ECRVSP Documentos: Transferência de Município

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

The description adds behavioral context beyond annotations, such as the permanence of header-based auth vs. session-only token login. It also clarifies that calling with no args returns a link, which is not in annotations. No contradictions with annotations are 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 three sentences, each with a distinct role: context, best practice, and alternative. It is slightly verbose but front-loaded with the tool's scope; no 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?

For a simple authentication tool with one optional parameter and no output schema, the description covers usage modes and the parameter. It doesn't mention return values or errors, but that is not critical for this tool's straightforward functionality.

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 schema coverage at 0%, the description fully compensates by explaining the 'token' parameter (JWT), when to pass it, and the no-args behavior for obtaining the link. This provides complete semantics beyond the bare 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 states the tool's purpose: authenticating IDE agents to the MCP server via browser login and token retrieval. It provides specific actions (log in, copy token) and distinguishes between permanent and session-based authentication, making it distinct 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?

The description gives explicit usage instructions, including best practice (header config for permanent connection) and alternative (paste token for session-only). It doesn't explicitly compare to sibling 'connect', but the context is clear enough for the agent to know when to invoke 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?

Annotations already mark readOnlyHint:true and idempotentHint:true. The description adds value beyond annotations by explaining the response shape under different conditions (e.g., authenticatable, pending[] empty, connect_url). This enriches the agent's understanding of expected outcomes without contradicting the read-only and idempotent 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, with the primary purpose front-loaded in the first sentence. Conditional details are concise and add necessary nuance without redundancy. 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?

Given the lack of parameters and no output schema, the description sufficiently explains the tool's behavior, including conditional returns (authenticated, pending[], connect_url, per-install URLs). While it could define 'all providers' more precisely, the description is complete for typical status-check usage and aligns with the simple nature of the 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?

There are zero parameters, so the description is not required to compensate for schema gaps. The baseline of 4 applies here, and the description appropriately focuses on return behavior rather than parameters. No additional parameter context is 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?

The description clearly states the tool 'Returns connection status and URLs,' using a specific verb and resource. It differentiates behavior based on state (all connected vs. missing credentials), making its purpose unambiguous. This distinguishes it from siblings like 'authenticate' or 'toolkit_info' without needing cross-references.

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 as a status check but does not explicitly state when to choose this over siblings like 'authenticate' or 'toolkit_info.' There is no mention of exclusions or alternatives. While the conditional behavior offers context, the description lacks direct guidance on when to invoke this tool versus others.

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, so the tool is known to be safe. The description adds meaningful context: it consults non-confidential public data ('não é dado sigiloso'), notes the client is the data controller under LGPD, and clarifies the data source is official Brazilian bodies. This goes beyond the annotations by addressing data sensitivity and compliance obligations, which is useful for the agent.

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 but packs multiple facts: purpose, hosting, payment model, data source, and LGPD responsibility. It is concise and front-loads the primary purpose. There is no fluff, though the sentence is somewhat long and could be structured better for readability. Still, it earns points for efficiency.

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 (23 parameters, 15 required) and no output schema, the description is severely incomplete. It explains the high-level purpose but provides no information about what the response contains, input constraints (e.g., required combinations like CPF or CNPJ), or how the parameters relate. The tool likely returns vehicle/municipality transfer data, but that is not stated. This is inadequate for such a parameter-heavy 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?

Schema description coverage is 0%, and the description provides no explanations for any of the 23 parameters. It does not clarify what fields like 'a3', 'a3_pin', 'login_cpf', 'login_senha', 'chassi', 'categoria', etc., mean or how they should be formatted. The description fails entirely to compensate for the lack of schema descriptions, leaving the agent guessing.

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 performs a consultation ('consulta') for municipality transfer documents ('Transferência de Município') from an official source. It is a read-only operation, which aligns with the annotations. However, it does not explicitly distinguish from sibling tools, though siblings like 'authenticate' and 'marketplace' are clearly unrelated. The verb and resource are specific enough for a 4.

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 mentions it is hosted by the platform, requires no platform credentials, and is paid per consult with prepaid credits. This provides context on how to use it (payment required) but does not provide explicit when-to-use vs. alternatives or any exclusions. It implies usage for consulting official Brazilian data, but no direct alternatives are named. This is minimal but not misleading.

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 sparse annotations (readOnlyHint=false, openWorldHint=true), the description discloses critical behaviors: invoke runs one-off even when the MCP is not installed, returns a connect link for credential needs, returns a checkout/top-up link for unpaid tools with a retry flow, and writes require workspace owner/admin. It also explains installed_in_toolkit vs installed_in_workspace flags.

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 dense and every sentence adds substance, and it front-loads the core search→describe→invoke flow before constraints. However, it is a single ~300-word unbroken paragraph with embedded 'KEY:' and 'core flow:' labels, which reduces scannability for a tool with this much surface area.

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, 0-required-param tool with no output schema and sparse annotations, the description is unusually complete: it covers the full MCP lifecycle, auth/payment edge cases, permission requirements, and the entire prompt-library subsystem. Minor gaps remain — the resume action, the immediate flag, and cancel/tier semantics are never mentioned.

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 23 parameters, the description compensates by explaining the full action enum, tool_id selection ('pick the right tool_id'), invoke arguments, prompt_vars ({{variables}} filled), and prompt_slug shareable links. However, several parameters like immediate, resume, tier_slug, and cancel_reason are not given semantics beyond their schema defaults.

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 states the tool is the 'official mcp.ai marketplace' — the catalog of every MCP/tool and the way to run them — with a clear core flow: search discovers MCPs, describe returns a full profile, and invoke runs the tool. It enumerates all 14 action values and explains the second prompt-library domain, which distinguishes it from siblings like authenticate/connect/toolkit_info.

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: 'prefer invoke for a single/occasional use' vs. 'Use install only to make an MCP PERMANENT', and 'request_mcp asks us to build a NEW MCP when nothing fits'. It also clarifies list_tools as what is callable right now, giving clear context on when to use each action.

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 neither read-only nor destructive and is idempotent. The description adds context that the conversation array aids reproduction, but it does not mention data transmission side effects, review workflow, or what happens after reporting.

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, direct and front-loaded with the tool's purpose. No filler or repeated 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?

The tool is simple with only three parameters and no output schema, and annotations provide some safety profile. Still, the description is thin on expected response behavior and does not clarify the conversation format, which may matter for reproduction use.

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 carries the burden. It only explains the purpose of the conversation parameter ('recent messages for reproduction') and calls it an array while the schema defines it as a string. The required message parameter and the context parameter receive no semantic explanation beyond obvious reading.

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 reports a bug, missing feature, or feedback, using a specific verb and resource. It is easy to distinguish from unrelated sibling tools like authenticate, show_version, 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?

It gives clear use context: report bugs, missing features, or feedback, and instructs including conversation data for reproduction. It does not explicitly say when not to use it or name alternatives, but the sibling tools are unrelated enough that exclusions are unnecessary.

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 is consistent with the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) and adds a small behavioral detail: it shows the current MCP platform and adapter versions. It doesn't go beyond what annotations already imply, and discloses no additional side effects or limitations.

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?

One concise, front-loaded sentence: 'Show the current MCP platform and adapter versions.' It is clear and direct, 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, no-output-schema read-only utility, the description sufficiently identifies its purpose and scope. It does not detail output format, but that is not necessary for the obvious—and expected—behavior of a version query 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 the input schema already reflects that, so no parameter explanation is needed. With no params the baseline is 4, and the description doesn't need to compensate for any schema gaps.

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 'Show' and clearly identifies the resource: 'current MCP platform and adapter versions.' It is clear enough, but it does not explicitly contrast with siblings like 'toolkit_info' to set itself apart from them.

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 intended use is implied by the description—if you need to check the platform/adapter versions, use this tool. However, it offers no explicit guidance about when not to use it or how it compares with other tools such as 'toolkit_info'.

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 provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds detail about the exact content of the response (connection status, accounts, tool counts), which enriches beyond annotations without contradicting them.

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?

Single concise sentence that front-loads the purpose ('Returns the current toolkit state') and enumerates specific data points. No filler or repetition.

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, no output schema, and annotations confirming read-only/idempotent behavior, the description fully covers what the tool does. The detail about the returned content is sufficient for agent comprehension.

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 rubric. The description effectively explains what the no-param call returns, leaving no 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 clearly states the tool 'Returns the current toolkit state' and lists specific data items (installed MCPs, connection status, accounts, catalog tools). This is a specific verb+resource structure, distinct from sibling tools like authenticate 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?

The description implies a clear use case for inspecting toolkit health and configuration. It does not explicitly name alternatives or when not to use, but the unique functionality is obvious among siblings, making context clear enough.

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