Receita Federal PF

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

Beyond the idempotentHint, the description explains the lifecycle of the token: a permanent connection via config header vs a session-only login when pasted. It also clarifies that calling with no args returns a login link, adding useful context not captured in 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 with three sentences. It conveys necessary information but includes external setup advice (config header) that could be considered outside the tool's immediate scope, making it slighty verbose. Still, each sentence carries value.

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 simple schema and lack of output schema, the description covers the main call patterns (no-args and token). However, it does not explicitly describe the response format, success/failure indicators, or edge cases like invalid tokens, which would be helpful for an auth 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 only lists an optional 'token' property with no description. The description compensates by explaining the token is a JWT pasted by the user and that omitting it (no args) retrieves the login link. This gives clear meaning to the parameter and the no-arg case.

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: 'log in in the browser, copy the access token' and authenticate for IDE agents. It specifies the resource (MCP.AI for IDE agents) and the action, making it distinct from generic 'connect' or other tools, though it does not explicitly contrast with siblings.

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 explicit instructions on when to use each call mode: 'Best: add it to this server's config as a header... for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' This clearly explains alternatives and the best practice.

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 read-only, idempotent, non-destructive behavior. The description adds meaningful detail about return value shapes in different states (authenticated:true with empty pending[], or connect_url and per-install URLs), which is 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?

Two sentences deliver complete information without redundancy. The first sentence gives the core purpose, and the second explains conditional behavior, all in a compact format.

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?

Despite having no output schema, the description adequately covers the main return scenarios and edge cases. For a status-check tool with no parameters, this is sufficient for an agent to select and invoke it 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?

The tool has zero parameters, so the baseline is 4. The description correctly focuses on outputs rather than inputs, and no parameter documentation 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, with specific behaviors for connected vs missing credentials. It distinguishes itself from the sibling 'authenticate' tool by focusing on status retrieval rather than establishing authentication.

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 explains the two main scenarios (all providers connected vs credentials missing) and what the return values indicate, giving context on when this tool's output is useful. However, it does not explicitly name alternatives or when not 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?

Despite annotations being present (readOnlyHint=false, openWorldHint=true), the description goes well beyond them by disclosing key behavioral nuances: invoke works even when the MCP is not installed, runs one-off without bloating the toolkit, returns connect links for credentials and checkout links for payment, and mentions permission requirements for writes. This provides substantial context that annotations alone don't convey.

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 densely packed with valuable information, but it is quite long and runs as a single block of text without clear paragraph breaks. It front-loads key concepts but could benefit from structure to enhance scannability, though it remains informative and not redundant.

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 is exceptionally complete for a complex tool with 23 parameters and no output schema. It covers the main action flow, operational details (one-off invocation vs permanent install), auth/payment hurdles, permission requirements, and the prompt library sub-feature, leaving little ambiguity about how to interact with 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?

With schema description coverage at 0%, the description compensates thoroughly by explaining the core action parameter and its values (search, describe, invoke, install, etc.), the flow from search to describe to invoke, and the purpose of prompt-related parameters. While not every parameter is detailed, the description maps the main action-based semantics, which is critical for correct usage.

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 is a comprehensive overview of the marketplace tool, clearly stating it's the official mcp.ai marketplace for discovering and running MCPs/tools. It distinguishes itself from siblings by covering capability requests, the core flow (search → describe → invoke), and the prompt library, making it unmistakable what this tool does and how it differs from other 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 explicit when-to-use guidance: prefer invoke for single/occasional use, install only for permanent addition, list_tools for currently callable tools, and subscribe/cancel for billing. It also mentions prerequisites like workspace owner/admin for writes and scenarios where invoke returns connect/checkout links, and alternatives like request_mcp when nothing fits, giving clear decision criteria.

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 read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond these: payment requirements, public data classification, and LGPD compliance. This helps an agent assess suitability and legal responsibilities.

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 main purpose is front-loaded in the first sentence. The following sentences add operational (payment, hosting) and legal (public data, LGPD) context without redundancy. It is slightly longer than strictly necessary but every sentence carries 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 tool is simple, and annotations cover safety. The description covers purpose, inputs, payment, and legal constraints. However, it lacks any description of the return value (no output schema) and leaves the 'completo' parameter unexplained, creating meaningful gaps.

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 explains the role of CPF and DataNascimento as inputs, aligning with required schema fields. However, it does not clarify the optional 'completo' boolean parameter, and no format constraints or examples are given. With 0% schema coverage, this is a partial gap.

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 action: consulting the registration status of an individual in the Federal Revenue using CPF and birth date. This specific verb+resource+input distinguishes it from sibling tools like authenticate 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 description provides rich context on when to use the tool: hosted by the platform, no credentials required, pay-per-query with prepaid credit, and it accesses public data. It does not explicitly mention alternatives, but the usage context is clear and actionable.

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 provide idempotentHint:true and destructiveHint:false, so safety profile is covered. The description adds the instruction to include conversation for reproduction, which is helpful, but does not explain outcome, authentication needs, or other behavioral traits. 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?

Two concise sentences, front-loaded with purpose, no wasted words. It earns its place by adding the reproduction instruction.

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 bug-report tool with annotations, the description is adequate but gaps remain: 'context' parameter is undocumented, conversation type mismatch is not clarified, and no indication of expected response. These gaps reduce completeness.

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 description must compensate. It covers 'conversation' and 'message' partially, but calls 'conversation' an array while the schema declares it as a string (default '[]'). 'context' is left unexplained, introducing potential invocation errors.

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?

Description states 'Report a bug, missing feature, or send feedback' with specific verbs and resource. This clearly differentiates from sibling tools (authenticate, connect, etc.) which serve unrelated 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 implies when to use the tool (when reporting issues), but provides no explicit when-not-to-use guidance or alternatives. It does not mention exclusions, so usage is implied 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds the qualifier 'current' and specifies that it covers both platform and adapter versions, which is useful, but it does not disclose additional behavioral traits like return format or whether it performs any network calls. The annotations carry much of the transparency burden.

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 filler. Every word ('current', 'MCP platform', 'adapter versions') contributes to the meaning.

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 zero-input, read-only version-checking tool with strong annotations, the description is adequate. It does not explain the return format, but that is not essential for a tool whose sole purpose is to report versions. The description fully conveys the tool's scope.

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 schema-description coverage is 100%. Per rubric, zero parameters receive a baseline of 4. The description does not need to explain any parameters 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 uses the specific verb 'show' and names the exact resource ('current MCP platform and adapter versions'). This clearly distinguishes it from sibling tools like 'authenticate' or '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 implies usage (when you need to know current versions) but does not explicitly state when to use this tool versus alternatives. It also does not mention any exclusions or point to sibling tools like 'toolkit_info' for broader system 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 declare readOnlyHint, idempotentHint, and destructiveHint. The description adds context by enumerating what state is returned (installed MCPs, connection status, accounts, tool counts), enriching the agent's understanding 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 a single, front-loaded sentence that lists the information returned without redundancy. Every word adds value.

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, zero-parameter info tool with no output schema, the description fully explains the return contents (installed MCPs, connection status, accounts, catalog tool counts), making it 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 tool has zero parameters, so the baseline is 4. There is nothing for the description to add beyond what the schema already provides (an empty 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 uses specific verb 'Returns' and resource 'current toolkit state' and details the exact contents (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from siblings like connect 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 clear usage context for retrieving toolkit state, which is sufficient given the tool's read-only nature. It does not explicitly mention alternatives, but the context is clear and no exclusions are needed.

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