Receita Federal: Simples (Emissão de DAS de MEI)

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

Annotations already declare the tool as idempotent and non-destructive, and the description adds behavioral details: it explains that calling with no args returns a link, and providing a token enables session-only login. It doesn't contradict the annotations and adds context about the two operational modes.

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, moderately dense paragraph but remains clear and structured with a 'Best:' vs 'Or' breakdown. It isn't overly verbose, though it could be slightly more organized with breaks; still, it's 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?

For a simple tool with one optional parameter and no output schema, the description covers the essential behaviors: how to obtain a link, how to use a token, and the difference between permanent and session logins. It's complete enough for an agent to use 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?

Although the schema only declares a string 'token', the description fully explains its meaning and optionality: it can be omitted to get a link, or provide a JWT for session login. This goes well beyond the schema and gives clear semantics for the single parameter.

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: authenticate the user by either providing a JWT token or obtaining a browser login link. It uses specific verbs like 'log in' and 'call with { token } or no args', and it distinguishes this authentication tool from sibling tools like 'connect' or 'marketplace' by focusing solely on 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 provides explicit usage context: it explains the two modes (permanent via config header vs session via token parameter) and instructs when to call with no args to get the link. It doesn't explicitly state when NOT to use, but the guidance is clear enough for an agent to decide.

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, so the description adds value by explaining conditional output details: authenticated:true with empty pending[] when all connected, or connect_url and per-install URLs when credentials missing. 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 with no filler. The main action is front-loaded, and each sentence adds meaningful behavioral 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?

Although there is no output schema, the description covers both main return states (connected and missing credentials) and includes the relevant URLs. For a zero-parameter status tool, this is 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?

There are zero parameters, and the schema coverage is 100% (empty schema). The description correctly avoids inventing parameter details, so baseline 4 is appropriate.

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 (specific verb+resource). It also distinguishes from siblings by describing scenario-specific behavior (all providers connected vs. missing credentials).

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 context on when to expect certain outputs, implying use for status checks. However, it does not explicitly mention when to prefer alternatives like authenticate.

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 annotations, which only indicate non-read-only and open-world. It discloses that invoke runs without installing the MCP, may return connect or checkout links that require user action and a retry, and that writes require specific permissions. It also explains the prompt library behavior. 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 well-structured, starting with a clear summary, then the core flow, key nuances, and a separate section for the prompt library. Every sentence adds value without filler, though it could be condensed. The organization makes it navigable for an agent.

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 (14 actions, 23 parameters, no output schema), the description covers the main workflows, auth requirements, and the distinction between invoke and install. It also covers the prompt library. However, it lacks explicit details on return formats, error handling, and some parameter semantics, leaving a few gaps for an agent to infer.

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 coverage, the description must compensate. It explains the core flow and implies parameters for main actions (e.g., action, mcp_id, tool_id, arguments), but does not explicitly document all 23 parameters. Parameters like limit, message, conversation, immediate, prompt_targets, and others are not individually described, though their purpose can be inferred from action names. Partial compensation but not comprehensive.

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 marketplace, functioning as the catalog and execution layer. It names specific actions (search, describe, invoke) and distinguishes itself from siblings by being the central hub for MCP discovery, description, and running 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 explicitly differentiates when to use invoke vs install ('prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'), explains the flow between search/describe/invoke, and notes that writes require workspace owner/admin. It also clarifies when to use list_tools, subscribe/cancel, and the prompt library actions.

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, so the agent knows it's a safe read operation. The description adds context that it is hosted by the platform, requires prepaid credits per consultation, and that the client is the data controller under LGPD. This is useful but does not contradict annotations, and it covers the lack of auth details implicitly. Score 3 is appropriate as it enriches but doesn't fully describe all behaviors.

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 paragraph, concise, and front-loaded with the purpose. It includes extra legal/payment context that are relevant to usage. It is not overly verbose, but could be structured better with sections for clarity.

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 tool returns, but it does not. However, the complexity is moderate with 3 params, but no parameter details. Annotations cover safety. The description covers the source and legal context but lacks return format and parameter specifics, making it incomplete.

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. However, it provides no details on the parameters (cnpj, periodo, data_pagamento). The description only mentions the resource, not the inputs. For a tool with 3 params, this is a significant gap, so score 2.

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 specifies the verb 'consultar' and the resource 'Simples (Emissão de DAS de MEI)' and adds the context of 'fonte oficial' and 'consulta em fonte oficial'. It distinguishes from siblings by being the only tool that queries Brazilian official sources for Simples/DAS data, though it does not explicitly compare to 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 does not state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites beyond the general mention of official sources. It implies usage for consulting MEI DAS information but lacks explicit guidance on when not to use it or 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 cover read-only, destructive, and idempotency traits, lowering the burden on the description. The description adds useful context by requiring the conversation array for reproduction, but it does not clarify side effects, submission behavior, or whether a report creates a ticket or notification.

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 deliver the main purpose and the most important usage detail without fluff. The description is front-loaded and 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 3-parameter tool with no output schema, the description covers the core purpose and the key reproduction requirement. However, the ambiguity around the conversation parameter's type (array vs. string) and the undocumented context parameter leave minor gaps that could affect correct 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?

Schema description coverage is 0%, so the description must compensate. It explains that conversation should contain recent messages for reproduction, and message is implied as the report content. However, it does not explain the context parameter, and the phrase 'conversation array' conflicts mildly with the schema's string type (likely JSON-encoded).

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 a specific action ('Report') and concrete targets ('a bug, missing feature, or send feedback'). It is immediately distinguishable from sibling tools like authenticate or show_version, which have completely 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 communicates straightforwardly when this tool is appropriate: whenever a user wants to report a bug, missing feature, or give feedback. It also gives a practical prerequisite—including the conversation for reproduction—though it does not explicitly address exclusions or alternatives, which are not critical given the unrelated sibling tools.

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 aligns with the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) — 'Show' correctly implies a non-destructive read operation. The annotations already cover the safety profile well, and the description adds the specific context that both platform and adapter versions are returned. The modest lack of additional behavioral detail (e.g., error cases) is acceptable given the tool's simplicity.

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 sentence of 11 words, perfectly front-loaded with the core action. Every word earns its place, and there is zero redundancy 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?

For a zero-parameter, read-only version check with strong annotations and no output schema, the description is essentially complete. It provides the tool name and version context (platform and adapter) that an agent needs. One could imagine noting the exact version format or whether authentication is required, but these are minor gaps for such a simple 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 zero parameters and 100% schema coverage (trivially, an empty object), the baseline of 4 applies. There is nothing more the description could meaningfully add to explain parameter semantics since no parameters exist. The description correctly does not invent semantics that aren't there.

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 'Show the current MCP platform and adapter versions' uses a specific verb ('Show') and resource ('MCP platform and adapter versions'). It clearly distinguishes itself from the sibling tools, none of which obviously relate to version information.

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?

There is no guidance on when to use this tool versus alternatives. While the purpose is clear, the description doesn't address when to prefer this over potentially overlapping tools like 'toolkit_info', nor does it provide any usage context. No exclusions or alternatives are mentioned.

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, so the safety profile is covered. The description adds value by detailing exactly what state is returned (MCPs, status, accounts, tool counts). No contradictions or missing behavioral disclaimers (e.g., rate limits) are needed for a read-only info tool.

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, front-loaded sentence: 'Returns the current toolkit state:' immediately states the action and object, followed by a colon and a clean list of the four data categories. Every word is necessary; no fluff or redundancy. Excellent 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 simple read-only, zero-parameter tool with no output schema, the description fully captures all relevant facets: what it returns (MCPs, status, accounts, tool counts) and its side-effect-free nature (implicit via annotations). No additional details like pagination, error handling, or response shape are necessary for the tool's complexity level. It is 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 0 parameters, so the baseline is 4 per rubric. The description doesn't need to add parameter information, and the empty schema (100% coverage) confirms no missing semantics. The description clarifies what the output will be, which is sufficient for this simple interface.

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 elements (installed MCPs, connection status, accounts, catalog counts). It distinguishes this from sibling tools like 'show_version' (version info) and 'connect' (likely mutation), making the purpose unambiguous and mutually exclusive 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 implies usage for retrieving state but provides no explicit when-to-use guidance or alternatives. Sibling tools like 'connect' and 'authenticate' are clearly different in intent, but the description does not say 'use this to diagnose connection status' or 'use this over X when Y'. The intended use is inferred rather than stated.

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