Prefeitura MG Itaúna: Certidão Negativa de Débitos

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

The annotations (readOnlyHint:false, idempotentHint:true, destructiveHint:false) are not contradicted. The description adds behavioral context about persistence (permanent vs session) and the no-args return of a link, which enriches the operational understanding 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 efficiently structured, starting with the core flow and then presenting the two usage modes. It is slightly verbose but every sentence adds value, and it avoids redundant 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 one optional parameter and no output schema, the description covers all necessary invocation details, including the persistent vs session distinction and the no-arg case. It is complete for an agent to use 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 schema coverage at 0%, the description fully defines the single 'token' parameter by specifying it expects a JWT and is optional, and explains the behavior when omitted. This compensates entirely for the lack of schema detail.

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 indicates the tool performs user authentication for IDE agents via browser login and token exchange. It distinguishes the tool by explaining the two authentication modes (permanent config-based and session-only token). While it doesn't explicitly say 'authenticate', the flow is 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 explicit usage instructions with two clear options: adding a config header for persistent access or pasting a token for session-only, plus the no-args case to get a login link. It doesn't mention alternatives among siblings, but the guidance is sufficient for agent invocation.

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. The description adds value by revealing behavior beyond annotations: it returns connect_url when credentials are missing and enumerates the authenticated/pending[] response shape—useful context for agents needing URLs or status. It doesn't mention rate limits or exact URL formats, but for a simple status tool, this is reasonably 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?

Two sentences, highly scannable. The description front-loads the core purpose, then specifies response behavior conditionally. Every phrase earns its place—no fluff, which is ideal for an agent parsing descriptions.

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 utility with strong annotations, the description fully captures what an agent needs: what it returns, the meaning of fields, and the conditional behavior when credentials are missing. No output schema exists, but the description covers the key return values, so nothing critical 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 tool has zero parameters, so there's no parameter semantics to add. The description correctly avoids inventing parameter details, and the schema coverage is 100% (trivially). A baseline of 4 is appropriate for zero-parameter tools since the description simply doesn't need to explain 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 returns connection status (authenticated, pending[]) and URLs, using specific returned fields. While the verb 'connect' is a noun here, the description clarifies it represents a status check. It differentiates itself from siblings by focusing on status and URLs, though it doesn't name a specific sibling.

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 this tool—to check connection status and get URLs—and contrasts with the authenticated vs. pending states, implying usage for connectivity checks. It doesn't explicitly name alternative tools but the sibling list suggests alternatives like 'authenticate' for initiating auth flows. The lack of explicit exclusion keeps it from 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?

Beyond the annotations, the description discloses critical behaviors: invoke runs MCPs even when not installed, returns connect/checkout links for auth/payment, writes require owner/admin, and install modifies the toolset. This adds substantial context that annotations don't cover, with 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 long but well-structured, leading with the core flow (search→describe→invoke), then highlighting key edge cases and differentiating between invoke/install, then listing other actions and the prompt library. It's front-loaded and informative, though somewhat verbose.

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 23 parameters, no output schema, and many sub-actions, the description covers the essential flow, credentials, billing, permissions, and prompt-specific behavior. It does not specify return formats for each action, but the coverage is adequate for such a complex 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 coverage is 0% and the description doesn't individually explain parameters like query, limit, mcp_id, or arguments. It does elaborate on the action enum and the overall flow, which gives context but leaves parameter-specific semantics to be inferred. The description partially compensates but not fully.

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 explicitly states the tool is the MCP marketplace, covering discovery, profiling, and execution of MCPs, plus a prompt library. It names specific actions (search, describe, invoke, install) and distinguishes from sibling tools like authenticate and report_bug, making the purpose unmistakable.

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 explicitly differentiates when to use invoke vs install ('prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT'), and also contrasts with list_tools, subscribe/cancel, and the prompt library actions. It provides clear decision 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?

Transparently states that it is a query (read-only), not handling confidential data, and mentions LGPD compliance. Combined with annotations (readOnly, idempotent), it fully discloses behavior.

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 repetitive (e.g., 'consulta em fonte oficial' and 'hospedado pela plataforma' are echoed), but it remains concise overall and is structured as a single coherent paragraph.

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?

Provides useful context such as payment method, data origin, and LGPD compliance, but does not explain the expected output or the relationship between the two parameters, leaving some ambiguity.

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 lists 'cpf' and 'cnpj' as strings, but there is no description or guidance on whether one is required, if both can be used, or constraints. The parameter names are self-explanatory for Brazilian tax IDs, but the lack of semantics beyond that is a gap.

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 consult a negative debt certificate (Certidão Negativa de Débitos) for the municipality of Itaúna, MG, via an official source.

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 context on usage: hosted on the platform, requires prepaid credits, no credentials, and clarifies that it uses official Brazilian sources. However, it does not explicitly state when to use this tool versus alternatives.

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 readOnlyHint=false, idempotentHint=true, and destructiveHint=false, which already convey the operation type. The description adds useful behavioral context by instructing to include the conversation array for reproduction, which is not evident from annotations alone.

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 that conveys the tool's purpose and the key parameter requirement without any wasteful words. It is concise and well-structured.

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 reporting tool with no nested objects or output schema, the description adequately covers the main action and important parameter guidance. It does not describe return values, but for a one-way reporting action, this is not a significant omission.

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%, so the description must compensate. It explains the purpose of the 'conversation' parameter ('recent messages for reproduction') and implicitly clarifies the 'message' parameter as the bug/feature/feedback content. However, the 'context' parameter is unexplained, leaving a gap in full 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 clearly states the tool's purpose with a specific verb ('Report') and resource ('bug, missing feature, or send feedback'). It distinguishes itself from sibling tools like authenticate, connect, and show_version, which serve entirely different functions.

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 clear context on when to use the tool: to report a bug, missing feature, or send feedback. It does not explicitly exclude any scenarios or name alternatives, but sibling tools do not overlap with this function, so the 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 and idempotentHint, and destructiveHint is false. The description adds no additional behavioral context beyond the purpose, but this is acceptable for a simple read-only version query; it does not contradict 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 short sentence with no wasted words, directly stating the function. It is 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?

For a simple tool with no parameters, clear annotations, and no output schema, the description is fully sufficient. It tells exactly what the tool does without needing additional details.

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 an empty schema with 100% coverage, so the description needs to explain nothing. Per the rubric, this is the baseline score of 4 for tools with no 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 verb 'show' and the resource 'current MCP platform and adapter versions', which is specific and distinguishes it from sibling tools like authenticate or connect that 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?

No explicit guidance on when to use this tool versus alternatives; it simply states what it does, leaving the usage context implied. There is no mention of when not to use it or which sibling might be a better choice for related queries.

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, establishing a safe, non-mutating operation. The description adds valuable behavioral context by specifying exactly what state it reports (installed MCPs, connection status, accounts, catalog tool counts), thus going 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 a single, well-structured sentence that front-loads the main action ('Returns the current toolkit state') and then enumerates the specific data elements. Every word adds value, with 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?

Given the tool's low complexity (no params, no output schema), the description fully covers what the agent needs to know: what the tool does and what information it provides. The four listed components comprehensively define the expected return content, making the description complete for practical 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 tool has zero parameters, so the description carries no burden of parameter explanation. According to the rubric, a baseline of 4 applies when there are no params, and the description correctly avoids inventing unnecessary detail about inputs.

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 identifies the resource as 'toolkit state', enumerating four distinct components (installed MCPs, connection status, accounts, catalog tool counts). This specificity clearly distinguishes it from sibling tools like authenticate 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 implicitly communicates its use case as a read-only informational query about the toolkit's state. It does not explicitly suggest alternatives or exclusions, but the context is clear—this is the go-to tool when an agent needs an overview of the current environment. Since no parameters exist, there's no ambiguity about invocation.

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