Portal da Transparência: Busca

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

Annotations already indicate idempotentHint=true and readOnlyHint=false. The description adds meaningful context by explaining the consequence of each invocation path: permanent non-expiring connection vs. session-only, and that calling without args yields a link. It does not repeat or contradict the annotations, and it discloses the side-effect of token creation.

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, information-dense paragraph that front-loads the purpose and then explains usage. Every clause adds value without unnecessary fluff. It could be considered slightly long, but it avoids ambiguity and remains within a compact structure.

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 only one optional string parameter and no output schema, the description covers the essential aspects: what it does, two ways to auth, and parameter semantics. It doesn't cover edge cases like error handling or expiration, but those are not critical for an agent to invoke it correctly in most situations.

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 provides no description for the token parameter (0% coverage). The description compensates fully by specifying the token format ('<jwt>') and explaining both the presence and absence of the argument: call with {token} to pass the pasted JWT, or with no args to receive the login link. This is a model of parameter explanation.

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 states the tool's purpose with a specific verb and resource: 'log in in the browser, copy the access token.' It clearly identifies this as the authentication tool for MCP.AI IDE agents, distinguishing it from siblings like 'connect' and 'marketplace' by focusing on login.

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 explicit instructions for two primary workflows: using the server config for a permanent connection and pasting a token for session-only login. It also explains behavior with no arguments. While it doesn't contrast with sibling tools, it clearly explains the circumstances under which to use this tool and its invocation modes.

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, destructiveHint=false. The description adds that it returns authenticated:true when all providers are connected and empty pending[], and returns connect_url when credentials are missing. This provides additional behavioral context beyond what annotations offer, but does not 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?

The description is two sentences, front-loaded with the main purpose, and uses zero filler. Every sentence adds information about behavior and output conditions.

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 zero parameters and a clear output description, the description is complete. It explains the two response states (all connected vs. missing credentials) without being verbose. The absence of an output schema is compensated by the description detailing what the response contains.

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% (vacuously). The description explains what the response contains (connection status, URLs, pending array, connect_url). Since there are no parameters to describe, the description provides useful context about the output, which is valuable beyond the 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 what the tool does: it returns connection status and URLs. It also distinguishes from siblings by noting it checks provider connections, while siblings like 'authenticate' handle authentication and 'marketplace' deals with marketplace 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 when to use it: to check connection status. It does not explicitly mention alternatives, but the sibling names and the clear 'returns connection status' make the context clear. The description could mention when to use this vs. 'authenticate' but the purpose is sufficiently distinct.

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 discloses substantial behavioral context beyond the annotations: invoke works even when the MCP is not installed, returns connect links for missing credentials, returns checkout links for unpaid usage, and writes require workspace owner/admin. It also explains the side effects of install versus invoke, which is exactly the kind of context annotations alone do not provide.

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 information-dense and front-loaded with the core purpose and flow, but it is a single long paragraph covering many actions, billing, auth, permissions, and the prompt library. It would benefit from structured sections or bullets; as written, it is comprehensive but not concise.

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 complexity—23 parameters, 14 actions, no output schema—the description covers the major flows, permissions, auth/billing behavior, and the prompt library. It is not fully complete because per-action return formats and several parameter semantics are missing, but it provides enough context for an agent to navigate the tool effectively.

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 full burden for parameter meaning. It explains the action enum, mcp_id, tool_id, arguments, and several prompt_* parameters through the described flows. However, many of the 23 parameters—such as limit, query, immediate, tier_slug, conversation, request_name, cancel_reason, and report_context—are not explicitly explained, leaving 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 identifies the tool as the mcp.ai marketplace and the mechanism for discovering, describing, and invoking MCPs, with a concrete core flow: search → describe → invoke. It is multi-purpose and does not explicitly contrast itself with sibling tools, but the resource and actions are specific enough to be distinguishable.

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 actionable guidance: prefer invoke for one-off use, use install only for permanent toolkit additions, use list_tools to see what is callable now, and use request_mcp when nothing fits. It does not explicitly compare against sibling tools like authenticate or connect, but within its own action space the when-to-use guidance is strong.

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 useful behavioral context beyond the annotations: it discloses the pay-per-query model with prepaid credits, clarifies that the data is official and non-confidential (não é dado sigiloso), and highlights LGPD compliance responsibilities. This complements the readOnly and idempotent hints with operational and legal insights.

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, fairly compact paragraph that covers purpose, cost, data type, and legal responsibility without excessive verbosity. Each clause adds value, though the structure could be tighter (e.g., separating legal notes).

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 is simple (one parameter) and annotations cover safety, but the description omits expected output or response format, and does not clarify query limitations or result handling. For a paid, external API, such details might be crucial, but the absence of an output schema and minimal description leave gaps.

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 only one parameter 'query' with no description, and the tool description provides no guidance on its format, allowed values, or examples. With 0% schema description coverage, the description should compensate, but it does not, leaving the query parameter ambiguous.

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 search/consultation on the official Transparency Portal ('Busca, consulta em fonte oficial'), which is specific and actionable. It differentiates itself from the sibling tools (authenticate, connect, marketplace, etc.) by focusing on querying official data.

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 any guidance on when to use this tool versus alternatives. It mentions operational aspects like prepaid credits and lack of platform credentials, but offers no criteria for selection or exclusions (e.g., 'use for X, not for Y'). This leaves the agent without decision support.

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 provide readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds behavioral context by instructing to include conversation data for reproduction, which is useful for understanding what information is needed. It does not contradict annotations and adds value beyond them by clarifying the intended use of the conversation parameter.

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, comprising a single sentence that states the purpose and a key usage hint. It is front-loaded with the main purpose and avoids unnecessary detail.

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 feedback/reporting tool with an output schema absent and annotations partially informative, the description is adequate but minimal. It lacks details on expected behavior, such as whether the report is stored, how it is handled, or what happens after submission. The absence of an output schema means the description should provide more context, but it doesn't.

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%, meaning the description provides no information about the parameters. The description only mentions 'Include the conversation array with recent messages' but does not explain the 'message' or 'context' parameters. This is insufficient given the low coverage, and the description fails to add meaning beyond the schema's basic property names.

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 states the tool's purpose: 'Report a bug, missing feature, or send feedback.' It clearly identifies the verb (report/send) and the resources (bug, missing feature, feedback). It distinguishes from siblings like 'connect' or 'authenticate' by focusing on issue reporting, though it doesn't explicitly contrast with them.

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 contrast with alternative tools. It gives a brief instruction to include the conversation array for reproduction, but lacks comprehensive context about usage scenarios.

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, so safety profile is known. The description adds the specific output (versions), which is beyond the annotationstas. 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?

A single, concise sentence that exactly states the tool's functionality. No extraneous words, and the key information is 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 tool's simplicity (no parameters, no output schema) and sufficient annotations, the description fully covers the necessary context. It states what versions are shown and the scope ('current'), which is adequate for an agent to invoke 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?

Tool has zero parametersholistically, and schema coverage is 100%. The description does not need to elaborate on parameters, and the baseline for no-parameter tools 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 clearly states the action ('Show') and the specific object ('current MCP platform and adapter versions'). It is distinct from sibling tools like authenticate or connect, which serve different purposes.

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 the tool (to retrieve version info) and implicitly distinguishes it from sibling tools. No explicit exclusions or alternatives are mentioned, but the purpose is self-evident and unambiguous.

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 is consistent with annotations (readOnlyHint: true, idempotentHint: true, destructiveHint: false) and adds valuable context about what state is returned (MCPs, connection statuses, accounts, catalog counts). The description enriches the annotation by describing exactly what aspects of state are exposed, fulfilling the burden beyond the annotation-level data.

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, front-loaded sentence that efficiently packages all necessary information without any fluff or repetition. Every element (MCPs, status, accounts, catalog counts) earns its place.

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, parameterless state-query tool with strong annotations, the description is thorough. It covers what is returned and aligns with the tool's simplicity. It could mention whether data is live or cached, but this is a marginal gap given 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?

With zero parameters and 100% schema coverage (empty schema), the description bears no burden to clarify parameters. The baseline of 4 applies since there is nothing else to add 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 a specific verb ('Returns') and clearly enumerates what state is retrieved: installed MCPs, their connection status, associated accounts, and catalog tool counts. This is comprehensive and distinguishes it from siblings like `show_version` or `connect`, which serve different purposes.

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 a diagnostic use case (checking toolkit state) but provides no explicit guidance on when to use this tool versus alternatives like `show_version` or `connect`. There are no stated exclusions or when-not-to-use scenarios, though the purpose is self-evident enough for basic usage.

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