Neoenergia (Elektro): Download + OCR

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

The description adds meaningful behavior beyond annotations: it explains the permanent vs session-only distinction, the no-args link behavior, and the token-pasting flow for session login. It does not contradict the annotations and gives useful context about how authentication state is established.

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 compact and uses 'Best:'/'Or:' to structure the main decision. It earns its length, but the opening sentence is slightly convoluted and would be clearer if it directly stated what the tool returns.

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 one-parameter authentication tool, the description covers the main flows, session vs permanent setup, and how to request the login link. It does not specify the exact output shape or success/failure behavior, and it doesn't mention how 'authenticate' relates to the sibling 'connect' tool, but these are minor for this simple 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 input schema only says 'token: string' with 0% coverage, so the description carries the full burden. It does so effectively: token is the user-pasted JWT, and omitting it triggers the no-args login-link behavior. This provides exactly the semantics the model needs.

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 explains the auth flow: calling with no args returns an MCP.AI login link, and calling with the token supplies a pasted JWT for session-only login. It is specific enough about what the tool does, though it does not explicitly differentiate itself from the sibling tool '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?

It provides explicit usage modes: use the server config header for a permanent connection, or call the tool with the token for a session-only login, or call with no args to get the link. It misses explicit comparison with 'connect' and could more clearly separate user-configuration steps from tool-call behavior.

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 indicating read-only and idempotent, the description explains the output scenarios: it returns authenticated true with empty pending when all connected, and connect_url when credentials are missing. This provides additional behavioral insight.

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, consisting of two sentences that convey the necessary information without redundancy.

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 the main outcomes of the tool, including the happy path and the missing credentials case. While it doesn't enumerate all possible edge cases, it provides sufficient context for a connection status 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 input schema has no parameters, so the description cannot add parameter-specific meaning. Since schema coverage is complete, the baseline score of 3 applies.

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', which is a specific verb and resource. It differentiates from sibling tools like 'authenticate' and 'show_version' by focusing on connection status.

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 usage by describing what happens when all providers are connected versus when credentials are missing, which guides when to use this tool. However, it does not explicitly compare with alternative tools, so it's not fully 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, destructiveHint=false. The description adds context about LGPD compliance, that data is not confidential, that clients are data controllers, and that prepaid credits are used. It does not disclose rate limits, failure modes, or what happens on invalid credentials. Credits the annotations with reducing the need for behavioral disclosure, but the LGPD note is a differentiator.

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 run-on sentence with embedded legal/pricing information, which fronts the core purpose but meanders into LGPD details. It is not excessively long, but punctuation issues (e.g., missing space after parenthesis, awkward clause 'não é dado sigiloso.') make it slightly less readable. No bullet points or structured formatting.

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 0% schema coverage, the description needed to cover parameter formats, return values, and expected behavior. It only addresses LGPD and payment, leaving critical operational details undocumented. The tool's moderate complexity (string parameters only, no nested objects) means a more thorough description could have covered these gaps.

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?

Params are 7 with 0% schema description coverage, and the description provides zero parameter explanations. Parameter names (uc, uf, mes_ano, login_cpf, login_cnpj, login_senha, acesso_imobiliaria) are visible but formats (e.g., date format 'MM/YYYY' for mes_ano, whether uc is a string of digits) are undocumented. The description's LGPD focus does not compensate for the lack of parameter-level guidance.

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 performs 'Download + OCR' for 'Neoenergia (Elektro)' utility bills with 'consulta em fonte oficial'. This is specific about the resource (Neoenergia) and action (download/OCR/consult), distinguishing it from generic sibling tools. No explicit verb like 'returns' but 'consulta' implies retrieval. Minor ambiguity: 'Download + OCR' is a fragment, not a full sentence.

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 context about when to use this tool: for Neoenergia utility bill queries, hosted on the platform without platform credentials, with pay-per-query pricing. However, it does not explicitly state when NOT to use it or name alternative tools. No comparisons to siblings or other Neoenergia-specific tools are provided.

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 key behaviors beyond annotations: invoke runs a tool one-off even when the MCP is not installed, install makes an MCP permanent, writes require workspace owner/admin, and invoke returns connect or checkout links when credentials or payment are needed. It also reveals that prompt publish links open without login. There is 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?

Although long, the description is dense and well-structured: it front-loads the core purpose, then walks through the primary flow, key caveats, permission requirements, billing/auth links, and the separate prompt library. Every sentence adds meaningful operational guidance, and there is no filler or repetition.

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 14 actions, 23 parameters, and no output schema, the description is unusually complete: it covers the main search/describe/invoke workflow, install-vs-invoke distinction, billing/auth edge cases, permission requirements, and prompt-library flow. Gaps remain, such as the 'resume' action being absent from the description and no explicit action-to-parameter mapping, so it is not fully exhaustive.

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 23 parameters and 0% schema description coverage, the description carries a heavy burden and largely succeeds. It explains the role of action values, mcp_id, tool_id, arguments, and prompt-related fields (prompt_slug, prompt_vars, prompt_title, prompt_body). However, some parameters remain unexplained or underspecified, such as immediate, tier_slug, resume, conversation, and prompt_targets, which prevents a perfect score.

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 — the in-platform catalog of every MCP/tool, AND the way to run them.' It enumerates specific supported actions (search, describe, invoke, install, subscribe, prompt library) and distinguishes itself from siblings by explaining how list_tools and report_bug fit within or alongside it.

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: 'Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile... → invoke RUNS that tool.' It also gives clear when-to-use alternatives: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use,' and explains how to handle connect/checkout links and retry. It clearly separates MCP actions from prompt-library 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 provide safety traits (readOnlyHint=false, idempotentHint=true, destructiveHint=false). The description adds the requirement to include the conversation array but doesn't disclose additional behavioral traits such as side effects or response behavior. 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 a single sentence that front-loads purpose and follows with usage guidance. 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?

The tool is simple, but the description omits any mention of what happens after a report is submitted or how the response is handled. Given the lack of an output schema, this is a gap, though the annotations cover safety. It's adequate for a straightforward 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?

Schema description coverage is 0%. The description highlights the conversation parameter for reproduction, but doesn't clarify the required 'message' parameter or the optional 'context' parameter, leaving the agent to infer their meaning. This is insufficient for a tool with one required parameter.

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, and feedback. It effectively distinguishes from siblings like show_version and toolkit_info, which are informational tools.

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 clear context for when to use (reporting issues or sending feedback) and includes an explicit instruction to include the conversation array for reproduction. However, it doesn't explicitly state exclusions or alternative tools.

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, covering safety. The description adds that it shows 'current' versions, providing some context (no caching implied). It does not disclose output format or other behaviors, but given the simple nature and annotations, a 3 is fair.

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?

Single concise sentence that directly states the purpose without any filler. Perfectly front-loaded and efficient.

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 extremely simple with no parameters, no output schema, and rich annotations. The description fully covers what the tool does, and given the trivial context, it is 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 baseline is 4. The description adds no parameter info, but none is needed since the schema already documents zero 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?

Description clearly states the verb 'Show' and the resource 'current MCP platform and adapter versions', which precisely conveys the tool's function. It is distinct from siblings like connect or authenticate, as none of them relate to version display.

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 (to check versions) but provides no explicit exclusions or alternatives. Since the tool is trivial and sibling tools are unrelated, the implied usage is acceptable but not explicitly guided.

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, providing the safety profile. The description adds value by listing the exact returned data (installed MCPs, connection status, connected accounts, catalog tool counts), giving agents a clear picture of what to expect 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 action ('Returns the current toolkit state') and then provides a concise, informative list of contained data. No wasteful 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?

Given the tool's simplicity (no parameters, no required auth context), the description is complete. It enumerates the output contents and does not leave key aspects unexplained, even without an output schema.

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 of 4 applies. The description correctly omits any parameter explanation, and the schema is fully covered by having no properties.

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') and clearly defines the resource ('current toolkit state') with detailed enumeration of its contents: installed MCPs, connection status, accounts, and catalog tool counts. This distinguishes it from sibling tools like show_version or connect, which serve 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 implies clear usage: call this to inspect the toolkit's current state. It doesn't explicitly contrast with alternatives, but the context is unambiguous, and no exclusions are needed for such a straightforward info tool.

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