Certificado Anbima

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: no credentials needed, prepaid credit billing, data is public access, and LGPD responsibilities. It discloses operational and legal aspects 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?

The description is about three sentences long, front-loaded with the core purpose, then supplemented by payment, data-access, and legal context. Every sentence contributes operational value with no filler or repetition.

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 CPF-lookup tool, the description covers the main purpose, data nature, and legal framing. However, it omits what the 'completo' parameter does and does not describe the return payload, and there is no output schema to fall back on. It's adequate but has clear 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 0% description coverage, and the description only mentions CPF as the lookup key. The optional 'completo' boolean parameter is completely unexplained, and there is no format or default guidance. The description fails to compensate for the schema's lack of parameter documentation.

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: it queries Anbima professional certifications for a person using their CPF. The verb 'Consulta' and resource 'certificações profissionais Anbima' are specific, and the tool is well differentiated from unrelated siblings like authenticate, marketplace, and report_bug.

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 useful context about when to use the tool: it's a hosted, prepaid, no-credentials lookup of public data. It doesn't explicitly name alternatives or state when not to use it, but the sibling tools are clearly unrelated, so the intended use is obvious. A clear exclusion or alternative would push it to 5.

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?

Adds context beyond annotations by explaining the permanence of the config header versus session-only login, and the behavior of calling with no args to get a link. Annotations already declare idempotent and non-destructive, so no contradiction, but the description could further disclose side effects of pasting a token.

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 sentence with several clauses, but it's information-dense and front-loads the purpose. It's slightly verbose but not padded.

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 authentication flow, the two usage modes, and the token parameter. It's sufficiently complete, though it doesn't mention the expected return value in detail.

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 only lists a token string, but the description thoroughly explains it as an optional JWT for session login and clarifies that omitting it yields a login link. This fully compensates for the 0% schema coverage.

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 tool handles authentication for IDE agents with specific actions: log in, copy token, and use it. It distinguishes itself from sibling tools by being the dedicated authentication endpoint.

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 clear guidance on when to use which mode: permanent config header vs session-only token paste. However, it doesn't explicitly compare with sibling tools like 'connect', missing an opportunity to rule out 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 declare readOnlyHint=true and idempotentHint=true, and the description adds concrete behavioral detail: it specifies the exact response when all providers are connected (authenticated:true, empty pending[]) and when credentials are missing (connect_url and per-install URLs). This goes beyond the annotation metadata.

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 concise sentences, front-loaded with the core purpose and followed by a conditional explanation. Every sentence adds value and there is 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?

The description covers the main states (all connected vs. credentials missing) and explains return fields. However, it does not explicitly address partial connection states, though the presence of 'pending[]' implies non-empty lists in that case. Overall, it is sufficiently complete for a simple status-check tool with 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?

The tool has zero parameters and an empty input schema, so the baseline is 4. The description correctly omits any parameter details since none exist, and no additional semantic explanation 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 clearly states the tool 'Returns connection status and URLs' with specific detail about response fields (authenticated, pending[], connect_url). This distinguishes it from sibling tools like 'authenticate' by focusing on status retrieval rather than action-taking.

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 that this is a read-only status check, implicitly guiding use for verifying connection state. However, it does not explicitly state when to use it over alternatives or mention exclusions, though the conditional behavior makes the intended usage obvious.

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 sparse annotations (readOnlyHint=false, openWorldHint=true), the description reveals key behavioral traits: invoke works even when the MCP is not installed, returns connect/checkout links for auth/payment, writes require workspace owner/admin, and it explains the hidden one-off install behind invoke. This is rich, non-obvious behavioral disclosure.

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 long but organized into two coherent sections (marketplace and prompt library). It front-loads the core purpose and flows, and every sentence adds meaningful operational detail. While not terse, the length is justified by the tool's multi-action 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?

For a tool with 14 actions, 23 parameters, and complex auth/payment behavior, the description is remarkably complete. It covers the full lifecycle: discovery, one-off invocation, permanent installation, billing, bug reporting, MCP requests, and the prompt library, plus permissions. No output schema exists, so the description carries the completeness burden and meets 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?

Schema description coverage is 0%, so the description must compensate. It does explain the core parameters (action, mcp_id, tool_id, arguments) via the search/describe/invoke flow, but many parameters (resume, immediate, tier_slug, prompt_targets, prompt_category, conversation, etc.) remain undocumented. The description adds substantial context, but not full parameter-level semantics for all 23 params.

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 is the official mcp.ai marketplace, serving as both a catalog and execution layer for MCPs. It explicitly enumerates the core actions (search, describe, invoke, install, etc.) and the prompt library, distinguishing it from the unrelated sibling tools like authenticate or 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 provides explicit decision guidance: 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also gives a concrete workflow (search → describe → invoke), covers capability requests, and explains when to use report_bug vs request_mcp. This is exemplary usage 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, destructiveHint=false, and idempotentHint=true. The description adds the requirement to include the conversation array for reproduction, which is helpful 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?

Two sentences, front-loaded with the core purpose and followed by actionable guidance. Every word earns its place with no unnecessary 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?

For a simple feedback tool, the description covers the essential aspects: what to report and how to include reproduction information. Annotations provide the safety profile, and no output schema is needed. It is complete enough for an agent to wield 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?

Schema description coverage is 0%, so the description must compensate for parameter meaning. It clarifies the 'conversation' parameter as recent messages for reproduction, and implies the 'message' parameter holds the bug report content, but it never explains the 'context' parameter, leaving a significant gap.

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 'report' and clearly identifies the scope: bug, missing feature, or feedback. Sibling tools are unrelated (authenticate, marketplace, etc.), so this tool is unambiguous in purpose.

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 instructs to include the conversation array with recent messages for reproduction, which provides clear context on how to use the tool. It does not explicitly mention when not to use it or name alternatives, but the distinct purpose and unrelated siblings make exclusion unnecessary.

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 idempotentHint=true, establishing the safety profile. The description adds that it shows both platform and adapter versions, which is useful but does not go beyond that to describe return format or error behavior. This is adequate given 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 a single, complete sentence with no unnecessary words. It is front-loaded and immediately conveys the tool's function.

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 trivial complexity and the annotations already covering safety, the description fully covers what is needed. No output schema is present, but the behavior is simple enough that a return format explanation is not required.

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, making schema coverage trivially 100%. The description has no need to add parameter information, and the baseline of 4 for zero-parameter tools is appropriate.

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 identifies the resource as 'current MCP platform and adapter versions', making it clear what the tool does. This differentiates it from sibling tools like authenticate or report_bug, which have unrelated 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 tool's purpose as a version check is self-evident, and there is no competing tool among the siblings for this function. It provides clear context but does not explicitly state when to use it or mention exclusions, which are unnecessary given the simplicity.

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, so the safety profile is established. The description adds useful context by specifying exactly what the state contains, which goes beyond the bare annotation. 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 concise sentence that front-loads the purpose and lists the returned information. Every word contributes 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?

For a simple read-only tool with no parameters and no output schema, the description fully captures what the tool returns. It enumerates all key aspects of the toolkit state, making it self-sufficient for an agent to decide whether 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 reflects this with an empty properties object. The rubric baseline for 0 params is 4, and the description correctly omits any 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's function with a specific verb ('Returns') and resource ('current toolkit state'), and enumerates the specific data returned (installed MCPs, connection status, accounts, catalog tool counts). This distinguishes it from siblings like show_version or marketplace, which have different scopes.

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 (e.g., to inspect toolkit state) but does not explicitly state when to use this tool over alternatives or mention exclusions. Sibling tools like show_version could overlap, but no guidance is provided for choosing between them.

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