately states the verb ('Returns') and resource ('current toolkit state'), followed by a concise enumeration of the state's components. Every phrase earns its place with no 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 tool's simplicity (no parameters, no output schema), the description is fully complete: it tells the agent exactly what to expect from the response. The list of included elements (installed MCPs, status, accounts, catalog tool counts) adequately covers the tool's purpose.

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 full coverage (100%) by definition. The description adds meaning by clarifying what the returned state represents, which compensates for the lack of any 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 the tool returns the current toolkit state, enumerating specific components: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like authenticate or connect, which perform actions rather than report state.

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 for when to use this tool: whenever an overview of the toolkit's current state is needed, including installed MCPs and connection status. It does not explicitly mention exclusions or alternatives, but the purpose is sufficiently distinct from siblings that no further guidance is necessary.

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