Prefeitura SP São Paulo: CADIN

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

Adds meaningful behavioral detail beyond annotations: how login occurs, token source, permanent vs session-only persistence, and no-arg link return. Does not detail response/error cases, but annotations already cover idempotency and non-destructiveness.

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?

Three sentences, front-loaded with purpose and actionable instructions. The only slight inefficiency is embedding a manual server-config recommendation alongside tool-call semantics, but it earns its place by explaining the permanent-auth alternative.

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 single-optional-param auth tool with no output schema, the description covers login flow, token format, invocation modes, and what no-args returns. It omits explicit return value for token calls and error behavior, but is sufficient for an agent to invoke 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 0% schema coverage, the description fully compensates: token is explained as a JWT pasted from the browser, optional, and the no-args behavior is explicitly contrasted with token-bearing calls.

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 clearly states the tool authenticates to MCP.AI for IDE agents via browser login and access token. It specifies the exact resource and action, though it does not explicitly contrast with the sibling 'connect' tool.

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 clear when/how: use with no args to get a login link, or with a token after the user pastes it; recommends config header for permanent auth vs session-only paste. Lacks explicit exclusions or alternative tool names, but the context is unambiguous.

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, covering the safety profile. The description adds valuable details about the response structure and conditional behavior based on credential status, 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 two concise sentences that front-load the primary purpose and then cover both key behavioral cases. Every sentence adds value with 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?

The tool is simple (no parameters, no output schema), and the description covers all relevant states: connected vs missing credentials. It specifies exact response fields (authenticated, pending, connect_url, per-install URLs), making it complete for an agent to understand the tool's 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 tool has zero parameters, so schema coverage is trivially 100%. The description adds no parameter-specific details (none needed), and the baseline score of 4 applies because there are no parameters to clarify.

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 and URLs, with specific details about the response content (authenticated flag, pending array, connect_url). This distinguishes it from siblings like authenticate (which performs authentication) and show_version (which returns 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 implicitly communicates when to use the tool by describing two scenarios: when all providers are connected and when credentials are missing. It provides clear context for expected behavior but does not explicitly state alternatives or exclusions relative to sibling tools.

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 annotations (readOnlyHint=false, destructiveHint=false), the description adds significant behavioral context: it explains that invoke works without installation, returns connect links for credential needs, returns payment links for empty wallets, and that writes require owner/admin. It also clarifies the one-off vs permanent installation difference. No contradiction 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 long but densely informative. It is front-loaded with the core flow and key distinctions (invoke vs install). It is structured into logical segments (core flow, auxiliary actions, prompt library) without filler. While extensive, the length is justified by the tool's 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?

Given the tool's complexity (14 actions, 23 params, no output schema), the description is fairly complete. It covers the core usage paradigm, safety considerations, and alternate paths. It does not explain every parameter's interaction, but for an action-driven tool, the conceptual model is well articulated. The presence of a rich schema for parameters mitigates the lack of explicit parameter explanations.

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 0% schema description coverage, the description must compensate. It does explain the core action parameters implicitly (e.g., tool_id for invoke, query for search) by describing the flow, and it explains the action enum values. However, many parameters (limit, immediate, tier_slug, prompt_* fields, cancel_reason, etc.) are not mapped to their usage. The description covers the high-level semantics but not every parameter, leaving gaps.

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 it is the official mcp.ai marketplace and the way to run MCPs. It covers a broad set of actions (search, describe, invoke, install, etc.) and distinguishes itself from sibling tools by positioning itself as the central catalog and executor. However, because it is a multi-purpose umbrella tool, it lacks a single specific verb+resource focus, though it still differentiates through 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?

The description provides explicit guidance on when to use each action: 'prefer invoke for a single/occasional use; use install only to make an MCP PERMANENT'. It also explains the core flow (search→describe→invoke) and covers alternatives like list_tools for currently callable tools and request_mcp for new MCPs. It even notes auth requirements for writes, giving clear contextual 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 cover read-only and idempotent hints. The description adds useful behavioral details: it is not confidential data ('não é dado sigiloso'), the client is data controller, and there is a cost per query. These go beyond annotations and clarify the operational and legal impact.

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 verbose and includes repetitive legal disclaimers. Phrases like 'Hospedado pela plataforma, sem credenciais da plataforma' are unclear and add clutter. It could be significantly condensed while retaining essential info.

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 provides some context (official source, payment, legal compliance) but fails to explain key aspects like what CADIN is, how to use the parameters, what the output looks like, or error handling. Given the tool's simplicity, this is incomplete.

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 defines two parameters (cpf, cnpj) with no descriptions. The description makes no mention of these parameters, their formats, which is required, or their semantics (e.g., CPF for individuals, CNPJ for companies). This is a complete gap in parameter guidance.

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: 'CADIN, consulta em fonte oficial' (CADIN query from official source). It specifies the resource (CADIN) and the action (consulta), distinguishing it from sibling tools like show_version and 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 provides some context about usage: 'pague por consulta com crédito pré-pago' (pay per query with prepaid credit) and legal responsibilities under LGPD. However, it does not explicitly state when to use this tool over alternatives, nor does it mention any required conditions 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?

Annotations already indicate the operation is non-destructive and idempotent, so the description doesn't need to repeat that. It adds some context about including the conversation array for reproduction, which is helpful. It doesn't contradict annotations, but it doesn't disclose other behaviors like rate limits or side effects, which is acceptable given the simple nature.

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 main action ('Report a bug, missing feature, or send feedback'). It includes the key nuance about conversation array without excess. It earns high marks for efficiency.

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: three parameters, one required, no output schema. The description covers the purpose and gives a hint about reproduction. Given the simplicity, it's fairly complete, though it could mention that 'context' is optional or clarify the format of 'conversation'. Still, it's 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 must compensate. It does mention 'conversation array' and 'message' implicitly, but doesn't explain the 'context' parameter. However, it gives guidance on two of three parameters, and the 'message' parameter is self-explanatory. Given low coverage, this is a decent compensation, though it could be more explicit.

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 report bugs, missing features, or send feedback, and it mentions including the conversation array for reproduction. It distinguishes itself from sibling tools that are for authentication, marketplace, version info, etc., though it doesn't explicitly name alternatives.

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 there is a bug, missing feature, or feedback) and gives a hint about what to include (conversation array). However, it doesn't explicitly state when not to use it or mention alternative tools for specific cases, so it partially meets the 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 declare the tool as read-only, idempotent, and non-destructive. The description aligns with these annotations and clarifies that it reports platform and adapter versions. It adds no risky behaviors or surprising side effects, though it does not describe the exact output shape.

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, front-loaded sentence with no filler or redundant content. It directly states the tool's purpose and requires no parsing effort.

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 version query, the description is largely complete. It could optionally mention what the returned version payload looks like or distinguish itself from toolkit_info, but the core context is sufficiently covered for this low-complexity 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 input schema has zero parameters, and the description implies the tool takes no arguments. With no parameters to explain, the baseline is 4; the description provides no conflicting or missing parameter 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 specific verb ('Show') and clearly identifies the resource ('current MCP platform and adapter versions'). It is specific enough to distinguish this tool from general auth/connect/marketplace siblings, and the version focus 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?

Usage is implied: an agent would call this when it needs the current MCP or adapter version. However, there is no explicit guidance about when to choose this over sibling tools like toolkit_info, and no 'when not to use' or alternative suggestions.

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. The description adds value by specifying the exact contents of the returned state (installed MCPs, connection status, accounts, catalog tool counts), which is beyond what annotations provide. 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, well-structured sentence that front-loads the purpose and enumerates the returned data. Every word earns its place with no fluff 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 simple read-only info tool with no output schema and zero parameters, the description fully explains what the tool returns. It covers all relevant aspects and is complete given the low complexity.

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 zero parameters, so the schema coverage is trivially 100%. The description adds no parameter-specific information because none exist. With no parameters, the baseline of 4 is appropriate.

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 it returns toolkit state: installed MCPs, connection status, accounts, and catalog tool counts. It uses a specific verb (returns) and identifies the resource (toolkit state), fully distinguishing it from sibling tools like 'connect' 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 implies when to use it (to inspect current toolkit state) and it is read-only, which differentiates it from mutation tools. However, it does not explicitly mention alternatives or scenarios where another tool would be preferred, so it lacks explicit exclusions.

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