SEFAZ MS DTE: Caixa Postal

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

The description adds meaningful behavioral context beyond the annotations: it explains the two auth modes (permanent config header vs session-only token), that calling with no args returns the login link, and that the token is a JWT. It does not contradict the idempotentHint or destructiveHint annotations, and it clarifies the non-destructive, session-oriented behavior.

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 but not bloated; every sentence adds useful information about the login flow, permanent vs session-only options, and invocation patterns. It is slightly long and somewhat run-on, but it is front-loaded with the core purpose and remains readable.

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 auth tool with one optional parameter and no output schema, the description covers the workflow, token format, invocation modes, and persistence semantics. It does not explicitly describe the return value beyond 'get the link,' but that is sufficient given the tool's simplicity and the lack of an output schema.

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%, so the description carries the full burden for the single optional `token` parameter. It explains that `token` should be a JWT pasted by the user, that providing it performs session-only login, and that omitting it returns the login link. This fully compensates for the schema's lack of description.

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: authenticating MCP.AI for IDE agents by logging in via browser and obtaining an access token. It specifies the resource (MCP.AI for IDE agents) and the action (log in, copy token, authenticate), and it is distinct from sibling tools 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 provides concrete usage guidance: either add the token to the server config as a permanent Authorization header, or paste it into this tool for a session-only login. It also explains when to call with a token versus with no arguments. It does not explicitly mention when not to use this tool relative to siblings, but the guidance 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 already establish read-only, idempotent, non-destructive behavior. The description adds conditional details about the response shape: authenticated:true with empty pending[], or connect_url and per-install URLs when credentials are absent.

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 core purpose and the key behavioral branches without any filler. Every clause adds necessary 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?

Given zero parameters, no output schema, and comprehensive annotations, the description fully covers the tool's practical behavior. The two-state explanation is sufficient for correct invocation and result interpretation.

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 accepts zero parameters, so the schema fully covers parameter semantics. The description appropriately omits parameter details, and the baseline for no params is 4.

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 states the exact function: returns connection status and URLs, and distinguishes between connected vs. missing-credential states. It clearly separates this from sibling tools like authenticate or toolkit_info.

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: to check authentication status or fetch connect URLs when credentials are missing. It does not explicitly compare against alternatives like authenticate, but the scenarios are clear enough.

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 only saying readOnlyHint:false, the description discloses crucial behaviors: invoke works even when the MCP is not installed, runs one-off without bloat, returns connect or checkout links in specific auth/payment scenarios, and the one-off install behind invoke requires permissions. This goes well 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 dense paragraph with many clauses and parentheticals. While nearly every sentence carries important information, the structure is heavy and could be improved with bullets or clearer separation of topics. It is appropriately sized for the tool's complexity but lacks conciseness and readability.

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 (23 params, 14 action enum values, prompt library), the description is quite complete: it covers discovery, running, installation, permissions, billing, and prompt distribution. It does not explain return formats or all parameter details, but no output schema exists and the core usage is well 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?

Schema description coverage is 0%, so the description must compensate. It explains the action parameter thoroughly and gives implicit meaning to tool_id and prompt_vars via the described flows. However, with 23 parameters, it does not systematically address limit, query, mcp_id, arguments, or the various prompt/cancel fields, leaving many parameters under-documented.

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 as the official mcp.ai marketplace, the in-platform catalog and runner for MCPs/tools. It distinguishes itself from sibling tools by outlining a full core flow (search → describe → invoke) and explicitly covering related actions like install, subscribe, and request_mcp.

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, contrasting invoke (one-off, no install) with install (permanent addition), and enumerating actions like list_tools, subscribe, report_bug, and request_mcp. It also notes that writes require workspace owner/admin and explains how to handle connect/checkout links by retrying after the user completes the 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 correctly declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true, so the agent already knows this is a non-destructive but non-read-only reporting action. The description adds that the conversation array should contain recent messages for reproduction, which is useful behavioral context, but it does not disclose what happens after the report is submitted (e.g., acknowledgment, tracking number) beyond what annotations imply.

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 exceptionally concise: two sentences, immediately placing the core purpose first and a specific usage tip second. No filler, repetition, or redundant information from the schema is 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?

The tool is relatively simple with 3 parameters and no output schema, so complete documentation would be short. The description provides the core purpose and one key parameter detail (conversation for reproduction), but it omits the function of the 'context' parameter and gives no sense of what the user can expect upon completion (e.g., a response or success indicator).

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 for parameter explanations. It explicitly explains the 'conversation' parameter's purpose ('recent messages for reproduction'), but gives no explanation for 'context' or 'message' beyond the obvious. This is insufficient for full compensation, especially since 'context' is an optional parameter with a subtle meaning.

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 begins with the specific verb 'Report' and names explicit objects: 'a bug, missing feature, or send feedback', clearly identifying the tool's purpose. It is also distinct from all sibling tools (authenticate, marketplace, show_version, etc.), which belong to different functional domains.

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 states when to use the tool ('Report a bug, missing feature, or send feedback') and provides a specific usage instruction ('Include the conversation array with recent messages for reproduction'). It does not explicitly mention that other tools are not appropriate, but the sibling tools are so clearly unrelated that no exclusion is necessary.

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 idempotentHint=true, and the description aligns by calling it a 'consulta' (read operation). It adds useful context about the payment model and data privacy (client is data controller), which go beyond basic annotations. However, it does not disclose what happens on errors, rate limits, or the exact nature of the response. Since annotations cover the safety profile, the description adds moderate value.

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, brief paragraph that front-loads the purpose and then covers payment and legal aspects. It is concise and avoids unnecessary filler, though it could be better structured with clearer separations. Every sentence contributes to context, but some points (e.g., LGPD) are tangential to the immediate operation.

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 has 5 parameters, 2 required, and no output schema. The description explains the purpose and pricing but does not describe return values, parameter usage, or authentication flow (despite pkcs12 cert/pass being required). It mentions 'official source' but not what data is returned. Given the complexity, the description is incomplete for an agent to invoke correctly without additional schema descriptions.

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%, and the description does not explain any of the 5 parameters (ie, cnpj, pkcs12_cert, pkcs12_pass, ignora_nao_lidas). Even the required certificate parameters are only mentioned as 'sem credenciais da plataforma' (without platform credentials), which could confuse users. The description fails to compensate for the lack of schema descriptions, leaving parameter meanings unclear beyond their 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 states the tool performs a 'consulta' (query) on the official SEFAZ MS 'Caixa Postal' (mailbox). The verb and resource are specific, and the domain is clear (Brazilian tax agency). It is distinct from sibling tools, which are platform-level (authenticate, connect, etc.), so it differentiates implicitly, though it doesn't explicitly say 'use this instead of X'.

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 context about payment (pre-paid credit), official source, and LGPD compliance, but it does not state when to use this tool versus alternatives or any exclusions. There is no mention of prerequisites or conditions that would make this tool appropriate or inappropriate beyond the general 'consulta' purpose. Implied usage is present but not 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?

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that it reports 'current' versions and identifies the specific version categories, but does not disclose additional behavioral traits such as output format or latency.

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 wasted words. It conveys the entire purpose efficiently 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?

For a zero-parameter, read-only version query, the description is complete. It states exactly what the tool returns (MCP platform and adapter versions) and leverages the annotations for behavioral context, so no additional detail 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 no semantic burden on the description. The schema is empty with 100% coverage, and the description appropriately avoids inventing parameter details that do not exist.

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 ('Show') and clearly identifies the resources ('current MCP platform and adapter versions'). It is clear and unambiguous, though it does not explicitly distinguish itself from the sibling 'toolkit_info', which could also provide informational output.

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 intended use is implied by the tool's purpose: users should call this when they need version details. However, there is no explicit guidance about when not to use it or which alternative to choose, so it relies on contextual inference.

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 and idempotentHint, and the description adds valuable context by specifying exactly what state is returned (MCPs, connection status, accounts, catalog tool counts). This goes beyond the minimal metadata without contradicting it.

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 that is front-loaded with the key verb ('Returns') and immediately specifies the scope. Every element is informative, with no wasted words.

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, no-output-schema tool, the description fully covers what the agent needs to know about the returned data and the tool's purpose. It is complete within its 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 the schema coverage is trivially 100%. The description does not need to add parameter meaning, and no parameters exist to describe. Baseline of 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 the current toolkit state, listing specific components (installed MCPs, connection status, accounts, tool counts). This distinguishes it from sibling tools like show_version and authenticate, making the purpose unambiguous.

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 (to inspect toolkit status) but does not explicitly mention alternatives or exclusions. However, for a zero-parameter info tool, the context is clear enough to guide selection.

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