Receita Federal: Comprovante de Pagamento

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

Annotations already indicate idempotent and non-destructive behavior. The description adds useful context about the browser login flow, permanent non-expiring config vs session-only login, and the difference between supplying a token and calling with no args. It does not detail failure responses, but the safety-critical traits are covered.

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 mostly front-loaded, conveying the auth flow and both invocation modes in three sentences. The 'MCP.AI for IDE agents (Cursor, etc.)' opening is slightly noisy and 'paste it here' is a bit ambiguous in a tool-call context, but there is no meaningful 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?

For a simple tool with one optional parameter and no output schema, the description sufficiently covers auth modes, token semantics, and the no-args behavior. The return shape is not stated, but the description already explains that no args yields the login link, making this a minor gap.

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 zero description coverage for the only parameter, token, but the description compensates: token is a JWT used for session-only login, and omitting it returns the login link. This is enough to understand the parameter's role and optionality.

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: logging in via browser, copying the access token, and supporting either permanent header-based auth or session-only token auth. It does not explicitly contrast with the sibling 'connect' tool, so it stops short of full sibling differentiation.

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: 'Best: add it to this server's config as a header' for permanent access, or 'paste it here' for session-only login, with 'call with { token }' or 'no args to get the link'. This clearly explains when and how to use each mode.

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. The description adds meaningful behavioral context beyond annotations by explaining the two possible response states and what fields/URLs are returned in each. This is useful without being excessive.

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 and every clause earns its place. It front-loads the core purpose and immediately provides the conditional details an agent needs to interpret the response correctly.

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?

There is no output schema, so the description bears responsibility for explaining return values. It does explain the two main response modes and key fields (authenticated, pending[], connect_url). It could be slightly more explicit about the exact URL semantics, but for a simple zero-parameter read-only tool it is adequate and complete enough.

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 description coverage is 100%, so the schema fully documents the input surface. Per the baseline for zero-parameter tools, a score of 4 is appropriate; the description does not need to compensate for parameter 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's function: 'Returns connection status and URLs.' It distinguishes this from the sibling 'authenticate' by describing informational output rather than an authentication action. The two state conditions (all connected vs. missing credentials) provide concrete specificity.

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 context on when different outputs occur: when all providers are connected versus when credentials are missing. It does not explicitly name alternatives or say when not to use this tool, but the context makes the read-only status-checking usage apparent, especially alongside the 'authenticate' 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 only convey generic safety hints, but the description adds critical behavioral context: invoke runs tools even when the MCP is not installed, missing credentials return a connect link, empty wallets return a checkout/top-up link, writes require workspace owner/admin, and prompt share links open without login. There is 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 long but information-dense and logically structured: definition, core flow, invoke-specific behavior, install vs invoke, permissions, then the prompt library. It earns most of its length, though a little more paragraph separation would improve scannability.

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 very complex multiplexer with 23 parameters, no schema descriptions, and no output schema, this description covers the main intents, prerequisites, auth/billing failure modes, permissions, and result-link behavior. It is unusually complete for such a broad 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 23 parameters and 0% schema description coverage, the description must compensate — and it does by semantically explaining most action enum values and their roles in the workflow. However, it does not explain several parameters such as limit, tier_slug, immediate, cancel_reason, or prompt_vars in detail, leaving some meaning to be inferred from parameter 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 states the tool is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' and then enumerates the full search→describe→invoke flow plus prompt-library operations. It is specific about what the tool does and differentiates its role from narrower siblings like report_bug 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?

It provides explicit when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', and explains when to use subscribe/cancel, report_bug, request_mcp, search_prompts, and get_prompt. The core flow (search → describe → invoke) gives a clear decision path.

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, but the description adds meaningful behavioral context: it clarifies that the tool queries official public sources (non-sensitive data) and is hosted on the platform without platform credentials, requiring prepaid credit per query. It also contains LGPD data controller responsibilities, which are important for compliance. There is 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 concise and front-loads the core purpose, but it spends multiple sentences on legal and compliance disclaimers (LGPD, data controller) that are secondary to usability. While these add important context, they crowd out more critical operational details such as parameter guidance. The structure is functional but could be more focused.

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 (10 parameters, no output schema, no param guidance), the description is incomplete. It clarifies the data source and compliance aspects, but leaves the agent with no clear understanding of how to invoke the query (e.g., which credentials to supply, date formats, or the meaning of fields like codigo_receita). For a complex tool with zero schema descriptions, this is insufficient.

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 10 parameters, but schema description coverage is 0%, and the description provides no parameter-level details. The names (e.g., login_cpf, pkcs12_cert, codigo_receita) are opaque in Portuguese and lack any explanation of format, meaning, or relationships. This tool fails to compensate for the complete lack of schema description, offering no value beyond the raw parameter list.

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: to query payment receipts from the Brazilian Federal Revenue (Receita Federal) via an official source. It distinguishes itself from siblings by specifying the 'comprovante de pagamento' (payment receipt) use case and the formal/institutional nature of the tool, which is not evident in the sibling names.

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 conveys usage context by mentioning that it's a paid per-query service with prepaid credits and that it queries official Brazilian sources. However, it does not explicitly state when to use this tool over alternatives (e.g., other receipt or tax tools) or provide any exclusions. The absence of direct guidance on when not to use it and the lack of mention of alternative tools makes it only adequate.

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 emphasizes including conversation data for reproduction, which transparently signals that the tool transmits user conversation content. This adds beyond the annotations (idempotent, non-destructive) by disclosing data handling. However, it does not mention any side effects like sending network requests or storing data, but the hint about reproduction covers the key behavioral aspect.

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: the first states the purpose, the second gives a usage hint. It is concise, front-loaded, and free of unnecessary details. Every sentence adds value without 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?

The tool is relatively simple (three params, no output schema), but the description omits critical details like what 'context' means and what the return/outcome of reporting is. It also does not explain the expected format for the conversation array. Given the moderate complexity, the description is not fully complete for autonomous usage.

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 includes three parameters (context, message, conversation) with no per-field descriptions. The description only clarifies the 'conversation' parameter as an array for reproduction, while 'message' and 'context' remain unexplained. This leaves significant ambiguity for an agent, especially since 'message' is required and its semantics are not stated.

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.' This is a specific verb-resource combination and distinguishes it from sibling tools like authenticate or show_version. It also covers multiple related intents (bug/feature/feedback) succinctly.

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 a usage instruction: 'Include the conversation array with recent messages for reproduction.' This tells the agent how to use the tool effectively. However, it lacks explicit guidance on when to use this tool versus alternatives, though no sibling tool serves a similar purpose, so the context implies usage.

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 extra behavioral context beyond the annotations, so it does not go beyond what the annotations provide.

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 action. There is no unnecessary wording or ambiguity.

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 version-check tool with no parameters and no output schema, the description is complete enough. It tells the user what the tool does, and since the output is likely a straightforward version string, no further explanation is necessary.

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 there is nothing to explain. The absence of parameters is simple and the description does not need to compensate; this is a natural 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 clearly states the tool's function: it shows the current MCP platform and adapter versions. The verb 'show' and specific resource 'versions' make the purpose unambiguous, and it is distinct from sibling tools like authenticate or report_bug.

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 (checking version info) but does not explicitly state when to use it or alternatives. Given its simplicity, the context is clear enough, but there is no explicit guidance on when to prefer this over another 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?

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering behavioral traits. The description merely states it 'returns' state, which is consistent but adds no extra transparency 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, well-structured sentence that lists the exact information returned. It is concise and directly to the point without unnecessary 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?

Given the tool's simplicity (no parameters, no output schema), the description fully conveys what the tool does and what it returns. It is complete for the intended use case.

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 there is nothing to explain. The description does not need to elaborate on parameter meanings, and the schema coverage is effectively perfect.

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 precisely states the tool's function: returning the current toolkit state with specific details (installed MCPs, connection status, accounts, catalog counts). This clearly distinguishes 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 implies usage for retrieving state information but does not explicitly mention when to use it over alternatives. However, the purpose is self-evident, and the tool has no parameters, making its use straightforward.

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