Enel SP: Download + OCR

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

Beyond annotations (which indicate idempotent, non-read-only, non-destructive), the description explains behavioral traits: no args returns a login link, passing a token establishes a session, and config header creates a permanent non-expiring connection. It discloses the flow and token semantics, adding meaningful context 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 concise, front-loaded with purpose, and every sentence earns its place. It efficiently covers the auth flow, permanent vs. session options, and token usage 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 tool with one optional parameter and no output schema, the description is complete. It explains how to use both invocation modes, what to expect when no token is passed, and the recommended permanent setup. No critical information is missing.

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 defines a single token string with no description, but the description fully compensates by explaining that token is a JWT to be pasted after user login, that it is optional, and that omitting it yields a link. This adds critical meaning that the schema lacks.

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 to MCP.AI for IDE agents (Cursor, etc.). It uses specific verbs and resource ('log in', 'access token') and differentiates itself from siblings by describing the browser-based login flow and the optional token parameter. The purpose is unmistakable.

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, including two distinct usage paths: permanent connection via config header with Authorization: Bearer, and session-only login by passing a JWT token. It also specifies calling with no args to get the link, giving clear alternatives and context for each mode.

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 discloses the output behavior for different states (all connected vs. missing credentials), providing transparency beyond the readOnly annotation.

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, with two sentences, and front-loads the primary purpose.

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 output states but does not mention any edge cases like partial connections, so it is mostly 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?

There are no parameters, and the schema is empty, so parameter semantics are not applicable; the baseline score is given.

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, which specifies its 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 does not explicitly state when to use this tool compared to alternatives like authenticate, so usage guidance is lacking.

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 (readOnly, idempotent, non-destructive), the description adds context about being hosted on the platform, requiring no platform credentials, involving prepaid credits, and clarifying data control and LGPD compliance. This enhances transparency about operational and legal 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 concise, but contains slight redundancy (repeats 'fonte oficial' and 'oficiais'). It is structured as a single paragraph with clear sentences, though not overly verbose.

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 lacks context about the OCR purpose, what data is downloaded, or the expected output. It also does not mention prerequisites like having an account or credits, leaving the overall workflow unclear.

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 description provides no explanation of the parameters (instalacao, login_email, login_senha). The schema lacks descriptions, so the description should compensate, but it does not. Users are left to infer the purpose of these fields.

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 states the tool performs 'Download + OCR, consulta em fonte oficial' for Enel SP, clearly indicating a query operation on official Brazilian sources. It is specific to Enel SP but could be more explicit about the exact data retrieved.

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 mentions payment with prepaid credits but does not indicate when to use this tool versus alternatives. It does not compare with sibling tools like authenticate or connect, nor specify scenarios where this tool is preferred.

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 richly discloses side-effect behaviors beyond annotations: invoke works even when the MCP is not installed, returns connect/checkout links, and requires retry after user action. It also explicitly states that writes (install/uninstall/subscribe/cancel and one-off install behind invoke) require workspace owner/admin, adding meaningful context given readOnlyHint is false.

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?

Despite its length, the description is tightly packed with high-value information, progressing logically from core concept to workflow to edge cases to prompt library. Every sentence earns its place; it is neither bloated nor under-specified given 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?

The description covers all major action families and the prompt library, making it quite complete for the tool's complexity. Minor gaps remain (e.g., the 'resume' action, parameter 'immediate' semantics), but these are niche relative to the primary use cases and the lack of an output schema is not an issue.

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 compensates well by explaining the semantics of key parameters (action, mcp_id, tool_id, arguments, prompt_slug, prompt_vars) within workflow examples. However, it omits some params like 'resume', 'immediate', 'tier_slug', and 'cancel_reason', though most self-named params remain inferable.

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 is exceptionally clear: it states the tool is 'the official mcp.ai marketplace' and outlines the core search → describe → invoke workflow. It clearly distinguishes this from sibling tools by positioning it as both the catalog and execution engine for MCPs.

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 a single/occasional use', 'Use install only to make an MCP PERMANENT', 'list_tools lists what is callable right now', and 'request_mcp asks us to build a NEW MCP when nothing fits'. This provides strong when/to-use and alternative recommendations.

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 declare readOnlyHint=false, destructiveHint=false, idempotentHint=true, openWorldHint=false. The description does not contradict these. It adds context by instructing to 'Include the conversation array with recent messages for reproduction,' which tells the agent what to include. However, it doesn't explain side effects (e.g., whether this sends a network request, stores data, or has rate limits). With annotations providing some safety profile, the description provides modest added 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?

Two sentences total, front-loaded with purpose, then a helpful instruction. Every word earns its place. Excellent structure.

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 feedback/report tool, the description is quite complete given its simplicity. It explains the purpose and gives one key instruction about the conversation array. An output schema is absent, but the tool likely doesn't need one. The tool is simple enough that the description suffices, though more detail about the 'context' field could push it higher.

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 mentions the conversation array explicitly and its purpose ('with recent messages for reproduction'), which adds value. However, it doesn't explain the 'context' field or the format of 'message'. The description partially bridges the gap but not fully.

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.' It uses a specific verb ('report') and resources ('bug, missing feature, feedback'). It doesn't explicitly distinguish from siblings, but the sibling names (authenticate, connect, etc.) are not related to reporting, so purpose is clear enough.

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 when to use it (to report issues or feedback) but doesn't explicitly state when not to use it or mention alternatives. Given the sibling tools are unrelated, the usage context is fairly clear, but no exclusions or alternatives are given.

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 annotations already declare the tool as read-only and idempotent, so the description does not need to add extra behavioral details. It does not contradict the annotations, but it also does not provide additional context such as side effects or dependencies.

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 with no unnecessary words or repetition. It is well-structured and directly conveys the tool's purpose.

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 simplicity of the tool (no parameters, no output schema specified), the description is sufficiently complete. It clearly states what information the tool retrieves, without needing to describe return formats or side effects.

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 input schema is trivially fully covered. As per instructions, with 0 parameters the baseline is 4, and the description adequately explains what the tool does without needing parameter clarification.

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: showing the current MCP platform and adapter versions. It uses a specific verb ('show') and a clear resource ('versions'), distinguishing it from the sibling tools which handle authentication, connection, file downloads, marketplace, and bug reporting.

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 when to use the tool (whenever version information is needed), but does not explicitly mention alternatives or when not to use it. Since there are no similar tools among the siblings, the context is clear enough, but explicit guidance is missing.

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, and the description is consistent with those traits, merely promising to return information. It adds useful context about what is returned, but does not disclose any extra behavioral aspects such as data freshness, permissions, or side effects, which is acceptable given the annotation coverage.

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 clear front-loading, listing the return categories in a compact, readable manner. Every section of the description adds meaningful detail without any filler or unnecessary 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 parameter-free, read-only tool with strong annotations, this description is enough for an agent to understand exactly what information will be available. It enumerates the main dimensions of the returned state and does not need an output schema to clarify behavior or result shape.

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?

This tool has zero parameters, so the input schema already provides complete parameter coverage and the description does not need to add parameter-level explanations. The description instead focuses on the return content, which fits the parameter-independent nature of this tool.

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 as 'the current toolkit state', enumerating installed MCPs, connection status, accounts, and catalog tool counts. This scope fully distinguishes it from action-oriented siblings like authenticate/connect and from version-focused tools 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 intended usage is implied: an agent would call this when it needs to inspect the current toolkit state, such as before or after authentication/connection steps. However, the description does not explicitly state when to use it versus alternatives or mention any prerequisites/exclusions, so guidance remains implicit rather than explicit.

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