SEFAZ ES DEC: Caixa Postal

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

Annotations indicate readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds meaningful context: token is a JWT, session-only login vs permanent config, and no-args returns a link. It does not detail side effects or authentication failure behavior, but it goes 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?

The description is compact and front-loaded with the core action, but the second sentence is dense with semicolons and embedded alternatives. Still, every clause earns its place and the structure is understandable.

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 single-optional-parameter auth tool, the description covers all relevant invocation paths: config header, token paste, and no-args link retrieval. There is no output schema, and the response shape is only implied ('get the link'), but overall the tool is sufficiently contextualized for an agent.

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 a bare 'token' property, the description compensates by explaining that token is a JWT pasted by the user and that omitting it retrieves the login link. This clarifies optionality and purpose, though it could provide more explicit format expectations.

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 to MCP.AI for IDE agents by logging in via browser and supplying an access token. It names the resource (MCP.AI server) and the specific action (log in/authenticate), which distinguishes it from siblings like marketplace 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 gives explicit usage options: use the server config for a permanent connection, paste a token for a session-only login, or call with no args to get the login link. It provides clear context and preference ('Best:') but does not explicitly name sibling tools as alternatives, so it earns a 4 rather than 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?

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safe, non-mutating nature is covered. The description adds useful context about response content (authenticated true/false, pending array, connect_url) beyond what annotations provide. This adds some value, but the description does not go into deeper behavior like what happens when pending partial connections.

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 core purpose, and then explains conditional outputs. Every sentence adds value, no fluff. It is appropriately sized for a simple tool.

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 params, no output schema, but rich annotations and clear return behavior), the description is complete enough. It explains the two primary states and the URLs provided. Minor gap: it doesn't mention what happens when some providers are connected and others are not, which could be valuable given the sibling 'authenticate' 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, so the schema is trivially complete (100% coverage). The description provides meaning about what the tool returns without needing to explain parameters. With no params, a baseline of 4 is appropriate, and the description adds value by explaining the return semantics.

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, and provides conditional behaviors (when all providers are connected vs when credentials are missing). It distinguishes itself from siblings like 'authenticate' by focusing on status and URLs. However, it could more explicitly contrast with 'authenticate' to avoid confusion.

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 implies the tool is used to check connection status and get URLs, but does not explicitly state when to use this vs 'authenticate' or other sibling tools. The conditional behavior gives some context, but no explicit alternatives or exclusions.

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 only provide readOnlyHint=false and openWorldHint=true, so the description carries the behavioral burden. It adds important context: invoke runs uninstalled MCPs without bloating the toolkit, missing credentials return a connect link, empty wallets return a checkout link, writes require workspace owner/admin, and prompt links open without login. 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 a single dense paragraph, but nearly every sentence contributes operational knowledge. It could benefit from structure or bullets given the scope, but it avoids fluff and front-loads the primary purpose in the first sentence.

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 this broad, the description is remarkably complete: it covers discovery, one-off invocation, permanent installation, permissions, billing, connect/checkout flows, prompt library, and bug reporting. Minor gaps remain, such as no explanation of the 'resume' action and no mention of return shapes, but no output schema exists to offload that burden.

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 thoroughly explains the central action enum and its workflow, including search, describe, invoke, install, list_tools, subscribe/cancel, and the prompt-related actions. However, with 23 parameters and 0% schema description coverage, most fields like limit, immediate, tier_slug, cancel_reason, prompt_targets, and request_details receive no explanation beyond their names.

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 defines the tool as the official mcp.ai marketplace, covering both catalog discovery and execution of MCPs. It articulates a specific core flow (search → describe → invoke) and differentiates its role from the provided 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?

It gives explicit action-level guidance: prefer invoke for one-off use, use install only to make an MCP permanent, use subscribe/cancel for billing, and use request_mcp when nothing fits. It does not explicitly contrast against sibling tools like authenticate/connect, but it does explain when connect links are returned.

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 readOnlyHint=false (a write operation) and destructiveHint=false (safe). The description adds behavioral context by explaining the conversation array is for reproduction, but it does not disclose what happens after submission (e.g., ticket creation, response, or persistence). It does not contradict annotations, and with the low annotation burden, a score of 3 is appropriate—some value added beyond structured fields.

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 redundant words. It states the core purpose and provides one actionable tip (include conversation array) without fluff. Every element 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 tool has 3 parameters, no output schema, and no nested objects, the description should clarify all inputs and expected outcomes. It only covers the conversation parameter and what to report, but leaves unclear what happens after submission (e.g., confirmations, response format) and the purpose of the context field. The description is too sparse to fully guide an agent, especially for a tool that likely sends data externally.

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 the 'conversation' parameter (use recent messages for reproduction) but completely omits the 'context' parameter, leaving its purpose ambiguous. The required 'message' parameter is self-evident but not elaborated. With 3 params and only one clarified, the description fails to fully compensate for the lack of schema descriptions.

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.' It uses a specific verb ('report') and denotes the resource ('bug, missing feature, feedback'), distinguishing it from sibling tools like authenticate or show_version, which serve different functions.

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 by instructing to 'Include the conversation array with recent messages for reproduction,' suggesting the tool is for providing context to reproduce issues. However, it offers no explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites (e.g., must be authenticated). The guidance is minimal but present.

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 behavior, and the description adds meaningful context about payment, hosting, official data, and LGPD responsibility. However, it does not explain the actual behavior around the credential-related parameters or the meaning of ignoring read/unread messages, which would add useful transparency.

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 short, front-loaded with the core purpose, and each sentence adds distinct value: purpose, platform/payment context, and legal/usage caveat. No unnecessary repetition or filler.

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 parameter complexity, 0% schema coverage, and no output schema, the description is materially incomplete. It explains the nature of the data and commercial terms but not how to invoke it or what the caller must provide, so the description is insufficient for confident tool 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 description provides zero parameter-level guidance, and schema description coverage is 0%. The eight parameters such as ie, login_senha, pkcs12_cert, and ignorons/not_leave are not explained at all. An agent cannot determine which parameters are needed, how they should be formatted, or which combinations are valid.

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 an action and resource: consult the SEFAZ ES DEC 'Caixa Postal' in an official source. It also distinguishes itself from the generic sibling tools by framing this as an official-source data query rather than an authentication or platform utility.

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 contextual guidance: it is a paid per-query service, hosted by the platform, using prepaid credits, and it accesses the same non-confidential data available to the citizen. It does not explicitly name alternatives or exclusion scenarios, but the sibling tools are generic and unrelated, 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?

The annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds no extra behavioral context beyond stating the purpose, which is sufficient given 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, concise sentence with no unnecessary detail, well-structured for quick understanding.

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 has no parameters and no output schema, the description fully specifies its purpose. It is complete and sufficient for a simple version check.

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 no parameters, and schema coverage is 100%. The description does not need to explain parameters; baseline is 3.

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 the current MCP platform and adapter versions. It is specific and distinguishes from sibling tools like 'connect' 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?

The description implies usage for checking versions but does not explicitly state when to use it versus alternatives (e.g., 'toolkit_info'). It lacks clear contextual 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 readOnly, idempotent, and non-destructive behavior. The description adds no side-effect details, but it is consistent with these annotations and does not introduce ambiguity.

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, focused sentence that conveys all necessary information without redundancy or extraneous detail.

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?

Even without an output schema, the description explicitly lists the type of information returned (installed MCPs, connection status, accounts, catalog counts), providing sufficient context for expected results.

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 absence of parameter documentation is appropriate and does not hinder understanding.

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 enumerates specific components (installed MCPs, connection status, accounts, catalog counts), making its purpose unambiguous and distinct from sibling tools 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 a read-only status retrieval use case, but does not explicitly contrast with when to use other sibling tools. Given the clear name and purpose, it is still easy to infer appropriate usage.

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