Prefeitura GO Itumbiara: Certidão Negativa de Débitos

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

Annotations indicate idempotentHint=true and destructiveHint=false, but the description adds meaningful context about side effects: it mentions that this call initiates a browser login flow, and that providing a token yields a non-expiring connection if configured. It also notes the alternative of session-only login, which implies temporary state. This goes beyond the annotations by explaining the user interaction required and the permanence implications, though it doesn't detail any side effects on existing sessions.

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 front-loaded, starting with the primary purpose and audience, then quickly covering the two usage modes and the no-args fallback. Each sentence contributes useful information without redundancy. It's a single paragraph with clear structure, maximizing information density without being 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?

For a tool with a single optional parameter and no output schema, the description is complete. It explains the workflow, the two login approaches, and the behavior with and without arguments. Given the tool's simplicity and the rich annotations (idempotent, non-destructive), the description covers all necessary aspects for an agent to use it effectively.

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?

Despite 0% schema description coverage, the description effectively documents the token parameter: it explains that the token should be a JWT pasted by the user, and that omitting it triggers the login link. This adds meaning beyond the bare 'token' property in the schema. It could be more explicit about the token format or expiration, but it covers the essential 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: authenticating an IDE agent with a browser login and token exchange. It specifies the resource (MCP server) and the action (authenticate), and distinguishes between two usage modes (permanent config vs. session-only). While sibling tools like 'connect' may overlap, the description's explicit focus on token acquisition and login makes 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 explicit guidance on when and how to use the tool: it instructs the agent to have the user log in in the browser, copy the access token, and then either add it to the server's config for a permanent connection or paste it as a parameter for a session-only login. It also explains the behavior when no args are provided (returns the login link). This is actionable and leaves no ambiguity about 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 mark readOnly and idempotent; the description adds conditional response fields (authenticated, pending, connect_url) and the behavior when credentials are missing. Could be slightly more complete on partial connection states, but adds meaningful context 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?

Two sentences with the main action first, followed by clear condition branches. No filler or redundant 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?

For a zero-parameter, read-only status tool, it covers the main output branches and includes return fields since no output schema exists. It does not address partial connection states or explicitly tie to authenticate, leaving a minor gap.

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 is empty, so the description appropriately avoids inventing parameter details. The baseline of 4 applies for zero-parameter tools.

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?

Clearly states it returns connection status and URLs, adding conditional response details. Differentiates from sibling authenticate by describing a read-only status check, not an authentication action.

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?

Implies when to call (to check whether providers are connected and obtain URLs), but does not explicitly contrast with siblings like authenticate or state when not to use it. The conditional branches provide usable context but no explicit alternative 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?

The description discloses important behavioral traits beyond annotations: invoke runs one-off even when not installed, requires connect/checkout links when credentials or payment are missing, writes require workspace owner/admin, and prompt links open without login. Minor gaps remain around actions like resume and uninstall side-effects, but the added context is substantial.

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 information-dense, covering the full action taxonomy, the core workflow, billing/auth edge cases, and the prompt library in a single block. Every sentence earns its place, though light structuring (separating prompt-library from MCP actions) 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?

Given the tool's high complexity, 14 actions, 23 parameters, and no output schema, the description provides a surprisingly complete mental model: search/discover → describe → invoke, permanent vs one-off installs, auth/billing behaviors, owner/admin permissions, and prompt-library flows. It stops short of documenting every action (notably 'resume') and some parameter semantics, but is adequate for selection and basic invocation.

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 description coverage at 0%, the description must compensate for the 23 parameters, and it does explain core ones like action, query, mcp_id, tool_id, arguments, prompt_slug, and prompt_vars. However, many parameters remain unexplained (limit, immediate, tier_slug, cancel_reason, report_context, conversation, request_details, etc.), so the mapping from intent to inputs is incomplete.

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, covering both catalog discovery and execution of MCPs/tools. It explicitly lays out the core flow (search → describe → invoke) and distinguishes this from prompt-library functionality, making the tool's purpose unmistakable and distinct from siblings.

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 explicit guidance on when to use which action: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT', 'request_mcp asks us to build a NEW MCP when nothing fits', and describes subscribe/cancel/report_bug roles. This goes beyond vague context and provides actionable 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?

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context beyond these: payment via prepaid credit, interaction with official Brazilian sources, non-confidential data, and LGPD data controller responsibilities. No contradictions 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 block of text containing multiple clauses. It includes essential purpose at the start but then mixes in legal and payment details. It is not overly long, but it could be better structured with the purpose first and operational details separated. Some content, like LGPD specifics, may be tangential for tool invocation.

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 no output schema and two undocumented parameters, the description is incomplete. It does not explain what the response contains, how the parameters relate to the query, or any prerequisites (e.g., needing a CPF or CNPJ). For a data query tool, this is insufficient for an agent to understand expected inputs and outputs.

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%, so the description must explain the parameters (cpf and cnpj). It does not. There is no mention of what these fields are, that at least one is typically required, or any formatting instructions. This is a critical gap for an agent to invoke the tool correctly.

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 what the tool does: it consults a Certidão Negativa de Débitos (negative debt certificate) from the official source of Prefeitura GO Itumbiara. The verb 'consultar' and the resource are explicit, and it is easily distinguished from the generic 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 context about usage conditions (hosted by platform, prepaid credit, no credentials, LGPD compliance) but does not explicitly state when to use this tool versus alternatives. Since the siblings are unrelated system tools, the intended use case is implied by the specific municipality and certificate type, but no explicit exclusions are given.

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 provide minimal safety hints (readOnlyHint false, idempotentHint true, destructiveHint false). The description only instructs to include the conversation array for reproduction but does not disclose side effects, whether the report is saved, or any rate limits or authentication requirements. Given the low annotation coverage, the description falls short in revealing behavioral traits.

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: two sentences, first stating purpose, second providing a key usage instruction. No redundancy or filler—every word earns its place.

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 output schema, the description covers the main purpose and one essential input (conversation). However, it omits guidance on the required 'message' field and the optional 'context' field, leaving the agent partially uninformed about how to construct a valid call. Adequate but with clear 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?

Schema description coverage is 0%, so the description must substantiate parameter meaning. It mentions the conversation parameter explicitly ('Include the conversation array') but fails to explain the required 'message' parameter or the optional 'context'. This partial compensation is insufficient for a tool with three 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 uses a concrete verb 'report' with explicit resource types: 'a bug, missing feature, or send feedback.' This clearly differentiates from unrelated sibling tools like authenticate, connect, and marketplace, making the tool's purpose immediately obvious.

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 it (when you need to report an issue or send feedback) but offers no explicit exclusions or alternatives. Since siblings are unrelated, no exclusion is needed, but the description lacks any guidance on prerequisites or when not to use the tool.

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 useful context by specifying exactly which versions are shown—MCP platform and adapter—which is valuable beyond the annotation title.

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 with no filler or redundancy. Every word contributes to explaining the tool's function.

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, zero-parameter read-only informational tool, the description is complete. It names the exact output scope (MCP platform and adapter versions) and does not require additional caveats or return-value documentation.

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 baseline is 4 per the rubric. The description does not need to explain parameter meaning, and no parameter information is missing.

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 ('Show') and a clear resource ('current MCP platform and adapter versions'), which precisely defines what the tool does. It goes beyond the tool name by identifying the two version categories being reported.

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 intended usage is implied: call this tool when you need to know the current MCP platform and adapter versions. However, there is no explicit guidance about when not to use it or how it compares to sibling tools such as toolkit_info.

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 mark it as read-only and idempotent. The description reinforces this by stating it 'returns' state, and adds no conflicting info. It doesn't introduce extra behavioral caveats, but the safety profile is well covered by 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, concise sentence that directly states the tool's function without extra verbiage. It efficiently lists the key components of the returned state.

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 simple read-only nature and lack of output schema, the description provides sufficient detail about what information is returned. It completely covers the tool's functionality without needing to enumerate return values.

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 coverage is 100%. The baseline for 0 params is 4, and the description correctly implies no inputs are needed. No parameter details are required.

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 that the tool returns the current toolkit state, listing specific data points (installed MCPs, connection status, accounts, catalog tool counts). This 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?

The description effectively communicates what the tool does but does not explicitly state when to use it over alternatives. It implies utility for checking toolkit status, but lacks explicit usage context or scenarios.

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