Prefeitura GO Uruaçu: Certidão Negativa de Débitos

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

Annotations already declare idempotentHint=true, and the description adds context about permanent vs session-only authentication, the non-expiring nature of the header approach, and the behavior of no-arg invocation returning a link. It doesn't contradict annotations and adds meaningful behavioral detail, though it omits return/error specifics.

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 with multiple clauses and instructions. While every sentence carries useful information, it is not front-loaded with a clear purpose statement and reads as a run-on. Better structure would improve scanability.

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?

There is no output schema, so the description should clarify return values. It implies that no args yields a link and token arg yields authentication, but it never explicitly states response format or success/failure. It is adequate for a simple auth tool but leaves 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?

The schema has only an optional 'token' parameter with zero coverage. The description compensates by explaining that the token is a JWT pasted by the user for session-only login, and that omitting it triggers a login-link response. This provides essential meaning beyond the raw 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 indicates the tool is for authenticating the MCP server for IDE agents, with specific instructions for browser login and token-based session. It distinguishes the tool's function well, though it lacks a succinct one-line purpose statement. The verb 'authenticate' and resource are implied through context.

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 usage guidance: either add a permanent header to config or use a session token. It explains when to call with no arguments (to get a login link) and when to include a token (after user pastes). This is comprehensive and leaves 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.

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is known. The description adds value by explaining the two output states: authenticated:true with empty pending[] versus connect_urls when credentials are missing, which is beyond what annotations alone provide.

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 concise and front-loaded sentences. The first gives the core result, and the second adds conditionals that entirely determine what a caller will see. No redundancy or filler.

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 parameterless, read-only status tool with good annotations, the description is nearly complete. It explains all major output states and clarifies what happens when credentials are missing. It could specify the exact shape or naming of URLs, but no meaningful gap remains.

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 there is no parameter burden for the description to carry. The schema itself needs no elaboration, and the description correctly focuses on the tool's observable behavior instead.

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 names a concrete resource: connection status and URLs. It also distinguishes itself by describing state-dependent outputs, making it clear this is a read-only status check rather than an authorization action like 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?

The description implies usage as a connection-status check via its condition behaviors, but it does not explicitly say when to use this tool over authenticate or other siblings. The context is clear enough, but exclusions and alternative selection guidance are absent.

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?

Adds substantial behavioral context beyond annotations: invoke works without installing, failure modes return connect/checkout links with retry instructions, writes require workspace owner/admin, search/describe flag installed_in_toolkit vs installed_in_workspace, and publish_prompt returns a login-free shareable link. No contradiction with annotations; readOnlyHint=false supports the documented write operations.

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 but well-organized: definition, core flow, key non-obvious behavior, action routing, permissions, and prompt library. Every sentence adds distinct information, and the most important 'KEY: invoke works even when the MCP is NOT installed' is front-loaded after the flow.

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 (14 actions, 23 params, no output schema), the description provides a strong overall picture: it covers permission requirements, billing/auth failure modes, permanent vs one-off installation, and prompt publishing. Minor gaps remain, such as the 'resume' action and 'immediate' parameter, and exact search/list return shapes are not spelled out.

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 compensates by explaining the action enum and core flow (search → describe → invoke), plus prompt actions and their relevant variables. However, many parameters remain unexplained (limit, immediate, tier_slug, cancel_reason, report_context, request_details, prompt_targets, etc.), leaving reliance on parameter names and defaults.

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 marketplace as the official mcp.ai catalog and execution layer, with specific verbs for discovery, description, and invocation. It differentiates its internal actions (search/describe/invoke/install) and covers the prompt library as a secondary distinct capability.

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 states when to use invoke vs install ('prefer invoke for a single/occasional use', install for permanent toolkit inclusion), lists discovery/search and list_tools for current callables, and gives specific routing for subscribe/cancel, request_mcp, report_bug, and prompt-library actions. No competing alternatives are left ambiguous.

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 important context: it is a paid service requiring prepaid credits, hosted by the platform with no platform credentials, and returns public data. This goes beyond annotations by disclosing the commercial/operational aspect and legal compliance context.

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 paragraph with concise sentences covering purpose, source, payment model, and data privacy. It front-loads the core purpose and includes necessary operational details without excessive length.

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 output schema and no parameter descriptions, the description covers the main use case, the data source, payment requirements, and legal context. It could be more explicit about parameter usage (e.g., requiring CPF or CNPJ) but overall provides adequate context for an agent to understand what the tool does and the conditions of 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?

Schema description coverage is 0%, so the description must compensate for parameter meanings. The description names the tool as consulting a certificate via CPF or CNPJ, which implies these are the identification numbers, but it does not explicitly explain that either cpf or cnpj must be provided or their roles. The schema shows two string properties with no descriptions, so this is a minimal compensation.

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 consults Certidão Negativa de Débitos (negative debt certificate) for the municipality of Uruaçu, GO, from an official source. It specifies the resource (certificate) and action (consult), and distinguishes it from siblings by naming the specific municipality and certificate type.

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 this is a paid consultation using platform credits, hosted by the platform, and that it accesses official public data. It implies this is for legitimate compliance purposes (LGPD) and notes the client is data controller, but does not explicitly state when to use it instead of other tools or when not to use it.

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 explains the action but does not disclose any side effects, permissions required, or what happens after reporting. The annotation indicates idempotentHint=true, which adds some transparency, but the description itself does not elaborate on consequences or return 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 concise, consisting of two clear sentences without superfluous details. It directly conveys the purpose and a key input requirement, making it well-structured 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 description lacks information about the expected output or what the tool returns after reporting. It also does not provide details on parameter formats or examples. Given the absence of an output schema, this leaves the agent uncertain about the tool's full behavior.

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 provides no descriptions for parameters, and the tool description only hints at the 'conversation' parameter. The 'message' and 'context' parameters are not explained, leaving their meaning and format ambiguous. This is a significant 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: reporting bugs, missing features, or sending feedback, and explicitly instructs to include the conversation array for reproduction. This distinguishes it from sibling tools like authenticate, connect, and 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 specific guidance on how to use the tool by instructing to include the conversation array with recent messages, which helps the agent understand the expected input. However, it does not explicitly mention when not to use it or alternatives, but the distinct purpose makes that implicit.

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 establish read-only, idempotent, and non-destructive behavior. The description adds the useful detail that it reports both 'MCP platform' and 'adapter versions', which goes beyond the structured hints. This is appropriate transparency for a simple zero-parameter inspection operation.

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. It front-loads the verb 'Show' and immediately states the expected output, making it easy to parse.

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 no parameters, no output schema, and clear read-only annotations, the description is complete. A user or agent can fully understand what the tool does without needing more context.

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 no parameters, and the schema covers 100% of the input requirements (none). According to the rubric, a zero-parameter tool gets a baseline of 4; the description effectively communicates that no input is needed to obtain the version 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 uses a clear, specific verb ('Show') and a precise object ('current MCP platform and adapter versions'). It fully distinguishes this tool from siblings like 'toolkit_info' by indicating it specifically returns version information.

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 no guidance on when to invoke this tool vs. alternatives, nor does it mention relevant contextual usage such as checking versions before troubleshooting. With siblings like 'toolkit_info' and 'connect', the absence of any when-to-use or when-not-to-use guidance leaves the agent to infer the 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 indicate read-only and idempotent behavior; the description reinforces this by describing a pure retrieval action without side effects. The description adds detail on what data is returned, which aligns with the annotations and provides 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 covers all essential points without redundancy. It is appropriately sized for the tool's simplicity and does not waste 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 stateless info tool with no parameters and no output schema, the description sufficiently conveys the tool's scope and output contents. It mentions all key aspects (state, MCPs, connections, accounts, catalog tools), leaving no significant gaps for typical 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?

The tool has no parameters, so there is nothing to describe. The description correctly omits any parameter details, and the input schema is empty, making the tool's expectations unambiguous.

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 ('Returns the current toolkit state') and enumerates the specific components (installed MCPs, connection status, accounts, and catalog tools). This is specific and distinguishes it from sibling tools like 'show_version' or '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?

While the description implies usage (to retrieve overall toolkit status), it does not explicitly state when to prefer this over alternatives. However, the purpose is self-evident and the sibling list provides context, making the intended use clear enough for most scenarios.

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