ECRVSP Veículos: Base Estadual de SP

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

No contradiction with annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false). The description adds genuine behavioral value beyond annotations: the persistence semantics ('permanent, non-expiring connection' vs 'session-only'), the user-interaction requirement (user pastes a JWT in the browser flow), and the no-arg behavior returning a link. A minor omission is any statement about success/failure output, but for an idempotent auth tool the disclosure is strong.

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 with some awkward phrasing ('log in in the browser') and parenthetical asides that hurt scannability. However, every clause does earn its place by conveying the permanent-vs-session tradeoff, the JWT format, and the config-header alternative. Restructuring into two distinct flow options would make it notably clearer.

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 low-complexity tool (1 optional param, no enums, no nested objects, no output schema), the description covers the key decision points: both auth flows, the persistence tradeoff, and the no-arg return of a link. The one notable gap is the absence of any stated return-value contract — especially relevant since there is no output schema — though 'to get the link' weakly implies the no-arg response shape.

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% — the schema only declares 'token' as an unadorned string. The description fully compensates: it reveals the expected format ('<jwt>'), when to pass it ('after the user pastes'), and the alternative of calling with no args. For the tool's only parameter, the agent now understands exactly how to populate it, which is precisely the needed compensation.

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 handles authentication ('log in in the browser, copy the access token') for MCP.AI IDE agents, with a specific verb+resource that is unambiguous. It distinguishes itself from siblings like 'connect' or 'marketplace' through its explicit focus on the login/access-token flow, though it never names a sibling for direct contrast.

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 an explicit decision tree: 'Best: add it to this server's config as a header' versus 'paste it here for a session-only login,' plus when to call with no args to get the link. This is actionable guidance for when to use each path within the tool, though it does not compare against or exclude 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?

Annotations already declare readOnly, idempotent, non-destructive. Description adds valuable detail on response variants (authenticated:true vs connect_url), but doesn't mention error handling or side effects. Since annotations cover the safety profile, description adds sufficient 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?

Two sentences, no filler, clearly structured with conditional cases. Maximally concise.

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 tool with no output schema, description explains return values in both states. It's sufficient for an agent to know what to expect. Could mention that it's a status check, but it's implied.

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?

No parameters exist, so the baseline is 4 as per instructions. Description doesn't need to explain 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?

Description states the tool returns connection status and URLs, with a specific verb ('Returns') and resource ('connection status and URLs'). It explicitly contrasts two scenarios (all providers connected vs. missing credentials), which distinguishes it from siblings like authenticate or marketplace. Purpose 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?

The description gives conditional behavior but doesn't explicitly state when to use this tool versus alternatives like authenticate. It implies usage for checking connection status but provides no exclusion or comparison with 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?

Beyond the readOnly/idempotent/non-destructive annotations, it discloses prepaid per-query cost, no platform credentials, that data is from official public sources and not confidential, and that the client is data controller under LGPD. These are material behavioral and compliance 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 three sentences, front-loaded with the tool's purpose and scope, and includes essential payment/legal context without being bloated. A structured parameter overview would improve it, but the current size is appropriate.

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?

There is no output schema, no parameter explanations, and the description leaves the required credential parameters and query behavior opaque. It provides good business and compliance context, but not enough for an agent to confidently know how to supply a3/a3_pin/login_cpf/login_senha or what result to expect.

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% for 7 parameters, and the description does not explain a3, a3_pin, login_cpf, or login_senha. Only indirect hints like 'sem credenciais da plataforma' and self-evident names like placa/chassi/renavam reduce the gap, but required auth fields remain unclear.

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 a specific query operation: 'consulta em fonte oficial' against the ECRVSP Veículos state database of SP. It names the resource and scope ('Base Estadual de SP', 'fontes e órgãos oficiais brasileiros') and is distinguishable from the unrelated 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?

It communicates clear context: use for querying official Brazilian source data available to citizens, not confidential data, with prepaid credit and without platform credentials. It implies legitimate-purpose scenarios and LGPD responsibility, but does not explicitly contrast against alternatives or state when not to 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?

Beyond the annotations, the description discloses important behaviors: invoke works on non-installed MCPs one-off without bloating the tool list, handles credential and wallet-empty cases with connect/checkout links, and restricts writes to workspace owner/admin. No contradiction with the 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 the tool is genuinely broad with 14 actions plus separate prompt-library features. It is front-loaded with the core flow and the key invoke-vs-install tradeoff, then covers permissions and additional commands; a few headings or bullets would make it even cleaner.

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 workflows, permission requirements, edge cases around authentication/payment, and the prompt library, which is strong for a complex tool with no output schema. It does not describe return shapes or pagination/limit behavior, leaving some ambiguity for an agent trying to invoke exactly.

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 and 23 parameters, the description shoulders the burden; it explains action values and end-to-end flows but does not give explicit semantics for many parameters such as limit, immediate, tier_slug, cancel_reason, conversation, and prompt_targets. It compensates for the main parameters like tool_id, arguments, and prompt vars, but not enough to fully cover the 23-parameter surface.

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 this as the official mcp.ai marketplace, positioning it as both a catalog of every MCP/tool and the execution path for running them. It describes distinct sub-flows (search, describe, invoke, install, prompt library) and concrete user intents like 'find an MCP that does X'.

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 discovers MCPs, describe returns a full profile, invoke runs one-off, while install is reserved for permanent toolkit additions. It gives direct preference guidance like 'prefer invoke for a single/occasional use' and tells when to use request_mcp, list_tools, subscribe/cancel, and the prompt-library commands.

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 readOnlyHint=false and destructiveHint=false, but the description does not disclose side effects like data transmission. It does add context by advising to include the conversation array for reproduction, which is useful. No contradiction with annotations, but more behavioral detail could be 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 only two sentences and immediately states the tool's purpose and a key usage tip. Every word adds value, and the structure front-loads the primary action. Extremely concise and clear.

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 bug-report tool with 3 flat string parameters and no output schema, the description provides sufficient guidance on what to include (conversation array). It could mention side effects or privacy implications, but given the tool's simplicity and existing annotations, the description is largely 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?

Schema description coverage is 0%. The description only references the 'conversation' parameter ('conversation array'), but does not explain 'message' or 'context'. Since schema coverage is low, the description should compensate but fails to explain most parameters. The reference to 'conversation' provides minimal help.

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 and resource: 'Report a bug, missing feature, or send feedback.' It clearly distinguishes this tool from siblings like 'marketplace' or 'authenticate' by stating its exact purpose. No ambiguity about what the tool does.

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 this tool (to report bugs, missing features, or feedback) but does not provide explicit alternatives or exclusions. It hints at usage by instructing to include the conversation array for reproduction, but lacks guidance on when not to use it or how it compares 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?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds no extra behavioral details but is consistent with those annotations, so the bar is met 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, concise sentence that fully conveys the tool's purpose without superfluous content.

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 simplicity (no parameters, no output schema), the description is complete and sufficient for an agent to understand and invoke it 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?

The tool has no parameters, so there is nothing to describe. The schema confirms this, and the description does not imply any hidden inputs.

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 current MCP platform and adapter versions. It is specific and distinguishes from 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?

While the purpose is obvious, the description does not explicitly mention when to use this tool versus alternatives (e.g., for debugging or compatibility checks). The usage context is implied but not stated.

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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description does not contradict them. It adds useful behavioral context by enumerating exactly what state information is returned, which helps an agent understand the tool's read-only, informational 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, well-structured sentence that front-loads the action and then enumerates the returned components in a clear list. There is no redundant or filler wording.

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 lacking an output schema, the description enumerates the major result categories, making the return semantics reasonably clear. Given that there are no parameters and the behavior is read-only, this is a complete and sufficient description for correct 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?

The tool has zero parameters, so the schema fully covers all inputs. The description needs to explain parameter semantics; its focus on return content 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 begins with a specific verb ('Returns') and names a concrete resource ('current toolkit state'). It clearly lists what the output contains—installed MCPs, connection status, connected accounts, and catalog tool counts—which distinguishes it from siblings 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?

No explicit guidance is provided for when to use this tool versus alternatives. The description implies that it is for inspecting toolkit state, but it does not state whether it should be called before/after connect or how it relates to sibling tools like authenticate or marketplace.

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