CPFL: Download

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

Annotations indicate idempotentHint=true and destructiveHint=false, which align with the description's non-destructive nature. The description adds context about the token being non-expiring if added to config, and session-only if pasted. It also mentions the browser login flow. This goes beyond annotations by explaining the authentication flow and token persistence, which is valuable.

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 and front-loaded with the main purpose. It uses a colon to introduce the two usage modes, which is efficient. However, it could be slightly more structured (e.g., bullet points) but overall it's well-organized and not 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?

Given the tool's simplicity (one optional param, no output schema), the description covers the essential aspects: how to authenticate, the two modes, and the token handling. It doesn't mention error cases or what happens if the token is invalid, but for a simple auth tool, this is adequate. The description is complete enough for an agent to use it 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?

The schema has one optional parameter 'token' with no description. The description explains that the token is a JWT and how to use it: call with { token: "<jwt>" } after the user pastes, or with no args to get the link. This adds meaning beyond the schema, but the description doesn't elaborate on the token format or validation. Since schema coverage is 0%, the description compensates partially, but could be more explicit about the token's role.

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: to authenticate with MCP.AI by logging in via browser and obtaining an access token. It distinguishes between two usage modes (permanent config vs session-only) and mentions the tool name 'authenticate' implicitly. It doesn't explicitly contrast with siblings, but the purpose is specific and actionable.

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 guidance on when to use this tool: for IDE agents like Cursor, and explains two usage scenarios: adding the token to server config for permanent connection, or pasting the token for session-only login. It also tells the agent to call with no args to get the link, and with token to complete login. This is clear and actionable.

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, so the safety profile is covered. The description adds valuable behavioral detail about the response structure (authenticated, pending, connect_url) in different states, going 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?

Two sentences, no redundancy, front-loaded with the core purpose, and the conditional outputs are clearly summarized. 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?

For a zero-parameter read-only tool with no output schema, the description is largely sufficient, but it only covers the two extreme states (all connected vs missing credentials), leaving potential partial connection states unaddressed.

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 fully covers everything. Baseline of 4 applies, and the description need not explain parameters.

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 'Returns connection status and URLs', which is a specific verb+resource. It is unambiguous but does not explicitly differentiate from the sibling 'authenticate' tool, though the read-only nature implies status checking rather than establishing connections.

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 conditional scenarios: when all providers are connected vs when credentials are missing, which implies when to use the tool for checking status. However, it does not explicitly name alternatives or exclusions, though the context is clear enough.

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 (readOnlyHint, idempotentHint, destructiveHint), the description discloses payment per query ('pague por consulta com crédito pré-pago'), the non-confidential nature of the data ('não é dado sigiloso'), and LGPD responsibility. This adds 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 concise, with the key action and resource front-loaded in the first sentence. The remaining two sentences add relevant context (hosting, payment, LGPD) without unnecessary elaboration.

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 4 parameters, no output schema, and no parameter explanations, the description is insufficient for an agent to invoke the tool correctly. It lacks return behavior, parameter semantics, and operational details, despite providing some high-level context.

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 does not explain any of the four parameters (email, senha, instalacao, unidade_consumidora). It even creates ambiguity by stating 'sem credenciais da plataforma' while requiring email/senha, leaving users to infer these are external credentials.

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 'CPFL: Download, consulta em fonte oficial,' identifying a specific resource (CPFL) and actions (download/query). It distinguishes itself from generic sibling tools like authenticate or marketplace, though it could be more explicit about what is being consulted (e.g., utility bills).

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 no direct guidance on when to use this tool compared to alternatives. It mentions 'sem credenciais da plataforma' and the prepaid payment model, but these are operational traits, not explicit use-case instructions or exclusions.

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 indicate non-read-only, non-idempotent, open-world behavior. The description adds meaningful context: writes require owner/admin, invoke returns connect/checkout links for auth/payment follow-up, install is permanent while invoke is one-off, and search/describe flag installation status. It does not describe all possible side effects (e.g., uninstall consequences, billing side effects), but it covers the major behavioral traits. No contradiction with annotations; this is solid 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 (about 280 words) but dense and front-loaded with the core flow (search → describe → invoke). Each sentence adds essential information about capabilities, key behaviors, or usage distinctions. It could be more structured (e.g., bullet points) for easier parsing, but given the tool's complexity and multiple action families, the prose is justified and not redundant.

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 23 parameters, no output schema, and complex multi-action behavior, the description covers the essential context: a clear core flow, the distinction between invoke and install, auth/payment handling, owner permissions, prompt library, and even workspace/toolkit flag semantics. It lacks explicit return structures for each action (e.g., what search returns beyond results), but given the absence of an output schema and the extensive prose, it is reasonably complete for an agent to use the main flows.

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 `action` enum and high-level concepts (e.g., tool_id, arguments, prompt slugs) through the core flow, but the majority of the 23 parameters—`limit`, `immediate`, `conversation`, `prompt_targets`, `cancel_reason`, `report_context`, etc.—are never defined. An agent would have to guess at required values for many auxiliary actions, making correct invocation difficult. The description only partially compensates for the missing schema descriptions.

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 explicitly identifies the tool as 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly states its function (discover, describe, invoke, install, manage MCPs and prompts) and distinguishes it from sibling tools by being the central hub. The verb+resource is specific: it's the marketplace that both catalogs and runs MCPs/prompts.

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 thorough guidance on when to use each action: use invoke for one-off runs, install for permanent installation, list_tools to see what's callable, subscribe/cancel for billing, request_mcp for new tools, and the search/describe flow for discovery. It also explains key nuances like 'invoke works even when the MCP is NOT installed' and that writes require workspace owner/admin. This explicitly frames when to use this tool and its internal actions, going beyond mere existence.

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, idempotentHint=true. The description adds that the conversation array is needed for reproduction, which informs the agent about the expected input. It does not disclose additional behavioral traits (e.g., that data is submitted externally or side effects beyond reporting). No contradiction with annotations, but the added value is modest.

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 concise sentences: the first states the purpose directly, the second gives a critical usage hint. No unnecessary words, perfectly front-loaded.

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 three parameters (one required), no output schema, and rich annotations. The description covers the main purpose and the key reproduction guidance. It omits explanation of the 'context' parameter, but given the simplicity and that the schema provides defaults, it is largely complete. Could be slightly richer, but adequate.

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 (recent messages for reproduction) and implies 'message' is the content of the bug/feedback. However, it does not clarify the 'context' parameter or the default values. It adds meaning to two of three parameters, partially compensating for the lack of 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 the verb 'Report' and the resources: 'bug, missing feature, or send feedback.' It is specific and distinct from sibling tools (authenticate, connect, marketplace, etc.), which are unrelated. The purpose is 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 says to use this tool for reporting bugs, missing features, or feedback, providing clear context. It also gives a specific instruction to include the conversation array for reproduction. However, it does not explicitly mention when not to use it or alternatives, though siblings are unrelated, so exclusion is less critical.

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 context by specifying exactly what is shown (MCP platform and adapter versions), which is useful 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?

A single, clear sentence delivers the entire description. No wasted words, front-loaded and immediately readable.

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, parameterless tool, the description is complete. It states what the tool shows, and given the absence of an output schema, it sufficiently conveys the expected return. A minor gap is lack of detail about how versions are presented (e.g., text, JSON), but this is unlikely to confuse an agent.

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 complete coverage by definition. The description doesn't need to add parameter semantics, and it correctly doesn't invent any.

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?

Description clearly states the verb 'Show' and the specific resources: 'current MCP platform and adapter versions.' This precisely defines the tool's function and distinguishes it from siblings like toolkit_info, which might provide broader 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 context is clear: use this tool to display version information. While it doesn't explicitly mention when not to use it or alternatives, the tool's purpose is self-evident and no competing sibling appears to overlap directly, so the absence of exclusions 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, so the safety profile is covered. The description adds value by specifying what the returned state includes (installed MCPs, connection status, accounts, catalog tool counts), which 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 a single, well-structured sentence that front-loads the purpose and lists the key information returned. Every word earns its place with no fluff.

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 has no parameters, no output schema, and strong annotations, the description is complete enough. It clearly states what the tool returns, which is the main thing an agent needs to know. It could mention that it's a snapshot or that it might require authentication, but that's minor.

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 description doesn't need to explain parameter semantics. The baseline for 0 params is 4, and the description appropriately focuses on the return value instead.

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 the current toolkit state, listing specific elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource and distinguishes it from sibling tools like authenticate or connect.

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 a read-only informational tool for checking the toolkit state, which is clear from the context. It doesn't explicitly state when to use it versus alternatives, but the purpose is self-evident and no exclusions are needed.

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