Enel RJ: Lista de Instalações

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

Annotations already declare idempotentHint=true and readOnlyHint=false, and the description adds meaningful context: token use creates a session-only login, no-arg calls generate a link, and config-header auth yields a permanent non-expiring connection. This goes beyond the annotations without contradicting them.

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 reasonably compact and front-loads the main purpose. Some wording is slightly awkward ('log in in the browser'), but every sentence contributes meaningful setup or invocation details.

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 one-parameter auth tool with no output schema, the description covers the important pathways: browser login, config header persistence, session token, and no-args link retrieval. It could add a bit more about response/error behavior, but it is sufficiently complete for this 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?

Even though schema coverage is 0%, the description fully explains the single `token` parameter: it is optional, should be a JWT pasted by the user, and omitting it triggers the link-generation flow. This fully compensates for 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 identifies the tool as an auth/login flow for MCP.AI IDE agents, with the specific actions of logging in and copying an access token. It does not explicitly contrast itself with the sibling `connect` tool, so it lacks explicit sibling differentiation, but 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?

The description gives concrete usage guidance: permanent auth via config header, session-only auth via passed token, and no arguments to retrieve a login link. It does not explicitly state when to avoid using this tool or how it compares to `connect`, but it clearly explains how 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, which cover safety. The description adds valuable behavioral context: it explains the output states (authenticated: true with empty pending[] when all connected, connect_url when credentials missing) and mentions per-install URLs. It does not contradict 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 two sentences, tightly written with no fluff. Every sentence provides necessary information about the tool's behavior and output conditions, earning 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 the tool has no parameters and simple output, the description covers the essential behavior. It mentions output conditions and key fields (authenticated, pending[], connect_url), which is sufficient for an agent to invoke it. The lack of an output schema means the description does the work of explaining return values, and it does so adequately.

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, so there is no parameter semantics to add. Baseline for 0 params is 4, and the description does not waste space on 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 that the tool returns connection status and URLs, distinguishing it from sibling tools like 'authenticate' and 'marketplace'. It specifies output conditions (authenticated: true when all connected, connect_url when credentials missing), making the purpose concrete and 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?

The description explains what the tool returns in different states, which implies it should be used to check connection status before performing other operations. However, it does not explicitly state when to use this tool versus alternatives like 'authenticate' or 'toolkit_info', nor does it provide 'when not to use' guidance.

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 provide readOnlyHint, idempotentHint, and destructiveHint=false, but the description adds meaningful context: prepaid per-query cost ('pague por consulta com crédito pré-pago'), that data is not confidential ('não é dado sigiloso'), and LGPD compliance responsibility ('O cliente é o controlador dos dados'). This goes well beyond the structured 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 long, with the core purpose front-loaded in the first sentence and the remaining sentences adding relevant operational/compliance details. No wordy filler, though the LGPD clause could be seen as slightly verbose for tool-selection purposes.

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 read-only tool with 2 parameters and no output schema, the description covers purpose, official source, payment model, credential expectations, and legal responsibility. It does not explicitly describe the return value, but 'Lista de Instalações' strongly implies the output, so the context is adequately 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 description coverage is 0%, and the description only indirectly addresses the two login parameters by saying 'sem credenciais da plataforma'. While the parameter names login_email and login_senha are self-explanatory, the description does not explicitly state that these are Enel/RJ credentials or explain their format and purpose, leaving a partial 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 opens with 'Enel RJ: Lista de Instalações, consulta em fonte oficial', clearly stating the action (consultar/lista) and the resource (Enel RJ installations). It also distinguishes itself from the generic platform siblings (authenticate, connect, marketplace) by naming a specific domain and official source.

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 clear usage context: it queries official Brazilian sources, uses prepaid credit, and requires no platform credentials. However, it does not explicitly state when not to use this tool or name alternative tools for similar queries, so it lacks exclusions but is otherwise 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?

The description reveals key behavioral traits beyond annotations: invoke works even when the MCP is not installed, returns a connect link if credentials are needed, and returns a checkout/top-up link if the wallet is empty. It also states that writes require workspace owner/admin, and that search/describe flag installation status. These are concrete, non-obvious behaviors not present in 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 dense, single paragraph with long sentences and many clauses, making it harder to parse. It front-loads with the core purpose and then covers many details, but the structure could benefit from bullets or shorter sentences. Every sentence earns its place, but the formatting hampers quick comprehension.

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 23 parameters and no output schema, the description covers the main flows, auth requirements, and the prompt library well. It omits details on some actions (e.g., resume, detailed behavior of report_bug/request_mcp) and specifics on return values, but it is largely complete for selecting and using the tool at a high level.

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 does explain the action enum thoroughly and implicitly references query, mcp_id, tool_id, and arguments through the workflow. However, many parameters (limit, immediate, tier_slug, prompt_body, prompt_vars, cancel_reason, etc.) are not explicitly described, leaving unclear how to populate them.

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 mcp.ai marketplace catalog and execution interface, with a specific verb+resource structure: 'search discovers MCPs', 'describe returns one MCP's full profile', 'invoke RUNS that tool'. It also distinguishes from sibling tools by focusing on marketplace functionality rather than authentication, connection, or version 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 gives explicit decisions: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', and outlines the core flow of search → describe → invoke. It also clarifies when to use list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt-library actions, with sufficient context to guide selection among the many actions.

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 communicate the side-effect profile (readOnlyHint=false, destructiveHint=false, idempotentHint=true). The description adds the useful behavioral hint that the conversation should be included for reproduction, but it does not clarify what happens after submission, such as ticket creation or expected outcome.

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 short sentences with no wasted words. It front-loads the core purpose and adds only the one additional detail that directly improves reproduction 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 low-complexity tool with three simple parameters and no output schema, this description covers the purpose, the main required input, and the key reproduction guidance. It does not document return behavior, but that is not essential for a straightforward feedback-reporting 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, the description carries the full burden for parameter meaning, but it only addresses `conversation`—and even calls it an 'array' while the schema defines it as a string. `message` and `context` are not explicitly defined, leaving 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 uses a specific verb ('Report') and clearly names the resource scope: bugs, missing features, and feedback. None of the sibling tools overlap with this responsibility, so the purpose is effectively differentiated.

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 clearly states when to use the tool—for bugs, missing features, or feedback—and immediately tells the user to include the conversation array for reproduction. It does not explicitly name exclusions or alternatives, but the sibling list contains no conflicting tool, so the guidance is sufficient.

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. The description adds that it returns both MCP platform and adapter versions, which provides behavioral context about the tool's output. This goes beyond the annotations by specifying what kind of version information is returned.

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, clear sentence with no unnecessary words. It is perfectly compact and front-loads the action ('Show') and object ('current MCP platform and adapter versions'), leaving no room for ambiguity.

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?

This zero-parameter tool with no output schema requires minimal description. The description fully covers what it does: it shows versions. There is no missing information for a user to understand when to invoke this 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 zero parameters, the schema coverage is 100% trivially. The baseline for 0 params is 4, and the description adds no additional parameter documentation needed since there are none. The score matches the baseline expectation.

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-resource pair: 'Show the current MCP platform and adapter versions.' It clearly distinguishes this as a version query tool, which is distinct from sibling tools like 'authenticate' or 'connect'. The purpose is unambiguous and complete.

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?

For a simple read-only versioning tool, there is no need for explicit alternatives or conditions. The description implies its use case (checking versions), and given the tool's trivial nature, no further guidance is necessary. The score reflects that while no exclusions are stated, none are needed here.

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 useful behavioral context by specifying exactly what state is returned and that it reflects the 'current' snapshot, which goes beyond what annotations alone convey.

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. It lists the returned information compactly without wasted words, and every phrase adds specific meaning.

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 introspection tool with no output schema, the description fully covers what the tool does and what information it returns. There is no missing context required for an agent to select and invoke 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 tool has zero parameters, so the description is not expected to explain parameter semantics. Baseline 4 is appropriate because there is no parameter burden to compensate for, and schema coverage is trivially complete.

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 what that includes: installed MCPs, connection status, connected accounts, and exposed catalog tool counts. This clearly distinguishes it from sibling tools like connect or authenticate, which perform actions rather than report state.

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 its use case: whenever an agent needs to inspect toolkit state or connection status. However, it does not explicitly state when to prefer this over alternatives or mention exclusions, so it relies on inference rather than providing direct guidance.

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