Receita Federal: Cafir

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

Annotations already indicate idempotentHint true and destructiveHint false, but the description adds important behavioral context: permanent vs. session-only authentication, and that the token does not expire when added to config. This goes 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?

The description is a single sentence with multiple clauses, but it is well-structured with clear separators (') and enumerations. Every part contributes to explaining the tool's behavior. Though a bit lengthy, it is efficient and front-loaded with the purpose.

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 one optional parameter and no output schema, the description covers all necessary details: how to obtain the token, the two authentication modes, and the effect of calling with or without arguments. Complete enough for an agent to invoke correctly 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 schema only defines an optional 'token' property with no description. The description clearly explains that providing a token performs session login, while omitting it returns a link. This adds essential meaning that the schema lacks, compensating for the 0% schema description coverage.

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: authenticate to MCP.AI for IDE agents. It specifies the mechanism (browser login, token retrieval) and distinguishes two use cases (permanent config header vs. session token). This is specific and distinct from sibling tools like 'connect', which likely handles a different action.

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 and how to use the tool: log in via browser, copy token, and either add to server config for permanent access or pass as a token parameter for session login. It also mentions calling with no args to get the login link. This leaves no ambiguity about 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?

The description adds behavioral detail beyond the annotations, specifying the exact output structure under different conditions (authenticated:true with empty pending[], or connect_url for toolkit and per-install URLs). This complements the readOnlyHint and idempotentHint annotations, which already indicate a safe, idempotent read operation. No contradiction with the annotations is 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 extremely concise, consisting of two sentences that immediately state the tool's primary purpose. It front-loads the main action and then elaborates on expected outcomes with no wasted words. Every sentence contributes to understanding the tool's behavior.

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, read-only, clear output states), the description provides all necessary context. The annotations cover safety and idempotency, while the description explicitly details the return values and the conditions that trigger different responses. The absence of an output schema is adequately compensated by the description's mention of key fields like authenticated, pending, and connect_url.

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 for the description to explain about parameters. The baseline for zero-parameter tools is 4, and the description correctly avoids adding any redundant parameter information. The schema coverage is effectively 100% since no properties exist, so the description is not required to compensate.

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's function: returning connection status and URLs, with specific details on the two primary outcomes. This clearly distinguishes it from sibling tools like authenticate or marketplace, which serve different purposes. The resource is unambiguous ('connection status' and URLs).

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 what the tool does but does not provide explicit guidance on when to use it versus alternatives. It implies it is for checking connection status, but lacks a clear 'use this when...' statement or any mention of alternative scenarios. No exclusions or recommended usage contexts are included.

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 goes far beyond the sparse annotations (readOnlyHint=false, openWorldHint=true). It discloses the key behavioral twist that invoke runs a one-off without installing or bloating the tool list, the credential edge case (returns a connect link), the payment edge case (returns a checkout link and you retry), the flagging of installed_in_toolkit vs installed_in_workspace, and the admin permission model for writes. These are exactly the side-effects an agent needs to know and are not derivable from 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?

Every sentence earns its place and the density is justified by 14 distinct actions, but the content is delivered as one unbroken wall of text with no bullets, breaks, or headers. The critical distinction (invoke runs one-off vs install makes permanent) is buried mid-paragraph. Information-to-word ratio is high, but scannability for an agent parsing quickly suffers from the lack of structure.

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 of this complexity — 14 actions, 23 params, zero annotations beyond safety hints, no output schema — the description is remarkably complete. It covers the full action surface (core flow, billing, bug reporting, MCP requests, prompt library), addresses return behaviors for key paths (connect link, checkout link, shareable mcp.ai/p/<slug> link), and handles permission and edge cases. Minor residual gaps: exact return formats aren't uniform and a few params remain undefined, but this is strong coverage for the complexity level.

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 across 23 params, the description carries the full compensation burden. It does a strong job on the most important param — action — by narrating each enum value's behavior, and it contextualizes tool_id, arguments, mcp_id, tier_slug, and the prompt_* family through the flow explanations. However, several parameters get zero treatment: message, immediate, conversation, query, and limit are never explained, leaving gaps in a 23-parameter dispatcher.

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 unmistakably specific: it's the official mcp.ai marketplace catalog plus the execution engine for MCPs, with a secondary prompt library. It names exact verbs and resources ('search discovers MCPs by intent', 'describe returns one MCP's full profile', 'invoke RUNS that tool'), and it clearly separates the marketplace domain from the sibling tools (connect, authenticate, show_version). The sheer breadth is organized into a coherent purpose instead of a vague blob.

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?

Outstanding when/where guidance. It prescribes the core flow ('search → describe → invoke'), gives the pivotal decision rule ('Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use'), names alternatives explicitly ('To filter by user...'), and states permission prerequisites ('Writes require workspace owner/admin'). It even enumerates user-intent scenarios ('find an MCP that does X', 'consulta um CPF') that map to the search 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 declare readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context beyond annotations: billing model, lack of platform credentials, official-source data classification, non-confidential nature, and LGPD responsibility. 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 at three sentences and front-loads the core purpose. The billing and LGPD details add useful context, though the legal sentence is somewhat dense. Overall, it is well-structured without significant 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 with one parameter and no output schema, and annotations cover the safety profile. However, the description does not explain the required 'cib' parameter or what the response contains, leaving meaningful gaps for an agent attempting first-time 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 input schema has one required parameter, 'cib', with no description and 0% schema description coverage. The tool description never mentions 'cib', its meaning, format, or expected values, leaving the agent without enough information to construct a valid query.

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') of CAFIR data from the official Receita Federal source. This specific verb+resource combination distinguishes it from the generic sibling tools like authenticate, connect, and 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 provides clear operational context: it is hosted by the platform, requires no platform credentials, and is paid per query with prepaid credit. It does not explicitly name alternatives or exclusions, but the context is sufficient for an agent to understand when this tool is appropriate.

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 cover non-destructive and not read-only behavior, and the description adds that the conversation array is needed for reproduction. However, it doesn't explain what happens after reporting, whether a ticket is created, retry effects, or whether data is sent externally, so the behavioral picture is incomplete.

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-loaded: two sentences communicate the purpose and the key usage instruction without 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 simple flat submission tool with one required parameter and no output schema, this description provides enough context for basic invocation. It would be stronger if it mentioned expected return behavior and conversation formatting, but the core use case is adequately covered.

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 meaningful guidance by explaining that the conversation array is used for reproduction. However, schema description coverage is 0%, and the description doesn't clarify the 'context' parameter, and it calls conversation an 'array' while the schema declares it as a string, leaving serialization 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 uses a specific verb, 'Report', and concretely lists the accepted subject matter: bugs, missing features, and feedback. This makes the tool's purpose immediately clear and distinguishes it from siblings like show_version or receita_federal_cafir_consultar.

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 clearly indicates when to use the tool: when users need to report a bug, request a missing feature, or send feedback. It doesn't explicitly name exclusions or alternatives, but the context is clear enough for an agent to select it appropriately.

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, covering the safety profile. The description adds no extra behavioral detail beyond stating the purpose, which is consistent with the annotations but does not provide additional context such as output format or performance. This meets the baseline when 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?

A single concise sentence that communicates the tool's purpose without any wasted words or redundant information. It is appropriately front-loaded and effectively structured.

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 is fully adequate. It clearly states what the tool does, and the annotations cover safety. There is no missing information that would hinder an agent's decision to call this 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 input schema is empty. Per the rubric, a 0-parameter tool gets a baseline of 4. The description does not need to explain parameters, and the schema coverage is 100% (trivially).

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: 'Show the current MCP platform and adapter versions.' This is a specific verb ('show') with a specific resource ('versions'), and it distinguishes from siblings like connect or marketplace, though it could be confused with toolkit_info if that also provides version info, but the purpose is explicit.

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 provides no explicit guidance on when to use it versus alternatives like toolkit_info. No exclusions or context are given, so it relies on the tool's name and description to infer when it's appropriate.

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, so the safety profile is covered. The description adds value by specifying exactly what state information is returned (installed MCPs, statuses, accounts, catalog tool counts), which goes beyond the 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, well-structured sentence that is front-loaded with the core purpose and then lists the specific items. Every word contributes useful information, with zero fluff 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 simple, read-only tool with no parameters and no output schema, the description provides a clear and sufficient overview of the return content. It could potentially mention response format or error handling, but for this low complexity, it is almost 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 there is nothing to explain. Per rubric, a 0-parameter tool baseline is 4. The empty schema is fully covered, and no additional parameter semantics are 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 uses a specific verb ('Returns') and explicitly names the resource ('current toolkit state'), then enumerates the key components (installed MCPs, connection status, accounts, catalog tool counts). This clearly distinguishes it from sibling tools like connect or authenticate, which are action-oriented.

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 its use for inspecting the toolkit environment and checking connection/account status, which is a clear context. However, it does not explicitly state when to avoid using it or point to alternatives, so it stops short of a perfect 5.

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