Enel SP: Gestão Imobiliária

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

Annotations already indicate non-read-only, non-destructive, and idempotent behavior. The description adds context about the token being a JWT and explains the two authentication modes (permanent vs. session). It doesn't contradict annotations and provides useful operational details, though it doesn't mention behavior on invalid tokens or repeated calls.

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 paragraph that front-loads the purpose and then explains both usage paths. It avoids unnecessary fluff but could be slightly better structured with bullet points. Still, every sentence earns its place by conveying essential instructions.

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 one optional parameter and no output schema, the description fully covers the authentication flows: browser login, token capture, config setup for persistence, and session-only usage. It also tells the agent exactly how to invoke the tool under different conditions, making it complete for the intended use case.

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 by explaining the 'token' parameter as a JWT string and clarifies it is optional (calling with no args returns a link). This gives the agent the necessary semantic understanding beyond the bare schema property definition.

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 authenticates the user for MCP.AI, describing two mechanisms (browser login with token or configuration header). It uses a specific verb ('authenticate'), names the resource ('MCP.AI for IDE agents'), and distinguishes from siblings like 'connect' by focusing solely on authentication flow.

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 guidance: it recommends adding the token to the server config for permanent connections, or pasting it for a session-only login. It also specifies when to call with no arguments (to obtain the link) and when to pass the token. This contrasts with alternatives and gives clear decision criteria.

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, but the description adds meaningful context about what the response contains (authenticated flag, pending array, connect_url) and how behavior changes based on provider connectivity. 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 two sentences, front-loaded with the core purpose, and each sentence adds distinct value—one describes the overall result and the other clarifies conditional output. No unnecessary 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?

For a zero-parameter read-only tool with comprehensive annotations, the description fully explains the tool's behavior in both possible states (all providers connected vs missing credentials). No output schema is needed given the simple JSON structure implied by the description. It is complete for its complexity.

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 0 parameters, so the baseline is 4. The description adds no parameter-specific semantics because none exist, but it does explain the output behavior in relation to different states, which is useful context for interpreting the response.

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, with specific detail about the authenticated flag and pending array. It distinguishes itself from siblings like 'authenticate' by focusing on status checking rather than initiating authentication.

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 happens under different conditions (all providers connected vs missing credentials), which implies when to use it (to check connection state). However, it does not explicitly mention when not to use it or contrast with alternative tools like 'authenticate', so 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?

With annotations already declaring readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds genuinely valuable behavioral context: the per-query cost model with prepaid credit, the disclosure that no confidential data is involved ('não é dado sigiloso'), and LGPD data-controller responsibilities. This goes well beyond the annotations and helps set expectations for a paid data-access 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 front-loaded with purpose and uses a compact 4-clause structure, but it contains redundancy ('fonte oficial' and 'fontes e órgãos oficiais' repeat the same idea; 'da plataforma' appears twice in one clause). The LGPD sentence is necessary legal context but could be tightened. Slightly disorganized but appropriately sized overall.

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 moderate complexity (4 flat string params, no output schema, no nesting) and strong annotation coverage, the description fills the important gaps: cost transparency, data-sensitivity boundaries, legal responsibility, and the credential model. It's missing minor elements like response-format hints and defaults for the optional param, but covers the material risks of a paid external query tool well.

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 coverage, the description bears full responsibility for parameter clarification but only provides one implicit clue: 'sem credenciais da plataforma' suggests login_email/login_senha authenticate to the external Enel service rather than the platform. No information is given about mes_ano's optionality or default behavior, the format expected for instalacao, or password handling, leaving the agent under-informed for 4 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 identifies a query operation ('consulta em fonte oficial') against a specific resource (Enel SP property management data), using a specific verb+resource format that sets it apart from meta-tool siblings like authenticate, report_bug, or show_version. It loses a point because the exact subject (electricity bills/installation data implied by 'contas' and 'instalacao') is only implicit in the name and never explicitly stated in the description itself.

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 useful contextual guidance about when this tool is appropriate: it's a pay-per-query service using prepaid credits, requires no platform credentials, and returns only publicly available citizen data from official sources. However, there's no explicit when-to-use vs. alternatives guidance, no exclusions, and no statement about when NOT to use this tool—usage context is implied rather than stated.

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 goes well beyond the sparse annotations (readOnlyHint false, openWorldHint true). It discloses that invoke runs tools even when not installed, returns connect/checkout links based on credentials/wallet, requires workspace owner/admin for writes, and prevents toolkit bloating. These behavioral traits are not 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 dense and information-rich, covering marketplace flow, prompt library, permissions, and edge cases without wasted words. However, it is a single run-on paragraph; breaking it into structured sections would improve readability. Still, every sentence 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?

Given the tool's high complexity (23 params, multiple action modes, no output schema), the description covers main workflows, permission requirements, conditional invoke behaviors, and the separate prompt library. It omits specific return formats and some parameter details, but is remarkably complete for the core actions.

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 has 23 parameters with 0% coverage. The description explains the meaning of key parameters through the action flow (action, mcp_id, tool_id, arguments, prompt_*), but leaves many parameters undefined (limit, query, immediate, request_*, cancel_reason, report_context, etc.). It partially compensates but is not exhaustive.

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 official mcp.ai marketplace covering discovery, description, invocation, and installation of MCPs/tools, plus a prompt library. It uses a specific verb+resource and enumerates the core flow (search → describe → invoke), distinguishing from sibling tools like report_bug, connect, and authenticate.

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 when-to-use guidance: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' It also contrasts list_tools ('what is callable right now') and explains conditional invoke behavior with connect/checkout links. This is clear decision support.

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 provide safety hints (readOnly=false, destructive=false, idempotent=true). The description adds useful context that the conversation array is needed for reproduction, but it does not disclose other behavioral details such as what happens after reporting (e.g., where the report goes, any side effects). No contradiction with 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 long, front-loaded with purpose, and every sentence adds value. There is no fluff or repetition of 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 simple 3-parameter tool with no output schema, the description covers the core purpose but omits details about expected input format for conversation, return values, or post-report behavior. It is adequate but leaves room for improvement.

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 0% description coverage, so the description must compensate. It explains the purpose of the 'conversation' parameter ('with recent messages for reproduction') but does not clarify the required 'message' parameter or the optional 'context' parameter, leaving most parameters underdocumented.

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 and resource, and none of the sibling tools overlap in function, making it easily distinguishable.

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 primary use case (reporting bugs or feedback) but does not explicitly contrast it with alternatives or state when not to use it. It does provide an actionable guideline to include the conversation array for reproduction, which adds some practical usage 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 provide the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false) and the description adds no context beyond the core purpose. It does not contradict annotations, but it also discloses no additional behavioral details such as output format, auth requirements, or potential side effects. With annotations present, a score of 3 is appropriate.

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 that states exactly what the tool does without any filler. It is appropriately sized and 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?

Given the tool's low complexity (no parameters, no output schema, simple informational purpose), the group is fully described by the one-sentence description. The annotations already provide the safety profile. There is no missing metadata or context that would materially affect usage.

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 per the scoring rules. The description adds nothing parameter-related, but there are no parameters to explain, and the schema is already 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 clearly states the tool's function with a specific verb ('Show') and a clear resource/customers ('the current version and adapter variants'). It is unambiguous, but it does not explicitly distinguish itself from sibling tools like toolkit_info, so it falls short of a 5.

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 tool should be used when you need version information, but it provides no explicit 'when-to-use' vs alternatives or exclusion criteria. Sibling tools (e.g., toolkit_info) might also seem relevant, and no guidance is given to differentiate, resulting in only a minimum viable score.

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, so the behavior is safe. The description adds the specific contents (installed MCPs, connection status, accounts, catalog tool counts) which goes beyond the annotations, making the tool's behavior transparent.

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?

One clear sentence that lists exactly what the tool returns. No unnecessary words.

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 informational tool with no parameters and no output schema, the description fully covers what the agent needs. It lists the specific elements returned, making it 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?

Tool has zero parameters, so the baseline is 4. Description doesn't need to explain parameters; it clearly states what the tool returns.

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 components (installed MCPs, connection status, accounts, catalog tools). This is specific and distinguishes it from sibling tools like authenticate or connect, which have different purposes.

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 makes the tool's purpose clear, so when to use it (to inspect toolkit state) is obvious. It doesn't explicitly mention alternatives or exclusions, but for a simple info query, it's sufficiently clear. There's no misleading guidance.

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