SEFAZ SC: Dívida Ativa

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

Annotations already declare readOnlyHint=false, so the mutation aspect is known. The description adds useful behavioral details: session-only login vs permanent token, and that calling with no args returns a link. It clarifies the side effects (login state change) without contradicting any annotation.

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 run-on, mixing branding, instructions, and multiple alternatives in a single long second sentence. While it front-loads the purpose, it could be formatted more clearly for readability.

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 tool with one optional parameter and no output schema, the description covers all relevant details: the two login modes, how to invoke, and the role of the token. No missing critical context for an agent to use 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?

Schema coverage is 0%, but the description explicitly explains the 'token' parameter as a JWT and clarifies that it is optional (no args allowed). It provides usage examples and distinguishes between session and permanent modes, adding significant meaning beyond 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 states the tool's purpose: authenticate to MCP.AI by logging in in the browser and obtaining an access token. It explicitly mentions the target audience (IDE agents like Cursor) and distinguishes itself from sibling tools like 'connect' and 'marketplace' by focusing 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?

Explicitly explains when to use this tool and the two invocation modes: for permanent connections (add token to config) vs session-only (pass token as argument or get link). It also notes the alternative of storing the token in config, providing clear situational 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 readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is established. The description adds behavioral detail about the two output states (authenticated:true with empty pending[], or connect_url and per-install URLs) without contradicting annotations. It does not cover partial connection states, but the added context is meaningful beyond 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 concise sentences, front-loaded with the core purpose ('Returns connection status and URLs') and then expands with two specific conditional outcomes. Every sentence adds value; there is no fluff 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 zero-parameter tool with clear annotations and an output schema absent, the description covers the primary expected behavior in two main scenarios. It leaves some ambiguity about partial provider states or the structure of pending[], but overall it is sufficient for an agent to understand the tool's role and typical results. An explicit mention of the read-only nature would be redundant given annotations.

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 schema coverage is 100% (empty schema), so the description need not explain parameters. It correctly does not mention parameters, and the baseline for no parameters is 4, which is appropriate here.

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 it returns connection status and URLs, using a specific verb ('returns') and resource ('connection status'). It distinguishes from sibling tools like authenticate and show_version by focusing on connection state, not actions or version info. The annotation title 'Connection Status' reinforces this purpose.

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 for checking connection status and describes two key scenarios (all providers connected vs missing credentials), giving context on when to expect certain outputs. However, it does not explicitly mention when not to use it or direct users to alternatives like authenticate for missing credentials. The clear functional role provides adequate 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?

Describes key non-obvious traits: invoke not requiring MCP installation, the one-off execution without bloat, credential/checkout link flow, owner/admin write prerequisite, and the prompt library existing for prompt text rather than MCPs. Annotations are consistent; no contradictions.

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?

Lengthy but well-organized by flow and sections. Every sentence conveys meaningful context (route, credential handling, billing, prompt library), though some content could be split into subsections to aid scanning.

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 complex multi-action tool, the description robustly covers the core flow, the install/invoke distinction, credential and payment behavior, admin requirements, and the separate prompt-library feature. The lack of an output schema is compensated by the description's completeness.

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% with 23 parameters, so the description must compensate. The prose explains high-level actions but does not map them to parameters like action, query, mcp_id, tool_id, arguments, or prompt_vars. Parameter names are left to be documented implicitly by flow logic.

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 marketplace/main catalog and the core actions (search, describe, install, invoke, subscribe). It distinguishes from siblings by naming the complete flow and scope.

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?

Provides explicit when-to-use, when-not-to-use, and alternatives: prefer invoke for one-off use, install only for permanent toolkit presence, search when discovering by intent, and request_mcp when nothing fits. Also distinguishes list_tools/describe/install/uninstall/subscribe/cancel.

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 disclose what happens after reporting (e.g., whether a ticket is created, how data is handled). Although annotations indicate idempotency and non-destructive behavior, the description itself adds no transparency about side effects or expected actions. The mention of 'conversation array' contradicts the schema's string type, which could mislead users.

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 extremely concise, with only two sentences, and it directly conveys the core action and a key requirement. There is no superfluous content, making it easy to grasp.

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 sparse schema (no parameter descriptions, no output schema), the description fails to provide sufficient context. It omits details about the expected format of 'message', what 'context' represents, and the return value or potential errors, leaving the user with an incomplete understanding.

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 only addresses the 'conversation' parameter (incorrectly calling it an array), while leaving 'context' and 'message' undefined. Schema coverage is 0%, and the inaccurate type information further diminishes the semantic value for 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 the tool's purpose: reporting a bug, missing feature, or sending feedback. The verb 'report' is specific, and the resource is the bug/feedback context, which is distinct from the sibling tools like authenticate or 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 an instruction on what to include (the conversation array) but does not specify when to use this tool versus alternatives, nor does it give any conditions or best practices for issuing a bug report. It lacks explicit guidance on selection 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?

The description adds valuable context beyond annotations: it explicitly states the tool is pay-per-query, requires no platform credentials, and that the data is non-confidential. This aligns with the readOnlyHint and idempotentHint annotations and adds cost and data-privacy constraints.

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 dense paragraph mixing purpose, hosting, billing, and legal compliance. It is not overly long but lacks clear structure; the legal LGPD paragraph could be separated from functional details. All sentences carry some information, but efficiency could be improved.

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 query tool with no output schema and two undocumented optional parameters, the description is incomplete. It does not mention what data is returned, how to interpret results, or that at least one parameter is likely needed. The legal/billing context is present, but the core functional context is missing.

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, and the description does not explain the parameters (cnpj, renavam) at all. The tool name hints at taxpayer/vehicle identification, but the description fails to clarify which parameter to use or how they relate to the query.

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 consults 'Dívida Ativa' from SEFAZ SC via official sources, but does not specify the exact operation or the role of the parameters (cnpj, renavam). It distinguishes from unrelated siblings but lacks specificity about what the tool returns or how it is invoked.

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?

No guidance is provided on when to use this tool vs alternatives. It does not mention prerequisites, required parameters, or typical use cases. The description focuses on legal and billing aspects rather than 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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds minimal context ('current' implies a live retrieval) but does not disclose any additional behaviors like response format or potential errors. It is consistent with annotations, so no contradiction, but the added value is limited.

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 with no fluff. It is front-loaded with the verb and directly states the purpose. Every word adds value, achieving maximum 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?

For a simple, parameterless, read-only tool with no output schema, the description is complete. It tells the user exactly what the tool does. The annotations cover safety, and the schema has no parameters to document. No additional context is necessary for an agent to invoke this 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?

With zero parameters, the schema is fully described (coverage 100%) and there is nothing for the description to clarify. Per the rubric, 0 params earns a baseline of 4, and the description doesn't need to add parameter details. It adds nothing beyond what's absent, which is fine.

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 resource ('current MCP platform and adapter versions'). It distinguishes itself from siblings like 'toolkit_info' by focusing on version details, though it doesn't explicitly compare.

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?

No guidance is provided on when to use this tool versus alternatives. The description is purely declarative with no mention of preferred contexts, exclusions, or related tools. For a simple version query this might be acceptable, but by the rubric it lacks explicit usage direction.

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 destructiveHint=false, covering safety. The description adds specific behavioral details about what the tool returns (installed MCPs, connection status, accounts, catalog tool counts), which is useful beyond annotations. No contradictions.

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 front-loads the purpose ('Returns the current toolkit state') and then lists specific contents. There is no wasted or redundant wording.

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, no output schema, and simple informational intent, the description fully covers what it does and what it returns. It is complete for an agent to invoke it confidently.

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 parametersable, so schema coverage is 100% by default. The description fully explains what the tool returns, compensating for any possible ambiguity about the output. Baseline 4 is raised to 5 because it gives a detailed breakdown of the returned information.

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, connected accounts, catalog tool counts). It uses a specific verb 'Returns' and a clear resource 'toolkit state', and distinguishes from siblings like 'connect' and 'authenticate' by focusing on state retrieval.

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 for checking toolkit state but does not explicitly state when to use it versus alternative tools. It provides no exclusions or alternative tool names, so the guidance is adequate but not explicit.

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