SEFAZ PE: Dívida Ativa

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

The description discloses the persistent vs. session-only nature of authentication: 'permanent, non-expiring connection' vs 'session-only login'. It also mentions the browser interaction. Although annotations indicate non-read-only and idempotent, the description adds clarity about the side effects, such as modifying config for permanent access. It does not contradict 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 somewhat verbose and meandering. It starts with context ('MCP.AI for IDE agents (Cursor, etc.)') which may be unnecessary, and the sentence structure is run-on: 'Best: add it ... Or paste it here ...' The content is clear but could be organized more concisely, e.g., with bullet points. However, it still conveys all necessary 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?

Given the minimal schema and annotations, the description provides sufficient context for an agent to understand the tool's purpose and usage. It explains both call variations, the token format, and the difference between permanent and session login. It lacks details like error handling or post-auth behavior, but those are not essential for this tool. Overall, it is complete for the intended use.

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 only parameter, 'token', is fully explained. The description specifies it is a JWT ('<jwt>') and explains the behavior when omitted: 'with no args to get the link'. This adds meaning beyond the bare schema, which lacks any description.

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: to authenticate with the server. It explicitly describes the authentication flow: 'log in in the browser, copy the access token' and offers two methods for establishing a connection. It is distinct from sibling tools, which are unrelated (e.g., 'connect', 'marketplace').

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 clear guidance on when to use each mode: 'Best: add it to this server's config as a header ... for a permanent, non-expiring connection' versus 'paste it here for a session-only login'. It also explains the exact call patterns: 'call with { token } after the user pastes, or with no args to get the link'. This effectively tells the agent when and how to invoke the tool, though it could be more explicit about prerequisites.

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 context about return behavior (authenticated, pending, connect_url) and conditional logic, which enhances transparency 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 main purpose, and every sentence adds value. It explains the core functionality and two key conditional outcomes without any fluff or redundancy. It is appropriately concise.

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, empty schema) and the annotations covering safety, the description is complete. It explains the return values (authenticated, pending, connect_url) and the conditions under which they appear, which fully satisfies what an agent needs to know. No output schema exists, so the description's coverage of return behavior is crucial and well done.

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 0 parameters and schema coverage is 100% (empty schema). Per the rubric, a 0-parameter tool gets a baseline of 4. The description correctly explains the return values and does not need to elaborate on parameters. There is nothing to add beyond what the schema already implies.

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, specifying exact fields (authenticated, pending, connect_url) and conditional behavior. This distinguishes it from siblings like authenticate (which likely performs authentication) and show_version (which returns version info). The purpose is specific 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 implies when to use the tool (to check connection status) but does not explicitly mention alternatives or when not to use it. It provides conditional scenarios (when all providers connected vs when credentials missing) that help infer usage, but there is no explicit guidance on choosing this tool over siblings.

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 that are all near-default values (readOnly=false, destructive=false), the description carries the full transparency burden and delivers: it discloses that writes require workspace owner/admin, that invoke runs tools 'pontualmente' without permanent installation, and that credential/payment gaps return connect or checkout links requiring user action before retry. No contradiction exists — the write-permission statements are consistent with readOnlyHint=false.

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 unbroken paragraph — a dense wall of text with no section breaks or bullet points. While nearly every sentence carries some information, the lack of structure makes the middle sections (billing, install vs invoke, prompt library) blur together and burdens the agent's parsing. It front-loads purpose well but is neither concise nor well-organized.

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 (23 params, 14 actions, billing, installs, prompt library) with no output schema and minimal annotations, the description covers the core discovery and run flows thoroughly, including auth requirements and retry behavior. But it leaves gaps: no return-value descriptions, no cancel/resume flow details, and unexplained immediate/tier_slug semantics. It is adequate for the main paths but not complete for a tool of this magnitude.

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 and 23 parameters, the description faces a heavy burden and compensates only partially. It explains the action enum values, the tool_id selection flow, arguments for invoke, prompt_vars variable filling, and prompt_slug sharing links. However, many parameters remain entirely unexplained — cancel_reason, cancel_comment, immediate, tier_slug, conversation, request_name, request_details, prompt_body, prompt_targets, report_context — leaving real gaps.

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 opening sentence identifies this as 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them', which is a specific and accurate purpose. It clearly explains the search→describe→invoke core flow and differentiates this catalog tool from siblings like connect and authenticate. However, the scope is sprawling (14 actions spanning billing, installs, and a prompt library), making the tool's verb diffuse despite the strong opening.

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 strong internal usage direction: the explicit core flow (search→describe→invoke), the clear 'prefer invoke for one-off, use install only for permanent' heuristic, and the retry-after-connect/checkout-link logic. It also positions list_tools for what is callable right now and distinguishes the prompt library actions. It lacks explicit when-not-to-use versus sibling tools, but the internal action guidance is genuinely helpful.

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 indicate idempotentHint: truecluster, but the description doesn't conflict. It adds a useful instruction about including conversation data for reproduction, which gives behavioral context. However, it doesn't disclose any side effects or authorization needs beyond that.

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 directly states the tool's purpose and one key usage instruction (include conversation). It's not overly verbose, but lacks structured parameter explanation.

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 gives purpose and reproduction guidance, but doesn't specify when to use vs. alternatives or any limitations. With annotations stating idempotent, it's clear it's not destructive, but could benefit from more context on expected outcomes.

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 'conversation' parameter's purpose but not 'context'. The schema has no descriptions, and the description calls 'conversation' an array while schema says string, which is slightly ambiguous. 'message' is self-explanatory. 'context' is vague.

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 names specific resources (bug, feature, feedback) and the action (report/send), which clearly differentiates it from sibling tools like 'authenticate' or '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 context on when to use it (for reporting issues) and explicitly instructs to include the conversation array for reproduction. However, it does not mention situations where it should not be used or how it compares to alternatives, but the context 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?

Beyond the annotations (read-only, idempotent, non-destructive), the description adds valuable behavioral details: prepaid payment per query, no platform credentials required, data sourced from official Brazilian entities, and LGPD compliance responsibilities. This significantly enhances the agent's understanding without contradicting 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 paragraph that opens with the core purpose, then adds payment, data source, and legal context. Every sentence earns its place; there is no redundancy or 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 simple read-only query tool with two optional self-explanatory params and no output schema, the description covers purpose, payment model, data authenticity, and legal obligations. It lacks explicit return-value details, but given the tool's simplicity and abundant context, it is nearly 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%, and the description does not explicitly explain the 'cpf' and 'raiz_cnpj' parameters. However, the parameter names are self-descriptive, and the tool's purpose implies they are identifiers for the active debt query. The description adds minimal semantic value beyond the schema, but the names provide enough hint.

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 queries active debt (Dívida Ativa) from SEFAZ PE in an official source. The verb 'consultar' and specific resource distinguish it from the generic sibling tools (authenticate, connect, etc.), making its 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 clear context: it's a paid, credential-free query tool for official Brazilian data. It does not explicitly name alternatives or state when not to use it, but the sibling tools are unrelated, so the usage context is sufficient. No explicit exclusions needed.

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 does not add much beyond the annotations (readOnly, idempotent, non-destructive). It is consistent with the annotations but does not provide additional context like return format or side effects.

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 directly states the tool's purpose without unnecessary detail.

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 adequate for a simple version check, but it does not specify what exactly is returned (e.g., format or fields). Given no output schema, a bit more detail could improve completeness, but it is not critical.

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 no parameters, and the schema coverage is effectively 100% (empty). The description does not need to explain parameters, so a baseline score of 3 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?

The description clearly states the tool's function: showing current MCP platform and adapter versions. It is specific and distinguishes from sibling tools like authenticate or 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?

The use case is obvious (checking versions), but it does not explicitly mention when to prefer this over alternatives. Still, the purpose is clear enough for typical usage.

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, destructiveHint=false, and idempotentHint=true, so the agent knows this is a safe read operation. The description adds useful specificity about what 'state' means (installed MCPs, connection status, accounts, catalog tool counts) beyond what annotations convey. However, it doesn't quite hit a 4 because it doesn't disclose behavioral specifics like whether accounts are returned with sensitive fields (tokens, emails) or whether the catalog count includes only active or also failed MCPs—minor gaps that a 4 would want addressed.

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 sentence, under 20 words, front-loads the verb ('Returns'), and uses colons and commas for scannable structure. Every word earns its place. This is an exemplary level of conciseness.

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 has no input params, no output schema, and is a simple state inspection with strong annotations. The description fully covers what the agent needs: a list of the four pieces of state information returned. There's no missing context—the tool is simple and the description correctly matches that complexity 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?

The tool takes 0 parameters, so parameter semantics are trivially satisfied. The description's value comes from telling the agent what the response will contain (state details), which is exactly what the agent needs to know to use this info. Baseline 4 is appropriate for a 0-parameter tool with solid descriptive coverage.

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 resource ('current toolkit state'), and explicitly enumerates the contents of that state: installed MCPs, connection status, associated accounts, and catalog tool counts. This is both precise and distinguishes it from sibling tools like 'connect' and 'authenticate', which are action-oriented rather than state-inspection-oriented.

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 it clear this is a status/introspection tool (as opposed to tools that connect, authenticate, or act), so the agent can infer when to invoke it. However, it does not explicitly name alternatives or exclusions—e.g., it doesn't say 'use authenticate before connecting'—though for a stateless info tool that's less critical. The clear state-inspection framing earns a 4 rather than a 5 for lack of explicit 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.