Benefício de Prestação Continuada (BPC)

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

Annotations already indicate idempotent and non-destructive side effects. The description adds useful context about the two modes (session vs permanent config), how tokens are used, and that calling with no args returns a login link. This enriches beyond annotation signals without contradicting 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 a single run-on sentence but front-loads the core purpose and packs essential guidance (browser login, token, two alternatives). It is somewhat dense but every clause adds value, only slightly compromising readability.

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 there is no output schema, the description mentions the return behavior (getting a link with no args) but does not detail success/failure responses for token submission. It is sufficiently complete for a simple auth tool, with annotations covering side-effect 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?

With 0% schema coverage, the description compensates by explaining the 'token' parameter as a JWT pasted from the browser, and clarifies it is optional (no args gets the link). It does not over-specify formatting but provides enough meaning for correct invocation.

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 an authentication mechanism for MCP.AI within IDE agents, with a specific flow (browser login, token copy/paste). It distinguishes itself from siblings like 'connect' by focusing on login/token exchange, making its 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 explicitly explains when to use the tool (for login) and provides two distinct invocation patterns: passing a token for session-only login, or calling with no args to obtain a login link. It also recommends the preferred permanent configuration method, giving clear context for both 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 the safety profile is known. The description adds valuable behavioral context: it mentions the pay-per-query model, that data access is public (not private/sensitive), and that the client is the data controller under LGPD. This goes beyond the 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 four sentences, each adding relevant information: purpose, access model, data publicness, and LGPD responsibility. It is front-loaded with the main function and avoids redundancy, making it appropriately sized and well structured.

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 has no output schema, so the description should explain what the tool returns or what 'completo' does. It does not describe the response format, error behavior, or the effect of the optional parameter. This leaves significant gaps for an agent to invoke the tool and interpret results 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 description coverage is 0%, so the description must compensate. It explains that CPF and NIS are the identifying inputs, but it does not clarify the 'completo' boolean parameter or any formatting requirements (e.g., punctuation). This leaves the optional parameter semantically 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's function with a specific verb ('Verifica') and resource (recebimento do BPC), and specifies the key inputs (CPF and NIS). It distinguishes itself from sibling tools, which are generic (authenticate, connect, etc.) and unrelated to BPC consultation.

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: it checks BPC receipt status for a beneficiary, requires prepaid credits, and has no credentials. It does not explicitly name alternatives or exclusions, but the purpose is self-evident and sibling tools are not relevant choices.

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 safety with readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable context: it reveals the return shape (authenticated:true with empty pending[], or connect_url for toolkit and per-install URLs) under different conditions, going beyond what annotations 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 concise: two sentences that lead with the core purpose and then elaborate on conditional outputs. Every sentence adds value, with no redundancy or filler.

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 states (all connected vs. missing credentials) and return values, which is sufficient for a zero-parameter read-only tool. However, it omits the partial-connection case (some providers connected), leaving some ambiguity. Given the tool's simplicity and supportive annotations, it's 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 tool has zero parameters, so schema coverage is trivially 100%. The description appropriately focuses on output behavior rather than parameter details since none exist.

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 specific conditional outputs. While it doesn't explicitly name sibling alternatives, it's evident this is a status-check tool distinct from '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?

Usage is implied but not explicitly stated. The description explains what happens in different scenarios (all connected vs. missing credentials) but doesn't say when to use this tool over siblings or when not to use 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?

Beyond the annotations, the description richly discloses behavioral traits: writes require workspace owner/admin, invoke runs tools one-off even when not installed, missing credentials return a connect link, empty wallet returns a checkout link, and search/describe flag installation status. It also explains that invoke does not bloat the toolkit. There is 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 dense and information-rich, but it is a single large paragraph without bullets or section breaks. Every sentence earns its place; it covers core flow, install vs. invoke behavior, permissions, billing, and the prompt library. Some structure would improve readability, but the content remains efficient for the tool's complexity.

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 23 parameters, no output schema, and a broad multi-action surface, the description is quite complete: it explains the discover→describe→invoke pipeline, the install-vs-invoke distinction, the auth/payment handling, the prompt library, permission requirements, and the purpose of each action. It does not specify the exact return format or provide per-action response details, but for such a large tool the coverage is strong and leaves few major 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?

Schema description coverage is 0%, so the description must compensate. It explains the core action parameters ('search', 'describe', 'invoke', etc.) and links prompt-library parameters to their purpose (e.g., 'get_prompt' with '{{variables}}' filled). It does not explain every one of the 23 parameters, but given the high parameter count and the description's focus on the central workflow, it adds substantial meaning 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 identifies the tool as the official mcp.ai marketplace and outlines its dual role: discovering and running MCPs plus managing the prompt library. It uses concrete actions like 'search', 'describe', 'invoke', and 'install', which distinguish its scope from siblings like 'authenticate' and 'toolkit_info'. However, the purpose is broad and multi-faceted rather than a single verb+resource statement, so it loses one point.

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 guidance on when to use each action: prefer 'invoke' for one-off use, use 'install' only for permanent additions, use 'list_tools' for currently callable tools, and use 'request_mcp' when nothing fits. It also clarifies when to use related prompt-library actions. This is exemplary usage guidance with clear alternatives.

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, so the description does not contradict them. It adds context about including the conversation array for reproduction, but it does not disclose other traits like authentication requirements or expected response. This is baseline with some added value.

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 front-loads the purpose and provides a key usage hint. No filler or 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?

The tool is simple and has annotations, but with 0% schema description coverage, the description needs to explain all parameters. It only covers 'conversation' and leaves 'context' unexplained. It also omits details about auth requirements or outcomes, though these are partly mitigated by annotations.

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 (array for reproduction) but does not explain 'context' or 'message' beyond their names. This partial compensation warrants a middle score.

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: 'Report a bug, missing feature, or send feedback.' This is a specific verb and resource, and it is distinct from all sibling tools (authenticate, connect, etc.), 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?

It explicitly lists the use cases (bug, missing feature, feedback) and instructs to include the conversation array for reproduction. However, it does not explicitly state when not to use the tool or name alternatives, though no close alternatives exist among the siblings.

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, which fully cover the safety profile. The description adds little beyond restating that it shows versions, but it is consistent with the annotations and does not contradict them. Since the bar is lower with annotations present, a neutral score is appropriate.

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 with no filler or redundant phrasing. It is front-loaded and every word contributes meaning, making it highly efficient.

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: no parameters, no output schema, and low complexity. The description clearly states what will be shown (platform and adapter versions), which fully covers the expected behavior for a version-query tool. There is no missing context that would prevent correct usage.

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 any parameter semantics, and the schema is fully covers the empty parameter list. No further elaboration required.

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 'show' and clearly identifies the resource: 'current MCP platform and adapter versions'. It is unambiguous and distinguishes itself from sibling tools like 'authenticate' or 'connect', none of which provide version 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 implies usage: call this tool when you need to know the current versions of the platform and adapter. However, it does not explicitly state when to use it versus alternatives, nor does it provide exclusions or preconditions. Given the tool's simplicity and its distinct purpose, implied usage is acceptable.

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, establishing the safety profile. The description adds value by specifying exactly what state information is returned (installed MCPs, connection status, connected accounts, and tool counts), which is behaviorally relevant beyond the bare hints.

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, efficiently structured sentence that front-loads the action and lists key details. Every word contributes to understanding the tool's purpose and output.

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 zero-parameter, read-only status tool with no output schema, the description adequately covers what is returned. It enumerates all major components of the toolkit state, providing sufficient context for an agent to decide to invoke it.

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% (empty properties). Per the baseline rule for 0-parameter tools, a score of 4 is appropriate since there are no parameters requiring 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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state') with an enumeration of included details: installed MCPs, connection status, accounts, and tool counts. This makes the tool's purpose distinct from siblings like show_version.

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 this is the tool to call when you need the toolkit's state, but it does not explicitly state when to use it over alternatives like show_version. No exclusions or alternative references are provided.

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