Procuradoria Geral do Estado CE: Dívida Ativa

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

The description discloses key behavioral aspects: calling with no args returns a link, calling with a token logs in for a session. It also mentions 'permanent, non-expiring' connection via config, hinting at persistence. This goes beyond the annotation (idempotentHint=true) to clarify that the tool may establish a session, which is useful 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 somewhat verbose but well-structured, with a clear split between general setup and specific call instructions. It avoids unnecessary fluff and presents steps in a logical order, though it could be slightly more compact.

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 authentication tool, the description provides sufficient context: it explains the two modes, mentions the token format, and indicates the permanence of the config-based approach. It does not describe the return value in detail, but given the absence of an output schema, this is acceptable.

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 only defines 'token' as a string with no description. The tool description explains that the token is a JWT obtained from the browser and used for session-only login, and clarifies that omitting it triggers link generation. This fully covers the 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: to authenticate with MCP.AI for IDE agents. It explains the two usage modes (no args to get login link, or with token to login) and includes specific guidance on permanent vs session-only login. The name 'authenticate' is reinforced by the detailed explanation.

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 instructions on how to use the tool: either call with no arguments to receive a link, or provide a token as an argument. It also contrasts session-only vs permanent setup via server config. While it does not explicitly refer to alternative tools, the usage context is clear enough for an agent to know when to invoke 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?

Beyond the annotations (read-only, idempotent, non-destructive), the description reveals that the tool returns different results based on connection state (authenticated true vs. connect_url). This adds useful behavioral context not apparent 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 concise and well-structured, using only two sentences to convey the core functionality and conditional behavior without unnecessary verbosity.

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 covers the key return scenarios (connected vs. missing credentials) and specifies the output fields (authenticated, pending, connect_url, per-install URLs). While an explicit output schema is absent, the description provides enough context for typical 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 no parameters, so there is nothing to explain. The description appropriately omits parameter details, and the schema coverage is effectively complete.

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: it returns connection status and URLs. It differentiates from sibling tools by focusing on connection status rather than authentication or version info.

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 or retrieve connection URLs) and mentions different scenarios (all providers connected vs. missing credentials), but does not explicitly contrast with alternatives. However, given the nature of the tool, this 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 only say readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false. The description adds substantial behavioral context: invoke runs tools one-off without installing or bloating the tool list, credential and payment failure modes return links, writes require workspace owner/admin, and installed status is flagged in search/describe. No contradiction with annotations is present.

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 and logically front-loaded: it starts with the tool's identity, then the core flow, key invoke behavior, install vs invoke, auxiliary actions, and the prompt library. It earns its length for a 14-action tool, though a single dense paragraph with semicolon-heavy sentences could benefit from bullet points or section breaks.

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 no output schema and minimal annotations, the description covers most critical operational context: the search/describe/invoke flow, one-off execution semantics, auth and billing link handling, install permanence, owner/admin requirements, and prompt-library behavior. Gaps remain for the 'resume' action and several parameters, but the description is strong enough for an agent to use the tool correctly in most cases.

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 compensate. It explains the meaning of the action enum and the roles of key parameters like mcp_id, tool_id, and prompt_slug within the core flow. However, many parameters (limit, immediate, tier_slug, conversation, cancel_reason, prompt_targets, request_details, etc.) are left unexplained, leaving the agent to guess their 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 identifies the tool as the mcp.ai marketplace catalog and execution layer, with a specific verb+resource framing ('catalog of every MCP/tool, AND the way to run them'). It distinguishes itself from siblings by explaining its core search→describe→invoke flow and naming adjacent actions like report_bug and request_mcp.

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 when-to-use guidance for each major action: use search to discover, describe to inspect, invoke for one-off runs, install only for permanent toolkit additions, list_tools for currently callable tools, and request_mcp when nothing fits. It also explicitly contrasts invoke vs install and explains the retry flow after connect/checkout links.

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 indicate read-only and idempotent behavior. The description adds that no platform credentials are needed and that it is a paid service, which are extra behavioral traits. It doesn't mention error handling or rate limits, but it does provide some extra 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 relatively short but includes some repetitive phrases and legal wording. The main purpose is clear in the first sentence, but the additional detail about hosting and payment could be more concise. Still, it's acceptable.

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 response format or what the tool returns. It also doesn't clarify which parameters are required. Given the tool's simplicity, it might be enough, but it could be more 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?

The description does not explain the four parameters (cpf, pagina, cnpj_base, numero_inscricao). Since the schema provides no descriptions, the description should compensate but doesn't, leaving parameter semantics ambiguous.

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 consults active debt information from the State Attorney General's Office of Ceará, using official sources. It also clarifies that it's the same data available to citizens, making the purpose specific and distinctive from the generic sibling tools.

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 that it's hosted on the platform, requires no platform credentials, and is a paid consultation, which helps when to use it. However, it doesn't explicitly contrast with alternative tools, but given the sibling tools are generic, it's sufficient. It also mentions LGPD compliance, indicating legal use.

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 indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description only adds the instruction to include the conversation array, which is a usage directive rather than disclosing behavioral side effects (e.g., whether a report is created, emailed, or stored). No additional transparency about consequences or requirements is provided.

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 well-structured: it states the action, lists the types of reports, and gives a specific instruction. No redundant information. It is clear and to the point.

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 simplicity of the tool, the description covers the main purpose and provides a key usage hint (conversation array). However, it lacks details about the other parameters (context, message) and does not explain what happens after reporting (e.g., confirmation, ticket creation). The absence of an output schema reduces the need for return value details, but the description could be more comprehensive about the expected inputs and side effects.

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 three parameters: context, message (required), and conversation. The description only mentions conversation and its purpose (for reproduction). It does not explain context or message, although their names suggest meaning. With 0% schema coverage from the description, parameter semantics are only partially addressed. The description adds value only for conversation.

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 also mentions the conversation array for reproduction, which directly relates to the tool's function. This distinguishes it from sibling tools like authenticate, connect, etc., 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 implies when to use the tool (when reporting a bug or sending feedback) and instructs to include the conversation array. It doesn't explicitly mention alternatives or exclusions, but given the specificity of the tool, the usage context is reasonably clear.

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 cover read-only, idempotent, and non-destructive behavior. The description adds minor detail about the output (platform and adapter versions) but does not disclose any additional behavioral traits beyond that. It is neither contradictory nor significantly additive.

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 any fluff or unnecessary details. It is well-structured and to the point.

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?

Without an output schema, the description adequately explains what the tool returns (current MCP platform and adapter versions). It is concise but sufficient for a simple version query, though it does not specify the format or any additional 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 definition. The description does not add any parameter-related information, which is acceptable given there are none, but it also does not enhance understanding beyond the 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 function: showing the current MCP platform and adapter versions. It specifies the resource (versions) and the action (show), making it distinct from siblings like report_bug or toolkit_info.

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 no indication of when to use this tool versus alternatives. It lacks explicit guidance on scenarios where this version query is appropriate or where other tools might be preferred, leaving the user to infer 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 establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description is consistent with those. It adds useful transparency by specifying the returned state contents, which is especially valuable because no output schema is provided, though it does not discuss latency or auth requirements.

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?

A single, front-loaded sentence that immediately states the purpose and then lists the four components of the returned state. Every phrase earns its place, with no filler or repetition of the tool name.

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 info tool with strong annotations, the description fully covers what the agent needs to know: what the tool returns and at what granularity. Since there is no output schema, the description appropriately carries the burden of explaining the return content.

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 empty schema is fully described and there is nothing for the description to add about parameter meaning. The baseline of 4 for no-parameter tools applies.

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 ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from siblings like show_version, which would only report 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?

No guidance is given about when to use this tool versus alternatives such as show_version or connect. The description states what it returns but does not suggest a use case like checking connection health before invoking other MCP tools, nor does it mention any exclusions.

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