Enel CE: Download

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

Beyond annotations, the description explains behavioral details: no args returns a login link, token arg authenticates a session, and config-header auth is non-expiring. This supplements the idempotentHint and destructiveHint annotations and adds useful 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 concise and front-loaded with the login concept, and each clause covers a distinct use case. It is slightly dense with config instructions, but nothing is wasted.

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-optional-param tool with no output schema, the description covers the main invocation paths and outcomes. It lacks an explicit success/return explanation, but the flow is understandable.

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?

Although schema coverage is 0%, the description explains the single 'token' parameter: it should be a JWT pasted by the user, and the call with no args yields the link. This 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 states the tool's purpose: authenticating MCP.AI for IDE agents via browser login and access token. It clearly identifies the login flow and the server connection, though it doesn't explicitly distinguish itself 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 provides explicit usage modes: add the token to config for a permanent connection, or paste it for session-only login, with a no-args option to get the link. It doesn't discuss exclusion scenarios or alternatives, but the guidance is 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=true and idempotentHint=true, covering safety. The description adds valuable behavioral detail by explaining the two distinct return states (authenticated true vs. needing connection URLs), which goes beyond the annotations. It does not contradict the annotations, and it clarifies the output structure without requiring an output schema.

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 exactly two sentences, front-loaded with the primary purpose ('Returns connection status and URLs'), followed by the two conditional outcomes. Every sentence adds value with no redundancy or filler. It is well-structured and easy to parse.

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 params, no output schema), the description covers all crucial aspects: what it returns and the two main scenarios. It could elaborate slightly on the structure of connect_url or pending[], but it is sufficient for an agent to understand the tool's behavior. The description is complete enough for a read-only status check.

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 description coverage is 100% (trivially). Baseline for 0 params is 4. The description adds no parameter-specific meaning because there are none, which is appropriate. No need to compensate for missing schema info.

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: 'Returns connection status and URLs.' It specifies the resource (connection info) and the verb (returns), and distinguishes it from sibling tools like 'authenticate' (which performs authentication rather than checking status). The two concrete return scenarios make the purpose 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 provides situational context (e.g., when credentials are missing, when all providers are connected) but does not explicitly state when to use this tool over alternatives or when not to use it. There is no mention of alternatives like 'authenticate' or 'show_version', so the usage guidance is implied rather than explicit.

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 meaningful behavioral context beyond that: it discloses the payment model ('pague por consulta com crédito pré-pago'), the data sensitivity level ('não é dado sigiloso' — not confidential, same as available to citizens), and the LGPD compliance responsibility for the client. It does not contradict annotations — the query/download operation aligns with readOnly. The description enriches the annotation baseline with cost and legal/regulatory context rather than repeating what annotations already state.

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 of moderate density with the core purpose front-loaded ('Enel CE: Download, consulta em fonte oficial'). Each clause earns its place: purpose, hosting/auth model, payment method, data source and sensitivity, LGPD responsibility. No filler or redundancy. It could be slightly restructured for scannability, but it is compact and efficient — this reads as concise specification, not under-specification.

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 is a paid, external-service query tool with 4 parameters (3 required), no output schema, and 0% schema coverage. The description covers the high-level context (purpose, payment, data nature, legal responsibility) but omits several essential operational details: what the return values look like, how to obtain 'instalacao' and the Enel login credentials, what error conditions exist (insufficient credit, invalid credentials, rate limits), and parameter semantics. Given the tool's complexity and the absence of output schema and schema descriptions, the description is materially incomplete for safe and correct agent invocation.

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% — the four parameters (instalacao, login_email, login_senha, login_empresa) have no schema-level descriptions. The tool description does not individually explain any parameter. It mentions 'pague por consulta' which implies login credentials are for the Enel CE service rather than the platform, but it never defines 'instalacao' (likely a utility installation/meter number) or clarifies credential provenance. With zero schema coverage, the description was required to carry this burden but did not, leaving the agent to guess at parameter 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 opens with 'Enel CE: Download, consulta em fonte oficial' — a verb+resource statement (download/query Enel CE data from an official source). It clearly distinguishes from the generic platform siblings (authenticate, connect, marketplace, etc.) as a domain-specific data retrieval tool for a Brazilian utility company. The verb and resource are specific, leaving no ambiguity about what this tool does.

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 usage context: 'Hospedado pela plataforma, sem credenciais da plataforma' tells the agent that platform authentication is not needed, which implicitly signals not to use sibling 'authenticate'/'connect' first, and 'pague por consulta' states it's paid per query. However, there is no explicit 'when to use this vs. alternatives' guidance, no exclusions, and no mention of when a different tool would be more appropriate. It provides evident context but lacks explicit alternative mentions.

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 are sparse (readOnlyHint=false, openWorldHint=true), so the description carries a heavy burden and delivers: it discloses that invoke works even when the MCP isn't installed, returns connect/checkout links and asks the user to open them before retrying, and states that writes require workspace owner/admin. It also explains side effects like 'one-off install behind invoke' and permanent-toolkit changes from install, going well beyond annotation-provided info.

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 every sentence earns its place, covering the core flow, key edge cases (not installed, paid/wallet empty), permission requirements, and the prompt library. It is front-loaded with the main purpose and action flow. However, the lack of any bullet points or paragraph breaks makes it harder to scan; a structured format would earn a 5.

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 high complexity (14 actions, no output schema, no required params), the description is remarkably complete: it explains the search-describe-invoke flow, install vs one-off invoke, auth/credential handling, billing top-up behavior, permissions for writes, list_tools for current callables, the prompt library, and error-recovery retry pattern. It prepares the agent to handle most realistic scenarios without needing additional external documentation.

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% with 23 parameters, but the description compensates partially by explaining the meaning of key parameters: action's enum values (search vs describe vs invoke vs install), tool_id as the selected tool from describe, and arguments as parameters to that tool. It also describes the prompt-related actions (search_prompts, get_prompt, publish_prompt) and their purpose. However, it does not detail many peripheral params like tier_slug, immediate, cancel_comment, report_context, or prompt_vars, so it isn't a full substitute for schema-level 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 states a clear purpose: 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates specific sub-actions (search, describe, invoke, install, list_tools, subscribe, etc.) and distinguishes them from one another, making it unmistakable what this tool does and how it differs from siblings.

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 when-to-use guidance: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... invoke RUNS that tool.' It also states exclusions and preferences: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use,' and clarifies when to use request_mcp ('asks us to build a NEW MCP when nothing fits'). This is exemplary usage 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?

Annotations already declare idempotentHint=true and destructiveHint=false, indicating no destructive side effects. The description adds the instruction to include conversation history for reproduction, which is useful behavioral context. However, it doesn't disclose what happens after submission (e.g., no response, asynchronous processing).

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 fluff. The first sentence states purpose, the second gives the key usage detail. Perfectly sized for a simple tool.

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 low complexity (3 params, no output schema), the description covers the essential use case. It lacks details about the 'context' parameter and post-submission behavior, but these are minor gaps for a bug report 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?

The description explains the purpose of the 'conversation' parameter (include recent messages) and implicitly links 'message' to the bug/feedback content. However, the 'context' parameter is not mentioned, and schema descriptions are absent (0% coverage), so the description only partially compensates.

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 with specific verbs ('Report', 'send feedback') and identifies the resource (bug, missing feature, feedback). It distinguishes itself from sibling tools which are all unrelated (authentication, marketplaces, version checks).

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 usage context: use this tool to report bugs or give feedback. It also provides a concrete instruction (include the conversation array) but doesn't explicitly state when not to use it or reference alternative tools. Since siblings are unrelated, the implicit 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, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds no unexpected behavioral context, but there is little else to disclose for a version display tool.

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 compact sentence that front-loads the verb and states the exact output. Every word adds value and no unnecessary details are included.

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 trivial nature of the tool, no parameters, no output schema, and clear annotations, the description fully covers what an agent needs to know to correctly invoke and assess the impact of 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?

There are zero parameters and schema description coverage is 100%, so there is nothing meaningful to add beyond the schema. The baseline 4 for zero-parameter tools is appropriate.

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 uses specific verb 'Show' and resource 'current MCP platform and adapter versions,' making its purpose unambiguous. It clearly distinguishes from the sibling tools like authenticate and connect, which perform actions.

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 is for displaying version information, which is clear enough for obvious use. However, it provides no explicit exclusions or alternatives; this is acceptable for a trivial no-parameter tool, hence not a 5.

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 what the tool returns (specific details), which is useful context. No contradiction, and it effectively leverages annotations while adding value beyond 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 a single, front-loaded sentence with zero fluff. It conveys all necessary information efficiently and is appropriately sized for a simple read-only tool.

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 parameters, no output schema, and annotations covering behavioral safety, the description fully explains the return content (installed MCPs, status, accounts, catalog tool counts). It is complete for an agent to decide when and how to use it.

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 zero parameters, so the description has no parameter documentation burden. The baseline for a no-parameter tool is 4, and the description fully explains the tool's purpose without needing 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 clearly states the tool returns the current toolkit state and enumerates specific details (installed MCPs, connection status, accounts, catalog tool counts). It uses a specific verb ('returns') and resource ('toolkit state'), distinguishing it from siblings like show_version which likely returns 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 when to use it (to inspect toolkit state) but does not explicitly state when not to use it or mention alternatives. The context is clear enough for an agent to know it's a status/info tool, though no exclusions or sibling comparisons are provided.

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