SEFAZ PE DEC: Caixa Postal

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

The behavior of accepting a token for a session-only login and returning a link when called with no args is disclosed, complementing the annotations. The description does not contradict the annotations and adds practical detail about the session vs. permanent distinction beyond what annotations express.

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 few sentences and front-loads the key login flow before offering options. It is somewhat verbose with configuration advice, but every sentence provides useful guidance for correct use.

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 one optional parameter, no output schema, and no required fields, the description covers the necessary cases: no-args returns link, token arg logs in for the session, and permanent config is an alternative. It is complete enough for a simple authentication tool and matches the complexity presented in the schema and annotations.

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 provides only a 'token' string with no description, so the text compensates by giving exact invocation shape: { token: "<jwt>" } or no arguments. This clearly explains the parameter's role, although it could go slightly further in specifying whether the JWT is literally the string copied from the browser.

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: authenticating an IDE/MCP.AI user by getting a login link or accepting an access token. It distinguishes the permanent-config vs session-only login approaches but does not explicitly differentiate from the sibling tool 'connect', so it misses the top score.

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 concrete context: use the server config header for a permanent non-expiring connection, or call this tool with a token for session-only login, or call with no args to get a link. It provides clear conditional usage but does not explicitly state when not to use this tool instead of a sibling.

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. The description adds valuable behavioral details: it returns authenticated:true and empty pending[] when connected, and connect_url and per-install URLs when credentials are missing. This clarifies the output variations, going 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?

Two concise sentences convey the core behavior and conditional outcomes. No fluff, front-loaded with the main purpose. Highly efficient.

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 parametersable and a read-only, idempotent tool with rich annotations, the description covers the essential behavior: success state and missing-credential state, including the return fields. It's complete for its simplicity, and no further explanation is needed.

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 (schema coverage 100% trivially). Per the baseline for 0 params, score is 4. The description doesn't need to explain parameters, and it doesn't.

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: 'Returns connection status and URLs.' It specifies the resource (connection status) and the output. It distinguishes from siblings like 'authenticate' (which likely initiates connections) by focusing on status reporting. The title 'Connection Status' reinforces the purpose.

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 explains two distinct scenarios (all providers connected vs. missing credentials). It doesn't explicitly contrast with alternatives like 'authenticate', but the context makes it clear this is for status checks. Provides adequate guidance without explicit 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?

Beyond annotations (readOnlyHint false, openWorldHint true), the description discloses that writes require owner/admin, invoke works even if MCP not installed, and describes return behavior for credential/payment cases (connect link, checkout link). This adds valuable non-obvious behavioral details.

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 overly long and rambling, mixing languages (Portuguese) and repeating concepts (e.g., credential/payment details are stated twice). It lacks a clear hierarchical structure, making it harder to parse despite 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?

While the description covers high-level flows (invoke, install, etc.), it omits details for many parameters and actions, especially the prompt-related ones (search_prompts, get_prompt, publish_prompt). It does not address output schemas or expected return structures, leaving the tool context incomplete for effective 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?

The input schema has 23 parameters with no descriptions, and the description does not explain any of them (e.g., prompt_body, tool_id, cancel_reason). It mentions 'id + params' in the describe flow but fails to clarify what each input parameter means or how they map to actions, leaving parameter semantics largely unexplained.

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 states the tool is the official mcp.ai marketplace, the in-platform catalog of MCPs/tools, and explains the core flow (search, describe, invoke). It is a specific verb (marketplace) with resource (MCPs and prompts) and distinguishes from siblings by covering both tools and prompts.

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 conditional guidance: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use.' It also explains when invoke works without installation and notes permission requirements for writes, which helps decide when to use this tool versus alternatives.

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 idempotentHint=true and readOnlyHint=false, which are consistent with a feedback-reporting tool. The description adds the conversation array hint but doesn't describe return behavior or error cases. No contradiction found.

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 concise sentences, front-loaded with purpose and a key usage hint. No waste.

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, but the description doesn't mention expected response or post-action behavior. Since there's no output schema, some explanation of what happens after reporting would be helpful. It mentions the conversation array but not other params. Adequate but not 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%. The description only hints at the conversation parameter, leaving message and context unexplained. It does not fully compensate for the schema's lack of 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 purpose: reporting a bug, missing feature, or sending feedback. It also provides a specific instruction on what to include (conversation array) for reproduction. This makes the tool's function immediately obvious.

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 to include the conversation array for reproduction, which is helpful. However, it does not specify when to prefer this tool over alternatives, but given the tool list, it's unique for reporting issues.

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, and the description adds valuable context: hosted by the platform without platform credentials, requires prepaid payment, confirms data is not confidential, and clarifies client responsibility under LGPD. This extends beyond the annotations without contradiction.

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, front-loading the core purpose in the first clause and adding necessary context in a few sentences. It avoids redundancy and is structured logically, though it omits parameter details that would be valuable.

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 there is no output schema, the description should explain what the query returns and ideally cover parameter usage. It provides operational context (payment, data status) but misses essential invocation details, leaving significant gaps for an agent to correctly use 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?

The schema has 0% description coverage for its 5 parameters, and the description provides no explanation of any parameter (e.g., nome, raiz_cnpj, pkcs12_cert, etc.). The required certificate fields are implied by naming, but the description does not clarify their roles or format, failing to compensate for the lack of 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 states the tool performs a 'consulta' (query) for 'Caixa Postal' from SEFAZ PE DEC, an official Brazilian source. This distinguishes it from generic sibling tools like authenticate or connect, making the purpose unmistakable.

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 use for querying official mailbox data and mentions payment per query with prepaid credit, but it does not explicitly state when to prefer this over alternatives or when not to use it. No exclusions are given, but the context (official, non-confidential data) hints at appropriate use cases.

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 read-only, idempotent, and non-destructive behavior. The description adds the word 'current' but provides minimal extra behavioral context beyond what the annotations convey, aligning with the baseline for annotated tools.

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 directly states the tool's function without any fluff, unnecessary details, or 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 that there is no output schema, the description sufficiently indicates that the tool returns version information. The simplicity of the tool (no parameters, no complex behavior) means this level of detail is complete for a user to know what to expect.

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 schema coverage is 100%. The description does not need to explain parameters, and per the rubric, a baseline score of 3 is appropriate when no parameter details are 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 explicitly states the tool shows current MCP platform and adapter versions, which is a clear and specific action. It distinguishes itself from sibling tools 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's use case is self-evident; it is used to retrieve version information. Since there are no similar sibling tools that return versions, no explicit alternatives are needed, and the description implicitly guides when to use it.

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 and idempotentHint, covering safe usage. The description adds specific details about what is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotation and gives a clearer picture of the tool's behavior. It does not mention any side effects, but consistency with annotations and the explicit 'Returns' phrasing ensure 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 a single, well-structured sentence that lists all key return elements without redundancy. It is concise, avoids unnecessary words, and directly conveys the essential information. No fluff or extraneous details are present.

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?

Since there is no output schema, the description must explain what the tool returns, and it does so comprehensively. It specifies the exact components of the toolkit state: installed MCPs, their connection status, connected accounts, and catalog tool counts. This provides a complete picture for a user to understand the tool's output without additional 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 tool has no parameters, so schema coverage is 100% by definition. The baseline for high coverage is 3, and the description does not add parameter-related information (as there are none). It does not need to compensate for missing schema details because there are no parameters to describe. Thus, the description adds no parameter semantics beyond the schema, earning the baseline score.

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 the current toolkit state, enumerating specific details (installed MCPs, connection status, accounts, catalog tool counts). It uses the verb 'Returns' and names the resource, making the purpose unambiguous and distinguishing it 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 implicitly communicates when to use the tool (to inspect the toolkit state), but it does not explicitly state usage scenarios or contrast with alternatives. While the purpose is clear, there is no direct guidance on when not to use it or when another tool might be more appropriate. This is slightly below the high benchmark that explicitly mentions filtering and alternative tools.

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