SEFAZ MT: IPVA

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

Beyond annotations (idempotentHint=true), the description discloses key behavioral details: browser login, token copying, permanent non-expiring vs. session-only connection, and behavior when called with no arguments. 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 front-loaded with the core purpose and then explains the two alternatives. It's slightly verbose but each sentence adds essential information, so it earns its length.

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 one optional parameter and no output schema, the description covers all relevant behaviors, usage modes, and parameter meaning thoroughly. It is fully complete for its 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?

The schema has 0% description coverage, but the description fully explains the `token` parameter as a JWT to be pasted, and also documents the no-args case. This compensates completely for the missing schema 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's purpose: logging in via browser, copying an access token, and using it for authentication. It distinguishes itself from siblings like 'connect' by explicitly describing its specific authentication 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 clear usage context: explains the recommended permanent config approach, the session-only paste option, and the no-args link retrieval. However, it does not explicitly contrast with sibling tools like 'connect' or state when not to use this 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?

Explains the two scenarios and their outputs, complementing the readOnly/idempotent annotations by detailing behavior without side effects.

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 with clear structure, no redundant 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?

Given no output schema, description gives sufficient detail about the output in both cases, making it complete for a simple check 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?

No parameters exist, so description doesn't add parameter details; schema already covers 100% with zero params, so it's adequate.

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?

States it returns connection status and URLs, and distinguishes between two outcomes, making it clear this is a status-checking tool distinct from siblings like 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?

Provides guidance on when to use: when checking if providers are connected, and explains the two possible responses, so a user knows what to expect.

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?

Adds significant context beyond the sparse annotations: invoke runs tools one-off without bloating the toolkit, auth-gated MCPs return connect links, paid MCPs with empty wallets return checkout/top-up links and then require a retry, installs are permanent, and write actions require owner/admin. These behavioral nuances are not available in the annotations and are essential for correct agent use.

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 dense, single-paragraph block with every sentence adding meaningful detail. It front-loads the core purpose and key flows, then covers secondary actions and prompt library context. Verbal and dense but not wasteful.

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 high complexity (23 parameters, 0 output schema, 11+ actions), the description covers most core workflows, permission requirements, return/redirect links, and the prompt-library additions. It still omits actions like `resume` and does not describe returned payload shapes for each action, so it is strong but not 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?

Schema coverage is 0% with 23 parameters, so the description carries most of the weight. The main flow action=search→mcp_id→tool_id+arguments is clearly implied, and the prompt library actions are partially linked to prompt_* parameters. However, many parameters (limit, immediate, tier_slug, cancel_reason, etc.) are not explicitly explained by parameter name, leaving ambiguity for less obvious parameters in the large 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 identifies the tool as the mcp.ai marketplace, explicitly covering discovering MCPs, describing them, running them, installing/uninstalling, subscribing/canceling, and managing prompts. It clearly distinguishes itself from siblings like toolkit_info, connect, and report_bug by explaining its unique centralized catalog-and-execution role.

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 when/when-not guidance: use invoke for one-off runs even when the MCP is not installed, prefer invoke for single use, use install only to make an MCP permanent, use request_mcp when nothing fits, and use search/describe to discover. It also names alternatives like list_tools and report_bug, and states the required workspace role for write operations.

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 mentions a specific behavior: including the conversation array for reproduction. It does not detail side effects, but the annotations already confirm idempotent and non-destructive behavior, so the description adds a useful hint about the input's role without contradicting 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 and well-structured: two sentences that state the purpose and provide a key instruction. No redundant or vague language.

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 no output schema, the description covers the core purpose and a critical input detail. It does not explain what happens after reporting or expected response format, but given the low complexity, it is reasonably 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 provides no descriptions for the three parameters, and the description only elaborates on the 'conversation' parameter (for reproduction). It does not clarify the meaning of 'message' (likely the bug description) or 'context', leaving the agent with incomplete understanding of required 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 purpose: reporting bugs, missing features, or feedback. It specifies the action ('report') and the target (bug/feature/feedback), making it distinct from sibling tools like 'authenticate' or 'consult'.

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 defines when to use it: when the user has a bug, missing feature, or feedback. It does not explicitly mention alternatives or exclusions, but the use cases are clear enough for an agent to choose this tool over others in the context.

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 explains important behavioral facts: the operation is billed per query, it runs via the platform without platform credentials, and it accesses only official, non-confidential Brazilian data. It also discloses LGPD responsibilities, which is important context for the agent before invoking the tool.

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 primary purpose and then adds the key operational and legal context that an agent should know. It is slightly dense and repeats 'consulta' a couple of times, but each sentence contributes meaningful 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 description handles the context around the operation well: official source, pricing, authorization model, and legal responsibility. However, it never explains how to select among the four identifier parameters, and with no output schema it also leaves the expected response format unstated. It is usable but materially 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?

With 0% schema description coverage and no required parameters, the description carries the full burden of explaining the four inputs (cpf, cnpj, chassi, renavam), but it never mentions them or says which identifier is needed. The agent is left to guess whether one or more of these fields are necessary for a valid query.

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 explicitly identifies the action and resource: 'SEFAZ MT: IPVA, consulta em fonte oficial', making clear this is an IPVA query against an official state source. It also clearly differentiates this tool from the sibling tools, which are platform/auth/utility operations rather than data lookup 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 useful usage context: it is a hosted official-source query, requires no platform credentials, is paid per query with prepaid credit, and is restricted to non-confidential, citizen-accessible information. This is clear contextual guidance, though it does not explicitly mention exclusions or alternative tools for IPVA lookup.

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 false, covering the safety profile. The description adds nothing beyond the core action, but the annotation coverage lowers the burden. It does not mention whether authentication is needed or return format, but for a version check this is acceptable.

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 that states exactly what the tool does with no filler. It is optimally 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?

Given the lack of parameters, the clear annotations (read-only, idempotent), and the simple purpose, the description fully covers what the tool does and its expected output (platform and adapter versions). Additional details like exact format are unnecessary for this trivial 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 tool has zero parameters, and schema description coverage is 100% by definition. Per the baseline for zero-parameter tools, the description need not add parameter details. The description correctly implies no input is required.

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 precisely names the action ('Show') and the specific resource ('current MCP platform and adapter versions'). It clearly distinguishes from siblings like authenticate or connect, which serve 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 a straightforward version query with no apparent conflicts. While it lacks explicit 'when to use' or 'not to use' guidance, its simplicity makes alternatives irrelevant, and the read-only nature implies safe debugging 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by defining exactly what state the read-only operation reports on and what aspects are included, without contradicting 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 a single, well-structured sentence that front-loads the action ('Returns') and then packs in the key categories of returned information without wasted words.

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 no parameters and a rich annotation set, the description is nearly complete: it tells the agent what kind of data to expect and at what granularity. It could slightly expand on return structure or edge cases, but for a zero-argument state-query tool this is sufficient.

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 description does not need to explain inputs. The baseline for a zero-parameter tool is 4, and the description appropriately focuses on what the tool returns 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 uses a specific verb ('Returns') and a specific resource ('current toolkit state'), then enumerates exactly what that state includes: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes 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 makes it obvious that this is an informational/status tool, so when to use it is implied. However, it does not explicitly mention when not to use it, nor does it point to alternatives like show_version for version-specific information.

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