SEFAZ MT: Primeiro Emplacamento

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

The description discloses key behaviors beyond annotations: no-arg calls return the login link, token calls perform a session-only login, and config-header auth creates a permanent, non-expiring connection. This adds meaningful context about side effects and session duration, with no contradiction to 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?

Three tightly packed sentences, organized with 'Best:' and 'Or,' and all content earns its place. It is front-loaded with context and immediately gives actionable invocation details without unnecessary prose.

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 simple single-optional-parameter interface and no output schema, the description is complete enough for an agent to correctly invoke the tool: no args returns the link, token arg authenticates, and the config route is explained as an alternative. It covers invocation modes, session semantics, and permanence.

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 one optional parameter and 0% schema description coverage, the description fully compensates by explaining that 'token' is a pasted JWT, that it is optional, and that omitting it retrieves the login link. This is exactly the semantic guidance an agent needs beyond the bare string 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 identifies the tool as an authentication flow for MCP.AI/IDE agents, with specific actions: browser login, token copy, and session/permanent token configuration. The verb+resource is clear, but it does not explicitly distinguish itself from sibling tools like '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?

Explicit guidance is provided: use the server config header for a permanent connection, or call with a pasted token for a session-only login, or call with no arguments to receive the login link. It also clearly distinguishes between the two invocation modes and the preferred config approach.

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 annotations by detailing the output in different scenarios (authenticated:true and empty pending[] vs. connect_url). This provides behavioral insight that annotations alone (readOnly, idempotent) do not cover.

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 short sentences that convey the necessary information without redundancy. It is well-structured and easy to understand.

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 and the absence of an output schema, the description adequately covers the key contextual points: what it returns and the two possible outcomes. It is sufficiently complete for an agent to decide when to use 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?

The tool has no parameters (empty schema), so the description does not need to add parameter details. It is complete in that regard, as there is nothing to explain beyond what the schema already indicates.

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 returns connection status and URLs, which is its primary purpose. It distinguishes itself from other tools by focusing specifically on connection checks, avoiding ambiguity with 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?

The description explains the behavior under two distinct conditions (connected vs. missing credentials), which implicitly indicates when to use the tool. However, it does not explicitly mention alternatives or state when not to use it, so it falls slightly short of being fully explicit.

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?

Even though annotations exist, the description adds substantial behavioral context: invoke runs tools even when the MCP is not installed, one-off invocation does not bloat the toolkit, auth returns a connect link, insufficient wallet balance returns a checkout link, writes require workspace owner/admin, and search/describe distinguish installed_in_toolkit vs installed_in_workspace. 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?

Despite being a long description, it is dense and every sentence contributes. It front-loads the identity and core flow, uses KEY-based emphasis for the most important behavior, and avoids redundantly repeating schema defaults or type information. A slightly more distinct paragraph break could help, but the length is justified by the tool's broad surface.

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 such a complex, 23-parameter hub-style tool, the description covers remarkably well: capabilities, execution flow, install-vs-invoke semantics, auth/billing outcomes, permissions, answer search, and the prompt library. Remaining gaps are mostly obscure optional parameters like immediate, resume, tier_slug, conversation, and some prompt metadata fields, which prevents a perfect completeness score.

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 compensates for zero schema description coverage by explaining many core constructs: action=search/describe/invoke, tool_id+arguments for invoke, prompt_vars for get_prompt, and install/subscription behavior. However, there are 23 parameters and several remain effectively unexplained, such as immediate, tier_slug, conversation, cancel_reason, cancel_comment, and prompt_targets, so the compensation is strong but incomplete.

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 marketplace as a catalog, execution engine, and prompt library. It is explicit about the core action flow (search → describe → invoke), but because the tool is a multi-action dispatcher rather than a single-verb/single-resource endpoint, it does not fit the 'specific verb+resource' ideal perfectly.

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 excellent when-to-use guidance: prefer invoke for one-off runs, use install only for permanent toolkit inclusion, use list_tools to see what is callable now, use request_mcp when nothing fits, and use search_prompts/get_prompt/publish_prompt for prompt-library tasks. It clearly contrasts invoke vs install and describes 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?

Annotations already indicate idempotentHint=true and destructiveHint=false, so the tool is known to be non-destructive and safe to repeat. The description adds only a note about including conversation arrays, which is parameter guidance rather than behavioral disclosure. It does not contradict the annotations, but it also does not add meaningful context about side effects, permissions, or what happens on submission. Given the annotation coverage, a score of 3 is appropriate.

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 with no superfluous words. It front-loads the purpose and includes a critical usage instruction. Every word earns its place, making it highly concise and well-structured.

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 reporting tool with three parameters, the description covers the core purpose and the most important parameter (conversation). However, it lacks any mention of expected return values or side effects (though output schema is absent). With annotations providing some safety guarantees, the description is adequate but not exhaustive, leaving gaps around 'message' and 'context' semantics. A score of 3 reflects this partial 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%, so the description must compensate. It explains that 'conversation' should contain recent messages for reproduction, adding value beyond the schema's plain string type. However, it does not explain 'message' or 'context', leaving their purpose ambiguous. The partial clarification lifts it above a 1 or 2, but it is not thorough enough for a 4.

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 ('report') and resource (bug/feature/feedback), and it distinguishes the tool from siblings like authenticate, connect, or marketplace, which serve entirely different functions. The 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 provides clear context on when to use the tool (reporting issues) and even instructs the user to include the conversation array for reproduction. However, it does not explicitly state when NOT to use it or mention alternative tools. Since the siblings are unrelated, the context is sufficiently clear without exclusion criteria, but it stops short of a full 5.

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 adds useful behavior beyond annotations: it is paid per query, requires no platform credentials, returns data already available to citizens, and clarifies data-ownership/LGPD responsibility. The read-only, idempotent, and non-destructive traits are already covered by annotations, so this context 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 front-loaded with the core purpose, but it contains redundancy such as 'fonte oficial' versus 'fontes e órgãos oficiais brasileiros' and bundles several legal/payment clauses that could be tightened. It is readable but not 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 one-parameter read-only query, the description offers good operational context around official sourcing, payment, and legal use. However, without an output schema, it does not describe the return shape or result contents, and parameter semantics are largely left to inference.

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 never explains the 'chassi' parameter, its format, or expected value. The field name and the vehicle-registration context make the parameter somewhat inferable, but the description does not compensate for the missing schema-level explanation.

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 query operation for SEFAZ MT first vehicle registration ('Primeiro Emplacamento, consulta em fonte oficial') with a specific resource and scope. It also notes that no platform credentials are needed, which helps differentiate it from the generic authentication and platform 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?

The description provides practical usage context: no platform credentials, prepaid credit required, official Brazilian source data, and LGPD responsibilities. It does not explicitly name alternatives or exclusions, but the sibling tools are unrelated, and this guidance is clear enough for a query tool.

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 value by specifying exactly what information is shown (platform and adapter versions), which is not deducible 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 a single concise sentence that front-loads the verb and resource. Every word earns its place, with 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 version tool, this description fully satisfies contextual needs. No output schema exists, but the description already states what the output conceptually contains (platform and adapter versions), and the absence of complexity makes further detail unnecessary.

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. There is nothing to clarify in parameter semantics, and the description appropriately stays silent since no parameter info exists.

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 uses specific verb 'Show' with clear resource ('current MCP platform and adapter versions'). This clearly differentiates it from sibling tools like authenticate, connect, or report_bug, which serve entirely 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 tool is self-evidently a version-inspection utility with zero parameters; its purpose implies the use case: check current platform/adapter versions. No explicit exclusions or alternatives are needed because no sibling tool provides this capability, and the context is 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?

The annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool's safety profile is well covered. The description adds clarity about the returned content but does not disclose additional behavioral aspects such as side effects, authentication, or rate limits. It goes slightly beyond the annotation by enumerating the state details, 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 a single, front-loaded sentence that efficiently enumerates the four key aspects of the returned state. Every word adds value, and the colon-list structure makes it easy to scan.

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 provides a complete picture of what the tool returns. It covers all the major categories of state that a user might expect (MCPs, status, accounts, catalog counts), leaving no obvious gaps in 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 input schema has zero parameters, so there are no parameter semantics to clarify. With no parameters to document, the description does not need to compensate for any schema gaps, and 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 explains what the tool does: it returns the current toolkit state with specific details (installed MCPs, connection status, accounts, and catalog tool counts). It uses a specific verb ('Returns') and resource ('current toolkit state'), and it differentiates from sibling tools like show_version by specifying the scope of information provided.

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 (whenever toolkit state information is needed), but it does not explicitly state when to use it over alternatives or provide any exclusion criteria. No direct comparison with sibling tools is made, so the guidance is implied rather than explicit.

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