SEFAZ DF: IPVA

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

The description adds useful behavioral context beyond annotations: no-args returns a login link, token input accepts a JWT for session-only access, and config-based header gives a non-expiring connection. It aligns with the idempotentHint and 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 appropriately concise, giving only necessary instruction in three sentences. The opening phrase 'MCP.AI for IDE agents (Cursor, etc.)' is slightly unclear, but the rest is direct and front-loaded.

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 authentication tool with one optional parameter and no output schema, the description covers both invocation patterns and the recommended alternative. It lacks only explicit return details and token expiry behavior for the session login.

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?

Even though schema description coverage is 0%, the description fully explains what the 'token' parameter is for ('<jwt>') and how to use the no-arg invocation to receive the login link. This compensates for the schema's lack of parameter 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 indicates the tool authenticates the user via browser and token, with explicit verb and resource ('log in', 'access token'). It distinguishes between session-only login and permanent configuration, though it doesn't explicitly distinguish itself from the 'connect' sibling.

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 clear instructions on when to use the tool: no args to get a link, or with a token to complete a session login. It also recommends an alternative permanent configuration approach (header-based). It lacks explicit guidance on when not to use this tool versus sibling 'connect'.

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 clear. The description adds value by detailing the output structure under different conditions (authenticated vs. missing credentials), which goes beyond the annotations and helps the agent anticipate responses. It 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 concise sentences, front-loaded with the core function and then providing conditional details. Every word contributes to understanding the tool's behavior, with no redundancy or fluff.

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 no output schema, the description carries the burden of explaining the return values. It covers the two main scenarios, but leaves some ambiguity around terms like 'per-install URLs' and 'pending' without further elaboration. For a simple status tool, this is sufficient, but a small nudge toward completeness would be needed for full clarity.

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 coverage is 100% (no params to document). The baseline for 0 params is 4, and the description effectively avoids the need for parameter explanations. It focuses on output semantics instead, which 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 the tool returns connection status and URLs, and explains the two primary outcomes: when all providers are connected (authenticated:true, empty pending[]) and when credentials are missing (connect_url and per-install URLs). This is a specific verb+resource with clear behavioral differentiation, distinguishing it from siblings like authenticate or 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 implies usage for checking connection status and provides context on what happens when credentials are missing (returning URLs for connection). However, it does not explicitly state when to use this tool over alternatives like authenticate, nor does it provide exclusions or prerequisites. The guidance is implicit rather than 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?

The description discloses important runtime behaviors beyond the annotations: one-off invocation without adding the MCP, connect-link sharing for credentials, checkout/retry for paid tools, owner/admin requirements for writes, installed_in_toolkit vs installed_in_workspace flags, and the fact that writes include uninstall/uninstall/cancel plus the one-off install behind invoke. This is far beyond what annotations say.

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 itself is a sprawling 23-parameter multi-capability hub, so length is generally justified. It is front-loaded with the core marketplace purpose, followed by search→describe→invoke, then install, billing, prompts, and permissions. It could be tightened, but each sentence adds behavioral or workflow knowledge.

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 and the lack of an output schema, the description is unusually thorough: it covers discovery, execution, authentication, payment, permissions, installed flags, and the prompt library. However, it is not fully complete because the schema absent 'invoke' and several prompt/tool parameters remain unexplained, so the agent cannot confidently compose a well-formed request just from this description.

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 23 parameters and 0% schema description coverage, the description must compensate, but it does not give a parameter-by-parameter mapping. It names action-search and several action values, but not the meaning of params, query, limit, prompt_access, tier_slug, report_context, conversation, etc. More importantly, it repeatedly says 'invoke runs that tool' but the action enum in the schema does not include 'invoke', leaving the agent an unresolved mapping between the described flow and the 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 explicitly identifies the tool as the mcp.ai marketplace, combining MCP discovery, execution, installation, billing, and prompt-library access. It clearly names the core actions (search, describe, invoke, install, subscribe/cancel, prompt actions) and differentiates the tool from focused siblings like report_bug or sefaz_df_ipva_consultar.

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 concrete workflow: search by intent, then describe to pick the right tool_id, then invoke to run it. It also explicitly states when to use install instead of invoke, when to use list_tools, report_bug, request_mcp, and how to handle credential/checkout cases. This is excellent alternative-based usage guidance.

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 this is not read-only, not destructive, and idempotent. The description adds useful guidance about including the conversation array for reproduction, but does not disclose what happens after submission, whether authentication is needed, or any side effects beyond the annotation hints.

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, front-loaded with the tool's purpose and followed by a practical instruction. Every word earns its place; there is no fluff or repetition of schema details.

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 three-parameter tool with annotations and no output schema, the description covers the core purpose and the key reproduction guidance. It is slightly incomplete on parameter-level semantics, but overall provides enough context for an agent to invoke the tool 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?

Schema description coverage is 0%, so the description must compensate. It explains that 'conversation' should contain recent messages for reproduction, but does not clarify the meaning of the required 'message' parameter or the optional 'context' parameter. The description also calls conversation an 'array' while the schema types it as a string, adding some ambiguity.

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 ('Report') and clearly identifies the resource: bugs, missing features, and feedback. It is immediately distinguishable from sibling tools like authenticate, connect, and marketplace, 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 description clearly implies when to use the tool: when the user wants to report a bug, request a feature, or provide feedback. It does not explicitly mention alternatives or exclusions, but no sibling tool overlaps with this functionality, so the context is sufficient.

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, destructiveHint=false. The description adds genuinely complementary behavioral context: the cost-per-query model with prepaid credit, the fact that it surfaces only citizen-available (non-confidential) data, and the client's LGPD data-controller responsibilities. One could argue it leans toward legal boilerplate rather than operational behavior, but the cost and data-origin disclosures add real 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?

Three sentences covering purpose, commercial model, and compliance fit in a compact block with no wasted words. However, the single-paragraph format buries operational info amid commercial/LGPD boilerplate, and there's no front-loading of the most decision-relevant facts. Acceptable but unpolished structure.

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 tool with 2 flat string parameters, no enums, no output schema, and strong annotations, the coverage is adequate but not thorough. The description covers data source, cost, and legal ownership but leaves gaps on input format expectations and what the response contains. Given the simple tool complexity, this is a reasonable if not generous 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?

With 0% schema description coverage and two parameters (renavam required, anos_anteriores optional), the description was expected to compensate but never mentions either parameter. The names are somewhat self-explanatory by Brazilian domain convention (renavam = vehicle registration number; anos_anteriores = previous years), but the description adds zero explanation of formats, expected values, or how to specify multiple previous years. The naming convention and common domain knowledge do most of the work, which is why this isn't a 1.

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 a query ('consulta') of IPVA data from SEFAZ DF, an official Brazilian source, matching the tool name's verb+resource. The phrase 'SEFAZ DF: IPVA, consulta em fonte oficial' provides specific verb+resource clarity. It loses a point for not explicitly stating what kind of result to expect and for requiring the reader to infer the core function from the name plus description.

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's paid per query with prepaid credit, requires no platform credentials, and the client is responsible for legitimate purpose (LGPD). However, it provides no explicit when-to-use vs alternatives, no exclusions, and no distinction from other data-querying tools. The LGPD note implies appropriate usage contexts but stops short of explicit guidance.

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 and destructiveHint=false, confirming this is a safe read operation. The description adds value by specifying what information is returned (platform and adapter versions), which goes beyond the annotations and gives the agent context about the output.

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 with no wasted words. It conveys all necessary information efficiently and is appropriately scoped for the tool's simplicity.

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, no output schema, and clear annotations indicating safety, this description is fully complete. It tells the agent exactly what the tool does, and annotations cover the behavioral aspects. There is nothing missing.

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 no parameters, the schema is trivially complete. The baseline for 0 parameters is 4, and the description doesn't need to explain any parameter semantics since there are none.

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 uses a specific verb (show) and identifies the exact resource (version information), 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 purpose is so self-evident that no explicit usage context is needed; there are no alternatives for retrieving versions. While it doesn't state when to use or not use the tool, the context is clear and unambiguous given the tool's simplicity.

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 useful detail about what state is returned but does not disclose additional behavioral traits such as freshness, latency, or potential staleness.

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, well-structured sentence that front-loads the core purpose and enumerates the return fields with no filler or repetition. 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?

The tool is simple, parameterless, and annotated as read-only and non-destructive. The description covers the main return aspects, though it omits details about output format, which matters slightly more given the absence of an output schema.

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 coverage is 100%, so there are no parameter semantics to explain. The description correctly focuses on return content rather than inputs, matching the baseline for parameterless tools.

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 clearly defines the resource ('current toolkit state') with enumerated content: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like authenticate 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 the informational purpose obvious, but it does not explicitly state when to use this tool versus alternatives such as show_version. Usage context is implied rather than directly stated.

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