Benefícios Sociais PF

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

The description explains behavior beyond annotations: calling with no args returns a login link, calling with a token establishes a session-only login, and there is an option for a permanent non-expiring connection via configuration. It does not detail token validation or error cases, but the core behavior is transparent.

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 three sentences that each provide actionable information. Slightly verbose with the 'best way' recommendation, but no redundant 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?

The description covers the main usage scenarios and expected inputs/outputs (link or session establishment). It does not specify the return value format or post-auth behavior, but given the simple schema and idempotent annotation, the context is largely 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 input schema has no parameter descriptions (0% coverage), but the description fully compensates by explaining that 'token' is a JWT to paste after user login, and that omitting it yields a login link. This adds clear meaning to the optional parameter.

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 this is an authentication tool for IDE agents, explaining the login flow and token exchange. It distinguishes its purpose from sibling tools by focusing on authentication, though it does not explicitly compare itself to '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?

Provides concrete usage guidance: when to call with a token, when to call with no args, and the preferred permanent configuration via the Authorization header. It does not explicitly mention when not to use this tool versus siblings, but the context is sufficiently 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 readOnly/idempotent behavior, and the description adds crucial context: public access data (not private), no credentials required, prepaid credit model, and LGPD controller responsibility. This goes beyond the annotations and clarifies legal/safety aspects.

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 three sentences and front-loads the main purpose. It includes relevant context (pricing, public data, LGPD), though the legal sentence adds length; still appropriately sized.

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 two-parameter tool with no output schema, the description covers purpose, data source, access type, and legal responsibility. But it omits the 'completo' parameter behavior and any return format, so it's not fully 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?

Schema coverage is 0%, so the description must compensate. It mentions CPF as the query key but fails to explain the 'completo' boolean parameter or the output format, leaving half the input surface undocumented.

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 'Consolida' and identifies the resource 'benefícios sociais recebidos por uma pessoa física a partir do CPF', clearly distinguishing it from the sibling meta-tools. It also states it consults public access data, making the purpose 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?

It provides clear context: hosted by the platform, no credentials, pay-per-query with prepaid credit, and LGPD responsibility. However, it doesn't explicitly state when not to use it or mention alternative tools, though the sibling tools are unrelated.

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, idempotent, and non-destructive. The description adds meaningful conditional behavior beyond these annotations, explaining exactly what happens when providers are connected (authenticated:true, empty pending[]) and when credentials are missing (connect_url for toolkit and per-install URLs). This is valuable, non-redundant 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 two sentences, front-loaded with the main purpose, and then adds necessary conditional details. Every sentence earns its place with no unnecessary words or repetition of annotation data.

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 parameters and no output schema, the description covers all relevant behavior (both connected and missing-credential states) and is fully complete in context. The enriched annotations and clear description make additional details unnecessary.

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 score of 4 applies. The description does not need to add parameter semantics, and the schema coverage is trivially 100% since there are no properties.

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 specific verb 'Returns' and clearly identifies the resource ('connection status and URLs'). It also distinguishes from sibling tools like 'authenticate' by explaining that this tool checks status rather than performing authentication. The conditional outcomes add clarity about what the tool does.

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 usage context: checking connection status and determining if authentication is needed. However, it does not explicitly mention alternatives or when not to use this tool. The sibling names provide obvious context, but the description itself does not reference them.

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 annotations (readOnlyHint=false, openWorldHint=true), the description discloses key behaviors: invoke works one-off without installation, credential needs return a connect link, paid-and-wallet-empty returns a checkout/top-up link, and writes require workspace owner/admin. It also explains the search/describe installed_in_toolkit vs installed_in_workspace flags. No contradictions with 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 dense paragraph but is well-structured: it starts with the core flow, uses 'KEY:' to highlight the most important behavior, then covers permissions and the prompt library. Every sentence adds value, though at ~200 words it is long; the complexity of the tool justifies the length.

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 23 params and many actions, the description covers the major workflows end-to-end: discovery, profiling, one-off execution, permanent install, billing/auth behavior, permissions, and prompt library. It omits specifics like pagination (limit) and return value formats, but given no output schema, it provides enough context for an agent to handle the primary use cases 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?

Schema coverage is 0%, so the description carries the burden. It explains the 'action' parameter values contextually, mentions mcp_id/tool_id/arguments implicitly in the flow, and describes prompt_vars as {{variables}}. However, many parameters (limit, query, message, immediate, tier_slug, cancel_reason, etc.) remain unexplained, leaving gaps for an agent trying to construct precise calls.

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 verb+resource statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It then enumerates the core flow (search → describe → invoke) and the prompt library, distinguishing this from sibling tools by covering cataloging, execution, and prompt management in one place.

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 explicit when-to-use guidance: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and 'list_tools lists what is callable right now.' It also explains when to use request_mcp ('when nothing fits') and gives the full action flow, leaving little ambiguity about selecting this tool.

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 idempotentHint=true and destructiveHint=false, and the description adds 'for reproduction' as context for the conversation parameter. However, it doesn't describe side effects like ticket creation, sending the report, or any rate limits. No contradiction with 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, front-loaded sentence with no redundancy: it states the purpose and then a concrete reproduction instruction. 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?

The tool is simple and the description covers the core purpose and an important reproduction guideline. However, it omits meaning for 'message' and 'context', and with no output schema or return-value description, the agent may be uncertain about expected behavior.

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 must compensate, but it only explains the conversation parameter, and even that lacks format details (schema says string, while description says 'array'). The required 'message' parameter and optional 'context' field are left undifferentiated.

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 'Report' with clear objects ('bug, missing feature, or send feedback'), making the tool's purpose immediately obvious. It also differentiates from sibling tools like marketplace and show_version, which serve unrelated functions.

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 states when to use the tool: to report a bug, missing feature, or feedback. It also gives a specific usage instruction (include conversation array for reproduction), though it does not explicitly mention alternatives or 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds no additional behavioral context beyond restating what the tool shows, which is acceptable for a trivial read-only tool but contributes nothing extra.

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 purpose without any wasted words. It is front-loaded and appropriately sized for a tool this simple.

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, clear annotations, no output schema needed), the description is complete. It fully explains what the tool shows, and the sibling list shows no overlapping functionality.

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 per the rubric the baseline is 4. The description adds semantic value by specifying what the tool returns (platform and adapter versions), which complements the empty 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 function with a specific verb 'Show' and a clear resource: 'current MCP platform and adapter versions'. It is easily distinguished from sibling tools like authenticate or connect, which serve entirely 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 its usage—run to see version info—but provides no explicit guidance on when to use it versus alternatives. While no alternatives exist among the sibling tools, the lack of explicit 'when to use' language lowers the score.

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, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds valuable context about the specific content of the returned state, enhancing transparency beyond annotations. 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 a single, well-structured sentence that front-loads the main purpose ('Returns the current toolkit state') and enumerates key details. No redundant or filler 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 simple zero-parameter tool with no output schema, the description adequately summarizes the return value at a high level. It could include more detail about output format or possible statuses, but the essential context is present, and annotations cover safety.

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 is empty, so there is no parameter semantic burden. The baseline for 0 parameters is 4, and the description appropriately focuses on output rather than inputs.

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 with a specific verb ('Returns') and resource ('current toolkit state'), then enumerates the exact data provided (installed MCPs, connection status, connected accounts, catalog tool counts). This distinguishes 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 implies usage: when you need an overview of the toolkit's state, this is the tool. It provides clear context without explicit exclusion or alternative instructions, which is acceptable for a simple read-only info tool.

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