Bolsa Família

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

Beyond annotations (idempotent=True, destructive=False), the description adds behavioral nuance: it explains the permanence difference between header config (non-expiring) and session-only token, and that calling with no args returns a link for browser login. However, it does not disclose the exact response format for either call, leaving some ambiguity for the agent.

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 relatively compact but packed with necessary information. The opening 'MCP.AI for IDE agents' sets context, though it could be trimmed. Each sentence adds functional value, and the flow (no args -> link, token -> session) is clearly 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?

For a tool with one optional parameter and no output schema, the description covers the core workflow and two authentication paths. The main gap is lack of explicit return-value specification, but the phrase 'get the link' and the overall context make it reasonably complete for an agent to handle the interaction.

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 schema description coverage at 0%, the description fully compensates by explaining the 'token' parameter as a JWT to paste, and the meaning of omitting it (get a link). This gives the agent complete understanding of the only parameter's role.

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: authenticate for IDE agents by logging in via browser and obtaining an access token. It distinguishes between two auth modes (permanent config header vs session-only token), making the verb+resource specific. The sibling 'connect' likely differs, but the description sufficiently explains the scope.

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 usage instructions are provided: 'Best: add it to this server's config as a header...' for permanent access, 'Or paste it here for a session-only login,' and 'call with { token: ... }' vs 'with no args to get the link.' This clearly tells the agent when to use each invocation pattern, including a step-by-step flow ('after the user pastes').

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 meaningful behavioral context beyond the annotations: it clarifies that the data is public and not private/confidential, explains the payment model (prepaid credit per consultation), and notes the client's data controller responsibility under LGPD. It is consistent with the readOnlyHint, idempotentHint, and destructiveHint annotations, 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 concise and front-loaded with the primary purpose. Each sentence adds relevant information: purpose, access/payment model, and legal/privacy context. It is not overly verbose, though the third sentence could be considered slightly redundant in emphasizing public access.

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 six parameters, no output schema, and no parameter descriptions in the schema, the description is not complete enough for reliable invocation. It fails to clarify the distinction between reference and competence dates, the format of date strings, and the expected response. Key invocation details are missing.

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 no parameter descriptions (0% schema coverage), so the description must compensate. It only mentions 'NIS' and 'mês/ano de referência', but does not explain the difference between MesReferencia/AnoReferencia and MesCompetencia/AnoCompetencia, nor the meaning of the 'completo' boolean parameter. This is insufficient for an agent to correctly populate all required 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 begins with a clear, specific verb-resource pair: 'Verifica o recebimento do Bolsa Família por um beneficiário a partir do NIS e do mês/ano de referência.' It explicitly names the input (NIS and reference month/year) and the resource (Bolsa Família receipt), and it is clearly distinct from the provided sibling tools (authenticate, connect, marketplace, 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 provides clear contextual usage guidance: it states the tool is hosted on the platform, requires no credentials, is paid per consultation with prepaid credit, and accesses public data only. This gives clear context for when to use the tool, though it does not explicitly name alternatives or when-not-to-use 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?

Despite annotations already declaring readOnly and idempotent hints, the description adds meaningful behavioral details: it explains the exact return shape for two scenarios (all connected vs. missing credentials), including the 'authenticated' flag, 'pending' list, and 'connect_url'. This goes beyond the annotations and provides valuable runtime 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 only two sentences, tightly packed with useful information. It is front-loaded with the main purpose and expands on the behavior without any 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?

With no output schema, the description adequately covers what the agent can expect in the response, including the two key states and the URL fields. Combined with the rich annotations, the tool is fully specified for a simple status-check operation.

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 the schema coverage is 100% with no properties. The description adds no parameter info because none is needed. Baseline of 4 is appropriate 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 clearly states the tool returns connection status and URLs, which is a specific verb+resource. It also distinguishes it from sibling tools like 'authenticate' by focusing on status checking rather than 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 clearly implies when to use this tool (to check connection state), and contrasts with the need to authenticate when credentials are missing. It does not explicitly name alternatives, but the context is sufficient to infer when this 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 non-obvious behaviors beyond the annotations: invoke runs tools not installed in a one-off manner without bloating the tool list; returns connect or checkout links for missing auth/payment; and notes that writes require workspace owner/admin. These details are not present in annotations (readOnlyHint=false) and are crucial for correct invocation.

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 lengthy but information-dense, front-loading the core purpose and flow before covering edge cases and secondary features. Some redundancy and run-on sentences ('without adding the MCP to the toolkit and without bloating the tool list') reduce readability, but the length is justified by the tool's complexity and multi-action nature.

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 covers the major functional areas: search/describe/invoke, install/uninstall, subscribe/cancel, report_bug/request_mcp, and the prompt library, including permission and payment handling. Gaps remain for some enum actions like `resume` and parameter details such as `immediate` or `conversation`, and no output format is described (there is no output schema).

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 adds meaning by explaining the semantics of `action` values (search, describe, invoke, install, list_tools, prompt actions) and the data flow to `tool_id` and `arguments`. It also explains `prompt_slug` and {{variables}} for get_prompt. However, not all 23 parameters (e.g., `resume`, `immediate`, `conversation`, `tier_slug`) are individually explained, leaving some 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 explicitly states 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly defines the tool's role as both a catalog and an execution interface, and outlines the core flow (search → describe → invoke). This distinguishes it from sibling tools like authenticate/connect by positioning it as the central discovery and invocation hub.

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 concrete usage guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also mentions alternatives like 'request_mcp asks us to build a NEW MCP when nothing fits' and 'list_tools lists what is callable right now', giving agents clear decision points for when to use this tool vs. other actions or 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?

The annotations already indicate idempotent and non-destructive, and the description further instructs to include the conversation array for reproduction, which is a useful behavioral detail beyond the annotations. It doesn't disclose the response format or side effects, but given the simple nature and annotation coverage, this is adequate.

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?

One concise sentence, front-loaded with purpose and a clear instruction. 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 description adequately covers the core purpose and one parameter, but it omits the 'context' parameter details and any post-report behavior. For a simple tool with no output schema, it is adequate but not 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. It explains the 'conversation' parameter's purpose but doesn't mention 'message' or 'context' parameters, and it ambiguously calls 'conversation' an array while the schema defines it as a string. This could mislead an agent.

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 ('Report') and the objects ('bug, missing feature, or send feedback'), which aligns with the tool name and distinguishes it from sibling tools dealing with authentication or marketplaces.

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 use for reporting issues or feedback, and the sibling tools are clearly unrelated, so an agent can infer when to use it. However, it doesn't explicitly list cases where this tool should not be used or 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 read-only, idempotent, and non-destructive behavior. The description adds context about what versions are shown (platform and adapter) and that they are 'current', implying live data, which is beyond annotation coverage.

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 with zero filler or redundancy. Every word 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 tool with no parameters, a rich annotation set, and no output schema, the description fully covers purpose and expected return. It is complete for this trivial 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?

There are zero parameters, so the description correctly contains no parameter-specific information. The baseline of 4 is appropriate because no compensation is needed.

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 identifies the exact resource ('current MCP platform and adapter versions'). This clearly distinguishes it from sibling tools like 'marketplace' 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?

No explicit when-to-use or when-not-to-use guidance is provided, but the tool's name and description imply usage when version information is needed. Absence of alternatives or exclusions leaves it at the implied-usage level.

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 destructiveHint=false. The description adds value by detailing what information is returned (installed MCPs, statuses, accounts, catalog tool counts), providing behavioral context beyond the annotations. No contradiction exists.

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, well-structured sentence that front-loads the action ('Returns') and efficiently lists the contained information. No filler or repetition of schema annotations.

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, a read-only annotation set, and no output schema, the description fully covers the tool's purpose and return contents. 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 tool has zero parameters, so the baseline is 4. The description does not need to explain parameter semantics because there are none to document.

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 and enumerates the specific contents (installed MCPs, connection status, accounts, catalog tool counts). This specific verb+resource+scope 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/connection status, and the read-only nature is evident. It does not explicitly list when-not-to-use or alternatives, but no sibling tool overlaps with this functionality, so clear context is provided without exclusions.

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