Neoenergia (Elektro): Download

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

Beyond annotations (idempotentHint, readOnlyHint false), the description discloses important behavioral nuances: token-based login is session-only while config-based is permanent and non-expiring, and calling with no args returns a link. This is useful context that helps the agent understand the tool's side effects and longevity.

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 somewhat wordy and the first sentence is awkwardly phrased, mixing an audience note with instructions. It could be tighter, but it avoids redundancy and all sentences contribute either to usage or context. Structure is acceptable but not exemplary.

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 lack of an output schema, the description partially covers return behavior ('to get the link') but does not specify what the tool returns upon successful token submission or any error handling. The authentication flow is explained, but the focus on config instructions distracts from the tool's own output. It is sufficient for a simple tool but not fully 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?

Schema coverage is 0%, so the description carries the full burden. It clearly explains the 'token' parameter: it is a JWT to be pasted after user authentication, and it is optional since calling with no args is supported. This adds meaningful semantics beyond the bare schema.

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 conveys the tool's function: authenticating to the MCP.AI server by either obtaining a login link or submitting a token. It distinguishes this from generic connection via its focus on authentication, though the opening 'MCP.AI for IDE agents' is somewhat vague and not a crisp verb-first statement.

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 modes: call with no args to get a login link, or call with a token for session-only login. It also contrasts this with the more permanent config-based approach, giving clear guidance on when to use each. It does not explicitly compare to sibling tools but offers practical 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, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds useful behavioral context by specifying outputs for 'all providers connected' versus 'credentials missing,' including authenticated:true, pending[], and connect_url.

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 includes no redundant or filler content. Every sentence adds meaningful behavioral 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 key return states and fields without an output schema, which is good for a simple read-only status tool. It could be more complete by addressing partial connection states, but the provided info is sufficient for most use cases.

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 baseline is 4. The description correctly focuses on behavior rather than parameter details, and there is no schema information to compensate for.

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 and resource: 'Returns connection status and URLs.' It distinguishes itself from siblings like authenticate by being a read-only status check rather than an authentication action.

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—checking connection status and retrieving URLs—and describes behavior under different credential states. However, it does not explicitly contrast with alternatives like authenticate or state when not to use this tool.

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 the tool as read-only and idempotent. The description adds important behavioral context: the payment model, lack of platform credentials, the public nature of the data, and LGPD responsibilities. This goes beyond what annotations provide.

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 four sentences, each adding meaningful information. It is front-loaded with the purpose and not overly verbose, though some redundancy exists (e.g., 'oficiais' repeated).

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 7 parameters, no output schema, and no parameter explanations, the description is insufficient for an agent to understand the expected inputs or return values. It covers purpose, payment, and legal aspects but omits critical operational details.

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 provides no explanation for any of the 7 parameters (uc, uf, mes_ano, login_cpf, login_cnpj, login_senha, acesso_imobiliaria). The agent is left to guess their meaning and format, making correct invocation difficult.

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 performing downloads/queries from an official Neoenergia source, and the name includes 'contas' to indicate utility bills. It distinguishes itself from generic platform siblings, though it could be more explicit about the exact data being 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 provides useful context for usage: it is hosted, requires no platform credentials, charges prepaid credit per query, and queries official public data. It does not explicitly name alternatives, but the sibling tools are unrelated generic operations, so this 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?

Reveals that invoke runs tools one-off without installation, that install makes permanent, that write actions require workspace owner/admin, and that auth/payment gaps return connect/checkout links. These behaviors go far beyond the sparse annotations and add critical 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 long but each section earns its place, covering the action flow, invoke vs install, auth/wallet handling, permissions, and the prompt library. It uses clear 'Core flow' and 'KEY' markers, though it could benefit from bullet-point formatting for the 14 actions.

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 this complex (14 actions, 23 params, no output schema), the description covers the central use cases, edge cases, and permission model well. Missing details on some actions (resume, request_mcp) and parameters prevent a perfect score.

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 explains key parameters through the workflow (query, mcp_id, tool_id, arguments, prompt_* fields) but leaves many schema fields (limit, request_details, report_context, cancel_reason) unspecified. Given 0% schema coverage, it substantially compensates but not exhaustively.

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?

Clearly identifies the marketplace as the catalog and execution layer for MCPs, with an explicit search→describe→invoke flow. Distinguishes itself from sibling tools by covering discovery, running, installation, billing, and the prompt library.

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 states the core flow, when to prefer invoke over install, how to handle connect/checkout links, and what list_tools/subscribe/cancel/report_bug/request_mcp do. This gives clear directives for agent decision-making.

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 expected behavior by instructing to include the conversation array for reproduction. It does not contradict the annotations (idempotent, non-destructive) and provides transparency about input requirements beyond what the schema offers.

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, one sentence, and efficiently conveys the purpose and a key instruction. It is well-structured and free of 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?

The description is sufficient for a simple reporting tool. It explains what to do and what to include, and there is no output schema to worry about. Minor gap: it does not mention any return value or confirmation, but that is not critical for this action.

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 no descriptions for parameters. The description only mentions the conversation array, but does not explain the required 'message' parameter or the optional 'context' parameter. With 0% schema coverage, the description fails to compensate for most parameters, leaving ambiguity.

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: reporting bugs, missing features, or feedback. It is specific and distinct from sibling tools like authentication or version info.

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 the intended use case (reporting issues) and provides a specific instruction to include the conversation array, which is a guideline. It does not explicitly contrast with alternatives, but the context makes it 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds no further behavioral details beyond that, such as response format or potential side effects, though none are expected for a version query.

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, front-loaded sentence that concisely conveys the tool's purpose without redundancies 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 zero-parameter, read-only version query, the description is complete. It identifies what versions are returned and carries no complex behavioral or output-structure requirements that would demand additional 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 the schema covers them completely, so parameter-level documentation is unnecessary. The description contributes no parameter semantics, but 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's action ('Show') and resource ('the current MCP platform and adapter versions'). It is specific enough to distinguish itself from the sibling tools, none of which are version-focused.

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 the tool should be used when version information is needed, but it does not explicitly state when to use it versus alternatives or mention any exclusions. This is adequate but relies on the user/agent to infer context.

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 valuable behavioral detail by specifying the exact state components returned, going beyond what annotations alone communicate.

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 front-loaded sentence that immediately states the tool's purpose and then lists the concrete return contents. Every word contributes value; there is no repetition of the tool name or schema 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 info tool with strong annotations and no output schema, the description is fully adequate. It names all relevant facets of the returned toolkit state and leaves no major ambiguity about what the agent will receive.

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 coverage is 100%, so the description does not need to compensate for undocumented inputs. The baseline of 4 for no-parameter tools applies, and the description adds no irrelevant parameter 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 uses a specific verb ('Returns') with a clear 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 connect, authenticate, and 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 implies this is a read-only introspection tool for checking overall toolkit state, which is reasonable guidance. However, it does not explicitly state when to prefer this over siblings like show_version or when not to use it, leaving usage conditions 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.