Light: Download + OCR

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

The description discloses key behavior beyond the annotations, such as the difference between permanent config and session-only login, and the fact that a user pasted token is needed. It is idempotent and non-destructive per annotations, which the description does not contradict.

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 compact paragraph of a few sentences, each carrying useful information. The mention of 'MCP.AI for IDE agents (Cursor, etc.)' adds some context but a little noise; still, nothing is bloated.

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 minimal schema and no output schema, so the description carries most of the load. It sufficiently explains the two call modes and the config alternative, though it does not explicitly say what a successful token call returns.

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 provides no description for 'token', but the description fully compensates: it clarifies that the JWT is the token pasted by the user and that omitting the token returns the login link. This gives the agent clear invocation semantics.

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 an authentication flow: getting a login link or passing a JWT token. It is not tautological and points to a specific action and resource, but it does not explicitly differentiate from the sibling 'connect' tool.

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 gives explicit usage variants: no args to retrieve the link, token arg for session-only auth, and a recommended permanent config path. This is useful guidance, although it does not mention when not to use the tool relative to sibling 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 description adds details about the output structure beyond the annotations, such as the authenticated flag and pending array, and explains the behavior in missing-credential scenarios. It does not contradict the read-only and idempotent 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 concise, using two sentences to convey the purpose and behavioral details without unnecessary verbosity.

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 scenarios of connection status, but does not address partial connection states or error handling. However, given the simplicity of the tool and the annotations, it is sufficiently complete for its purpose.

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 no parameters, and the description does not mention any input. Since there are zero parameters, the schema coverage is complete, and the description adds nothing about parameters, which is acceptable per the baseline.

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 that the tool returns connection status and URLs, and provides specific conditions for the output, making it distinct from sibling tools like authentication or download.

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 does not explicitly state when to use this tool over alternatives, but the purpose is clear. It lacks direct guidance on when to invoke it, though the conditions mentioned are output conditions rather than usage instructions.

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, openWorldHint=false, idempotentHint=true, destructiveHint=false, and the description complements this by explaining the data source (official Brazilian sources), the privacy context (no sensitive data, LGPD compliance), the payment model (pay-per-query with prepaid credit), and the responsibility split (client is data controller). This goes well beyond the annotations, detailing what the tool does not access (sensitive data) and the legal framework.

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. It front-loads the core purpose and then covers key behavioral aspects compactly. It's longer than a simple sentence but covers a lot of ground efficiently. Could arguably be split into structured bullet points for readability, but the flow is logical.

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 output schema and 5 parameters, the description does a good job covering the essentials: what it does, where data comes from, data privacy, and commercial model. The main gap is in parameter semantics and the fact that it doesn't describe expected response format, though with no output schema present, the tool's return values are left to the agent's imagination. The description is reasonably complete for an external consultation 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?

With 0% schema description coverage and no parameter descriptions in the description, the tool relies entirely on the input schema property names (login, senha, mes, codigo_cliente, codigo_instalacao). The description adds no parameter-level semantics beyond what's in the schema, and the Portuguese terms (like 'mes' for month) might require locale understanding. The description doesn't explain the meaning or format of these parameters, especially codigo_cliente vs codigo_instalacao.

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 says 'Light: Download + OCR, consulta em fonte oficial' – it clearly identifies this as a download and OCR consultation tool with official sources, using a specific verb+resource structure. It distinguishes itself from siblings by explaining it's a data consultation tool but doesn't explicitly name a sibling alternative.

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 explains when to use it ('consulta em fonte oficial', 'mesma disponível ao cidadão'), implies the use case of querying official Brazilian sources, and clarifies that it doesn't require platform credentials. It offers implicit context for when to use (for official data queries) but does not explicitly state when not to use it or name 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?

Beyond the annotations (which only provide hints like readOnlyHint=false and openWorldHint=true), the description reveals critical behavioral details: invoke works even if the MCP is not installed, does not add it to the toolkit, returns connect links for auth, returns checkout links for payment, and requires workspace owner/admin for writes. It also discloses that search/describe flag installed status and that install/uninstall/subscribe/cancel are persistent. 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 information-dense but delivered as a single unbroken paragraph, making it hard to scan. It leads with the main purpose and then covers core flows, caveats, permissions, and the prompt library, but could benefit from bullet points or short sections. It is not tautological, but its length and lack of structure reduce its efficiency.

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 enormous scope (14 distinct actions, 23 parameters, no output schema, sparse annotations), the description covers the major workflows: search/describe → invoke, install/uninstall, billing, permission requirements, and the prompt library. It omits details on return values and some sub-action behaviors, but for an agent selecting and invoking the tool, the essential context is present.

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 23 parameters and 0% schema coverage, the description must compensate. It explains the central 'action' parameter and key related parameters (tool_id, arguments, prompt_* fields) by describing the actions they drive. However, many parameters (limit, immediate, tier_slug, conversation, request_details, cancel_reason, etc.) remain semantically opaque, leaving the agent without full parameter understanding despite the description's effort.

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 — the in-platform catalog of every MCP/tool, AND the way to run them,' with an explicit scope covering catalog search, MCP execution, and prompt library access. It uses explicit verbs and resources (search, describe, invoke, install, list_tools, search_prompts, etc.) and distinguishes itself from sibling tools by defining its unique marketplace role.

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 detailed when-to-use guidance: 'prefer invoke for a single/occasional use,' 'Use install only to make an MCP PERMANENT,' and clarifies when credentials or payment are needed ('invoke returns a connect link' / 'checkout/top-up link'). It also distinguishes search/describe from list_tools and separates prompt library functions from MCP operations, giving 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 cover safety aspects (readOnlyHint=false, idempotentHint=true, destructiveHint=false), and the description adds the behavioral note about including the conversation array for reproduction. No contradiction exists, but it does not disclose potential side effects or response behavior beyond that.

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 primary purpose. No redundant information or filler; every word adds value.

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 tool with 3 parameters and no output schema, the description adequately covers the main purpose and reproduction guidance, but lacks explicit explanation of all parameters and the expected outcome. Given low complexity, this is a minimal viable description.

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 must explain all parameters. It only addresses 'conversation' ('Include the conversation array'), while 'message' and 'context' are left unexplained. 'message' is required and its purpose (the bug report text) is only implicitly implied, and 'context' is entirely omitted.

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 ('bug, missing feature, or send feedback'). It is easily distinguishable from sibling tools like 'authenticate' or 'show_version', which have 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 provides clear context for when to use the tool (reporting bugs, missing features, or feedback) and instructs to include the conversation array for reproduction. However, it does not explicitly state when not to use it or mention alternative tools, leaving scope for ambiguity.

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 safety. The description adds behavioral context by specifying exactly what version information is shown (platform and adapter), which is not redundant with annotations. No contradictions detected.

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, concise sentence that front-loads the action and resource. No filler or unnecessary details. 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?

Given zero parameters, no output schema, and strong annotations (readOnly, idempotent, non-destructive), the description fully covers what the tool does. It is complete for a simple version-query tool, providing enough context that an agent can confidently call it without ambiguity.

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 schema description coverage is 100%. The description does not need to explain parameters since there are none. Baseline is 4 due to no parameter requirements; the description adds appropriate clarity about the value returned.

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 a clear resource ('current MCP platform and adapter versions'). It distinguishes from sibling tools by naming the exact scope (MCP platform and adapters), which none of the siblings (authenticate, connect, marketplace, report_bug, toolkit_info, contas_light_download_ocr_consultar) appear to cover.

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 does not explicitly state when to use this tool versus alternatives, but the purpose is self-explanatory. For a version-info tool, usage is inherently obvious and safe to call anytime. Lacks explicit 'when to use' or 'when not to use' guidance, but the context of a version query is 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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the specific state fields returned, but no extra behavioral context such as authentication requirements, rate limits, or freshness of the data.

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-ordered sentence with no redundancy. It front-loads the purpose and enumerates the key output contents efficiently.

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 info tool, the description is complete: it lists the installed MCPs, connection statuses, and associated accounts, covering the expected return content. No output schema exists, but the description provides sufficient clarity without needing extra 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 tool has zero parameters and no required fields, so there is no parameter semantics to elaborate. The baseline of 4 applies because the schema and context fully cover the absence of parameters; description adds no conflicting or missing details.

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 uses the verb 'Returns' and specifies the exact resource: the current toolkit state, including installed MCPs, connection status, linked accounts, and tool counts. This distinguishes it from sibling tools such as show_version and 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 purpose implies use whenever the agent needs an overview of the toolkit's installed integrations and connection status. However, there is no explicit guidance on when not to use it or which sibling tools to prefer, though the scope is fairly intuitive.

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