Compliance de Apostas

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

Beyond the annotations (idempotent, non-destructive), the description discloses that the config-based approach creates a permanent, non-expiring connection while pasting a token is session-only. It also reveals the login flow (browser -> copy token), adding meaningful behavioral context 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 a single, information-dense paragraph. Every sentence adds value, but the structure is somewhat run-on and could be more scannable with bullets. Still, it is far from verbose and maintains focus.

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 one optional parameter and no output schema, the description covers the main workflows: getting the link, pasting a session token, and configuring a permanent header. It does not explain return values in detail, but this is acceptable for an auth tool where the main outcome is subsequent authenticated access.

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 full burden. It explicitly explains the 'token' parameter: call with { token: "<jwt>" } when the user pastes a token, or omit arguments to get the login link. This fully compensates for the schema's lack of description.

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: authenticating IDE agents (Cursor, etc.) by logging in and obtaining an access token. It distinguishes itself from unrelated siblings like 'connect' and 'marketplace' by specifying the exact resource (MCP.AI) and action (log in, copy token).

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 usage guidance: it explains the preferred permanent setup (add Authorization header to config) versus session-only login (paste token), and clarifies that calling with no args returns the login link. This gives the agent clear decision-making criteria.

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 (readOnly, idempotent, non-destructive), the description adds valuable context: it accesses only public data (not private/secret), outlines LGPD responsibilities for the customer, and mentions the payment model. This enriches the behavioral profile without contradicting 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 three sentences and each sentence carries relevant information (purpose, access modality, legal/privacy context). It is compact and front-loaded with the core function, though a bit longer than strictly necessary.

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?

Covers the essential context (purpose, payment, public data, LGPD) but omits any indication of what the query returns (e.g., result format, whether 'completo' changes output). With no output schema, such information would improve completeness, but the tool is simple enough that the basics suffice.

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%, and the description only mentions CPF as the lookup key. The optional 'completo' parameter is left completely unexplained, and there is no detail on its expected values or effect on the result. This is a notable 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 clearly states the tool's function: 'Verifica indicadores de compliance de uma pessoa para o setor de apostas a partir do CPF' (checks compliance indicators for a person for the betting sector from the CPF). It specifies the verb, resource, and input, and is distinct from unrelated sibling tools.

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 practical usage context: hosted by the platform, no credentials required, pay-per-query with prepaid credit, and that it consults public-access information. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to know when 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds specific behavioral detail about the response structure (authenticated, pending[], connect_url) in different states, which is useful beyond the annotation safety profile.

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 core purpose, and every word adds value. It efficiently conveys the two main outcome states without 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?

For a simple query tool with no output schema, the description explains the return values in the key scenarios. It could mention partial connection states or details about pending[] but is largely complete for an agent to understand what to expect.

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 schema provides no parameter semantics. Baseline for 0 params is 4; the description does not need to add parameter details, and none are 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 conditions (all providers connected vs credentials missing). This distinguishes it from sibling tools like authenticate, which is about performing authentication, not checking its status.

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 on when to expect different outcomes (e.g., when credentials are missing, returns connect_url), implying it should be used to check onboarding status and obtain URLs for completing authentication. It does not explicitly mention alternatives, but the conditions make usage context 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?

Goes well beyond annotations: describes one-off invoke behavior ('works even when the MCP is NOT installed ... without bloating the tool list'), permission requirements for writes ('require workspace owner/admin'), and response behaviors (connect link, checkout link). Annotations only say readOnlyHint false and openWorldHint true; the description adds substantial operational 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 lengthy but appropriately sized for a 14-action tool. It is front-loaded with the core purpose and flow, and every sentence adds operational detail. The structure (core flow, key behavior, action-specific notes, permissions, prompt library) is logical and wastes no space.

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 complex multi-action tool with no output schema and zero schema coverage, the description covers purpose, core flow, action semantics, permissions, special response links, and the prompt library. It is sufficient for an agent to select the correct action and parameters for most use cases, and it handles edge cases like missing credentials and empty wallet.

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 has 23 params with 0% description coverage, but the description compensates by explaining the high-level action parameter ('action=search...'), core flow parameters (tool_id, arguments for invoke), and prompt-related params (prompt_slug, prompt_vars, prompt_body). It doesn't individually explain all params like limit, immediate, tier_slug, but the action-oriented description gives meaning to the main parameter namespace.

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 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', clearly stating a specific purpose. It then details the core flow (search→describe→invoke) and differentiates actions like install vs invoke, making the tool's role distinct from siblings.

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?

Explicitly gives when-to-use guidance: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', 'list_tools lists what is callable right now'. Also explains special cases (credential link, checkout link) and which actions are for what, satisfying the when/when-not criteria.

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 provide readOnlyHint=false and destructiveHint=false, so the description's added value is the instruction to include the conversation array for reproduction. This gives useful context about what to provide, but it does not disclose potential side effects (e.g., data being sent, confirmation behavior) 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 a single, concise sentence that front-loads the purpose and immediately provides the key instruction about the conversation array. No unnecessary 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 tool is simple with no output schema, but the description still omits the 'context' parameter and does not mention what happens after reporting (e.g., confirmation, ticket creation). It is adequate but not fully complete for an agent to understand all aspects of the 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?

With schema description coverage at 0%, the description partially compensates by explaining 'conversation' (for reproduction) and implying 'message' (the content to report). However, the 'context' parameter remains unexplained, leaving a gap in full parameter understanding.

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 with a specific verb ('Report') and resource ('a bug, missing feature, or send feedback'). It distinguishes itself from sibling tools like show_version or authenticate, which serve entirely different 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 implies usage (when you have a bug/feature/feedback) but does not explicitly mention when not to use it or provide alternatives. There is no exclusionary guidance, only the inferred purpose.

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 handled. The description adds the specific scope of what is shown (platform and adapter versions) but does not disclose any additional behaviors such as network usage or caching. With annotations carrying the safety burden, this is adequate but not exceptional.

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 immediately states the tool's function. There is no wasted wording or repetitive 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?

For a parameterless read-only version query with no output schema, the description fully covers what the agent needs to know: it returns the current platform and adapter versions. The annotations handle safety, so no further context is 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 and the input schema is empty. According to the rubric, the baseline for 0 parameters is 4, as there is nothing for the description to explain.

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 clearly states the resource ('current MCP platform and adapter versions'). This is unambiguous and distinct from sibling tools, which focus on authentication, marketplaces, and bug reports.

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/when-not guidance or alternatives are mentioned. The intended usage (whenever version info is needed) is implied by the purpose, but the description does not differentiate from potentially similar tools like 'toolkit_info' or offer exclusion criteria.

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 covered. The description adds value by specifying exactly what data is returned, which helps set expectations. It doesn't add extra behavioral details like latency or side effects, but for a simple read-only state tool 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?

The description is a single sentence that is front-loaded with the core purpose ('Returns the current toolkit state') followed by a compact list of included details. Every word earns its place, with no fluff 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?

Even without an output schema, the description fully explains what the return value contains: installed MCPs, their connection status, accounts per MCP, and catalog tool counts. For a zero-parameter state tool, this is complete and sufficient.

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 correctly focuses on the return value rather than parameters, and there are no param semantics to explain.

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 a specific verb ('Returns') and a specific resource ('current toolkit state'), and enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like 'authenticate' and 'connect' which are action-oriented.

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 tool is for obtaining the overall toolkit state, which implicitly tells an agent when to use it. However, it does not explicitly mention when not to use it or name alternative tools such as 'show_version' for more specific version information, so it falls short of a 5.

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