Prefeitura SP São Paulo: Multas

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

The description adds behavioral context beyond annotations, explaining permanent vs session-only login and the effect of calling without arguments. It aligns with idempotentHint=true and does not contradict the 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 two sentences with key information front-loaded (MCP.AI for IDE agents) and concise practical steps. Slightly dense but efficient without useless 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 an auth tool with one optional parameter and no output schema, the description covers all essential usage modes and configuration. It doesn't mention return values, but that's minor given the 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?

Schema coverage is 0%, but the description clearly explains the 'token' parameter as a JWT obtained from browser login, and how to use it. This fully compensates for the lack of schema-level documentation.

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 authenticating for MCP.AI, explaining the browser login and token methods. It distinguishes from general connectivity by focusing on auth, though it doesn't explicitly contrast with the sibling tool 'connect'.

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: recommends configuring a header for permanent access, or pasting a token for session-only login. It also specifies when to pass a token versus calling with no arguments to get a link.

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 goes beyond the readOnlyHint and idempotentHint annotations by detailing conditional behavior: when all providers are connected it returns authenticated:true and empty pending[], and when credentials are missing it returns connect_url and per-install URLs. This provides meaningful behavioral insight not present in the 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 two sentences with no fluff. It front-loads the core purpose ('Returns connection status and URLs') and then efficiently explains conditional outputs. 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 tool with no parameters and no output schema, the description covers the main use cases: connected vs. missing credentials. It could be slightly clearer about what 'pending' represents or what the URLs are for, but it is quite complete for 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 does not need to document parameter behavior since there are none, and it correctly focuses on output semantics 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 clearly states the tool 'Returns connection status and URLs', using a specific verb and resource. It also distinguishes itself from siblings like 'authenticate' by focusing on status rather than the authentication action. The behavioral details (authenticated:true, pending[]) add specificity.

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 this tool is used to check connection status and get URLs when needed. However, it does not explicitly mention when NOT to use it or how it differs from siblings like 'authenticate' or 'toolkit_info'. The usage context is clear but not explicitly contrasted with alternatives.

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 openly discloses side effects and permissions: invoke runs uninstalled MCPs one-off without bloating the toolkit, writes require workspace owner/admin, and auth/payment gaps surface as connect or checkout links. This adds substantial context beyond the annotations and does not contradict readOnlyHint=false or openWorldHint=true.

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 packed, front-loading the marketplace purpose and core flow before covering installation, one-off invocation, billing, permissions, and the prompt library. It could be better organized with bullets, but every sentence contributes meaningful guidance.

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 14-action, 23-parameter tool with no output schema, the description covers nearly every action's purpose and important outcomes: profile details, connect/checkout links, permanent vs one-off installation, admin requirements, installed flags, and shareable prompt links. It misses a few edge behaviors such as the resume action and the immediate/tier_slug parameters, so it falls just short of 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 gives real meaning to the central action parameter and workflow: search discovers MCPs, describe returns full profiles with ids/params/pricing/auth, and invoke runs the selected tool_id. It does not enumerate all 23 fields such as immediate, tier_slug, resume, or prompt_targets, but the core parameter relationships are compensated clearly despite 0% schema description coverage.

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/catalog and the way to run MCPs, then names concrete capabilities such as search, describe, invoke, install, unsubscribe, and prompt-library actions. This establishes a specific verb+resource and differentiates it from sibling tools like authenticate and connect.

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 an explicit core flow (search → describe → invoke) and gives direct guidance: prefer invoke for one-off use, use install only for permanent additions, and use request_mcp when nothing fits. It also explains when list_tools, subscribe/cancel, report_bug, and the prompt actions apply.

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. The description adds meaningful context beyond this: prepaid billing per query, absence of platform credentials, use of official public data, and LGPD/controller responsibilities. 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 reasonably concise with three sentences and is front-loaded with the main purpose. However, some legal/administrative boilerplate about LGPD could be trimmed without losing essential operational value.

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?

Despite helpful annotations and business context, the description is operationally incomplete for a 7-parameter data tool with no schema descriptions and no output schema. It fails to explain parameter semantics, output/return behavior, or the guias/boleto/AIT aspects hinted at by the tool name.

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 gives no explanation for any of the 7 parameters, including required ones like placa, renavam, and login_senha. It vaguely mentions credentials but does not map them to the schema, leaving the agent without enough information to fill parameters 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?

Description clearly indicates this tool performs a consultation ('consulta') of Multas (fines) from the official São Paulo city source, which distinguishes it from sibling authentication/admin tools. However, the tool name also mentions 'guias' (payment guides), which is not reflected in the description, slightly narrowing the stated purpose.

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 useful context: the tool is hosted by the platform, does not require platform credentials, and requires prepaid credit per query. It also states the data is official and not confidential. However, it does not explicitly state when to use this tool vs. alternatives or provide exclusions, so usage guidance remains partly implied.

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 non-destructive and non-read-only behavior. The description adds the requirement to include the conversation array for reproduction, which is a useful behavioral hint. However, it does not describe what happens after reporting (e.g., whether a ticket is created) or any side effects, so it adds only moderate value beyond the 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 concise, consisting of two sentences that are front-loaded with the purpose. It wastes no words and directly states the essential 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?

The tool is relatively simplehol, but the description fails to explain all three parametershol. It covers the conversation parameter well but leaves 'message' and 'context' unexplained. Given the simplicity, more detail could be provided to make it fully 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 schema has no descriptions for the parameters, and the tool description only explains the 'conversation' parameter. The 'message' and 'context' parameters are not clarified, leaving significant ambiguity. Since schema coverage is 0%, the description should compensate but does not.

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 is a specific verb, target, and scope. It also distinguishes itself from the sibling tools, which are unrelated (authentication, marketplace, etc.).

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 a clear usage instruction: 'Include the conversation array with recent messages for reproduction.' This provides practical guidance for how to use the tool effectively. However, it does not explicitly mention alternatives or when not to use it, though that is not critical given the unrelated siblings.

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 context about what is displayed (platform and adapter versions), which is helpful. It does not mention any side effects or special behaviors, but given the read-only nature, this is sufficient.

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 with no fluff. It directly states 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?

With zero parameters, no output schema, and comprehensive annotations, the description fully covers what an agent needs: it is a read-only, idempotent action that returns version information. No additional details are necessary.

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; the schema is empty and the description accurately reflects that. No further elaboration needed.

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?

Clear verb+resource: 'Show the current MCP platform and adapter versions.' It is specific and distinct from sibling tools like authenticate or connect, which perform different actions.

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 for checking versions, which is straightforward. No explicit alternatives are mentioned, but the tool's purpose is self-evident for an informational request. It lacks explicit timing or when-not-use guidance, but given its simplicity, none 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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds the specific content returned (installed MCPs, connection status, accounts, catalog tool counts), which provides useful context beyond the annotations without contradiction.

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 that directly states the purpose and enumerates the returned details. Every word earns its place; there is 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?

Given no parameters, no output schema, and annotations covering safety and idempotency, the description is fully adequate. It specifies exactly what information is returned, which is all the context an agent needs to decide to call it.

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 there is nothing for the description to explain beyond the schema. The description does not repeat any parameter information, and the baseline for zero-parameter tools is 4. No loss of information occurs.

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 the current toolkit state, enumerating specific content (installed MCPs, connection status, accounts, catalog tool counts). This is specific and distinguishes it from siblings like 'show_version' or 'connect'.

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 context is implied: use this to inspect toolkit status. However, there is no explicit guidance on when to prefer this over siblings, nor any exclusions or alternative references. It lacks explicit 'when-to-use' statements.

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