Prefeitura SP Ribeirão Preto: Certidão Negativa de Débitos

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

Annotations already indicate non-read-only and idempotent, and the description adds the distinction between permanent (config-based) and session-only (token paste) connections. It doesn't detail side effects like token expiry or revocation, but it offers context beyond annotations. No contradiction found.

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, long run-on sentence that packs a lot of information but is somewhat convoluted. It is front-loaded with the IDE agent context, which might be essential but could be trimmed. The structure mixes instructions and options without clear separation.

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 a simple schema (one optional param), no output schema, and supportive annotations, the description covers the essential workflow: browser login, token acquisition, and two integration methods. It doesn't explain return values, but that's not required. Overall, it's adequate for a straightforward auth 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?

The schema has one optional 'token' parameter with no description (0% coverage). The description compensates by clarifying that the token is a JWT and explains that it's used for session-only login, while no args returns the login link. This adds meaningful semantics to the parameter.

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 by logging in via browser and obtaining an access token. It distinguishes between two usage modes (permanent config vs. session token) and separates it from siblings like 'connect' by focusing on user login. However, the opening 'MCP.AI for IDE agents' adds context that slightly muddies the core 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?

Provides explicit instructions: log in in the browser, copy token, and choose between adding as header for permanent access or pasting for session-only. It also explains how to invoke (with or without token). Lacks explicit 'when not to use' but gives clear operational 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 readOnly, idempotent, and non-destructive behavior. The description adds useful conditional behavior: authenticated:true with empty pending[] versus connect_url and per-install URLs. This goes 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?

Two sentences, front-loaded with the core purpose, and every sentence adds meaningful information about the tool's conditional behavior. No filler or redundancy.

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 with strong annotations, the description fully explains what will be returned under both relevant conditions. No output schema exists, but the description sufficiently communicates the return semantics.

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 schema fully covers parameter semantics. Per calibration, a baseline of 4 is appropriate; no additional parameter explanation is necessary.

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 states a specific action ('Returns connection status and URLs') and details the two concrete output states. This clearly distinguishes it from sibling tools like authenticate, which performs authentication rather than reporting on it.

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 for when to expect what results (all providers connected vs. missing credentials), implying this is for checking connection state. It does not explicitly name alternatives or exclusions, but the behavior is sufficiently scoped.

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?

Discloses that invoke works without installation, returns connect/checkout links for auth/payment, and notes writes require workspace owner/admin. This adds context beyond the annotations (readOnlyHint=false, openWorldHint=true) and covers side effects and permission 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?

The description is a single dense paragraph lacking bullet points, headings, or separation between the marketplace flow and prompt library sections. While information-dense and without fluff, the lack of structure hinders quick scanning for specific details.

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 core workflow, auth/payment flows, permission requirements, and the prompt library, which is comprehensive for a complex tool. Yet it omits explanations for some actions like resume, cancel details, and does not fully clarify return formats or all parameter interactions.

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 compensates by explaining many parameters in context: action enum, mcp_id, tool_id, arguments, tier_slug, prompt_* fields, etc. However, it does not systematically cover all 23 parameters, omitting details on limit, immediate, conversation, and report_context.

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 search and runtime execution. It lists distinct actions (search, describe, invoke, install, etc.) and distinguishes itself from sibling tools like report_bug and show_version by outlining its core 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?

Provides explicit when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'use install only to make an MCP PERMANENT', and directs to search_prompts/get_prompt for prompt text. Also contrasts with list_tools for current callable tools and request_mcp for new builds.

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 readOnly/idempotent/destructive hints. The description adds meaningful behavior details: payment requirements (prepaid credit), absence of platform credentials, and LGPD data controller responsibility. It clarifies that the data is non-confidential and publicly available, which is useful 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 compact—one paragraph, four sentences—and front-loads the core purpose. It packs relevant operational and legal info without fluff, though it could be better structured with separate lines for parameters.

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 query tool with three parameters and no output schema, the description explains the purpose and operational constraints but omits parameter guidance and what the response contains. It lacks details on required inputs and expected results, which would enhance 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% and the description provides no explanation of the three parameters (cpf, cnpj, inscricao_municipal). It does not hint which combination is expected or the required one, leaving the agent to rely solely on the schema for 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 specific resource (Certidão Negativa de Débitos from Prefeitura SP Ribeirão Preto) and the action (consulta/query). It distinguishes itself from sibling tools (authenticate, connect, etc.) by naming the exact 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?

The description provides operational context (hosted by platform, pay-per-query, no platform credentials needed) but does not explicitly state when to use this tool versus alternatives or when not to use it. There is no mention of exclusions or prerequisites around the input parameters.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false, which already signal the tool's safety profile. The description adds context by requiring the conversation for reproduction, but does not disclose what happens after submission (e.g., where the report goes, confirmation behavior). With annotations present, this is acceptable but not rich.

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 sentences, front-loaded with the action and ending with a actionable instruction. No wasted words, no repetition of schema fields.

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 tool is simple (3 params, no output schema, no nested objects), and the description covers the overall use case and one parameter well. However, the required 'message' parameter is unexplained, and there is no mention of return values or post-submission behavior, so completeness is only adequate.

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 carries the burden of explaining parameters. It clarifies that 'conversation' should contain recent messages for reproduction, but provides no guidance for the required 'message' parameter or the optional 'context.' The primary input is undocumented, leaving 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: 'Report a bug, missing feature, or send feedback.' This distinguishes it from sibling tools (authenticate, connect, marketplace, show_version, toolkit_info) which serve unrelated 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 provides clear context for when to use the tool (bug reporting, feature requests, feedback) and explicitly instructs to 'Include the conversation array with recent messages for reproduction.' It does not explicitly mention alternatives or exclusions, but siblings are unrelated, so the usage context 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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds no behavioral detail beyond saying what it shows (versions), which is useful but does not enrich the agent's understanding of side effects or response structure beyond that.

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 contains all necessary information with zero wasted words. It is appropriately sized for the tool's trivial complexity.

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 no-parameter, read-only query with no output schema, the description fully explains what the tool returns (current platform and adapter versions). No additional context is needed given the tool's simplicity.

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 provides no parameter-level detail because none is required; the schema already covers everything (empty properties).

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 verb "Show" is precise and the resource "current MCP platform and adapter versions" is clearly specified. None of the sibling tools (authenticate, connect, marketplace, etc.) perform this function, making the 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?

No explicit when-to-use guidance is given, but the tool's intent is self-evident and there are no competing siblings that offer version info. A minimal context of 'when you need version info' is implicitly clear, so no exclusions or alternatives are necessary.

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 (readOnlyHint: true), idempotent, and non-destructive. The description adds value by specifying the exact information returned (installed MCPs, connection status, accounts, catalog tool counts) beyond the annotations. It does not contradict the annotations, and it clarifies the tool's behavior (returns state rather than modifying anything).

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 sentence that is concise and front-loaded with the key purpose ('Returns the current toolkit state'). It lists the specific components without unnecessary detail, 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?

Given that the tool has no parameters, no output schema, and clear annotations declaring it read-only, the description is complete for its scope. It mentions the key outputs (installed MCPs, status, accounts, tool counts), which is sufficient for an agent to understand the tool's capabilities. It could perhaps mention the format or data structure of the response, but that may not be critical without an output schema.

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 the description clearly explains what the tool returns without needing to describe parameter semantics. The schema coverage is 100% as there are no parameters, so the baseline for 0 params is 4, and the description adds no extra parameter details because none exist.

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: returning the current toolkit state, listing installed MCPs, their connection status, accounts, and catalog tool counts. It uses a specific verb ('Returns') and a clear resource ('current toolkit state'), distinguishing it from sibling tools like authenticate, connect, and show_version.

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 what the tool does but does not explicitly state when to use it versus alternatives like 'show_version' or 'marketplace'. It implies that it's for general overview, but there is no explicit guidance on when to choose this tool over others. However, the scope is clear enough that an agent can infer appropriate usage.

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