SEFAZ PR DEC: Caixa Postal

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

With annotations already indicating non-read-only, idempotent, and non-destructive behavior, the description adds useful context about permanent vs session-only authentication and the browser login flow. It does not contradict annotations and clarifies expected auth setup behavior, though it stops short of describing internal state changes or failure 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?

Three sentences, each serving a purpose: context, permanent-config recommendation, and session-based usage. It is slightly dense but well organized and front-loaded with the tool's identity.

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 covers the main flow, both authentication modes, and what the user/agent should do. Since there is no output schema, a bit more detail on the returned link or success/failure indicators would help, but for a simple one-parameter tool this is reasonably 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?

Schema coverage is 0%, but the description compensates by explaining the optional 'token' parameter as a JWT obtained from the browser and clarifying the no-args case. This is meaningful beyond the bare string schema, though it could add more detail on token format or expiration.

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 an authentication mechanism for MCP.AI in IDE agents, using specific verbs like 'log in' and 'copy the access token.' It is distinct from siblings like 'connect' and 'show_version' in substance, though it does not explicitly name alternative 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 gives actionable guidance on when to use the tool ('call with { token: "<jwt>" }') and when to prefer the config-header approach ('Best: add it to this server's config...'). It also notes the no-args fallback to get the login link, but does not explicitly exclude any sibling 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 declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds valuable behavioral detail beyond these: it specifies the response for two distinct states (all connected vs. missing credentials), including specific fields like authenticated:true and empty pending[], and the connect_url attribute. This fully covers the tool's 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 compact: two sentences. The first sentence immediately states the core purpose ('Returns connection status and URLs'), and the second adds conditional details. Every sentence earns its place with no 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?

Given the tool's simplicity (0 params, no output schema), the description fully covers the necessary information: what it returns and the two key states. Combined with annotations that handle safety and idempotency, the description is complete and well-rounded.

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 coverage is trivially 100%. Per the baseline rule for 0 parameters, a score of 4 is appropriate. The description does not need to explain parameters and instead focuses on output behavior, which is sufficient.

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 a specific verb 'returns' and a defined resource. It distinguishes itself from sibling tools like 'authenticate' and 'show_version' by focusing on status/URLs, making its 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 provides explicit usage scenarios: when all providers are connected and when credentials are missing. It implies when to use this tool (to check connection status) but does not explicitly state when not to use it or mention alternatives, which is a minor gap.

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 substantial context beyond the annotations (readOnlyHint=false, openWorldHint=true). It discloses that invoke runs one-off without installing or bloating the tool list, that auth needs return a connect link, that empty wallets return a checkout/top-up link with a retry instruction, and that writes require workspace owner/admin. It also flags installed_in_toolkit vs installed_in_workspace status. 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 a single dense wall of text with no paragraph breaks or bullet lists, despite its considerable length (covering 14 actions plus billing, auth, and the prompt library). The purpose and core flow are appropriately front-loaded, and every sentence carries real information, but the lack of structural organization makes it hard to parse and locate specific action semantics quickly.

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 very high complexity (14 actions, 23 params, no output schema, 0% schema coverage), the description covers the main behavioral flows well — the search→describe→invoke pipeline, one-off execution, auth/payment edge cases, and permission requirements. But it omits per-action return values, does not explain many parameters (limit, query, immediate, tier_slug, conversation), and does not detail cancel/subscribe semantics beyond naming them. Adequate but with clear gaps for a tool this complex.

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 carries full burden for parameter meaning. It does explain the central parameters functionally — action (via the core flow), mcp_id and tool_id ('invoke RUNS that tool... with its id + params'), arguments, and the prompt_* fields. However, roughly half the 23 parameters (limit, query, immediate, tier_slug, conversation, cancel_reason, request_name, prompt_targets, etc.) receive no semantic explanation in the text, leaving those 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 opening line, 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' gives a specific verb+resource plus scope, clearly identifying this as the discovery-and-execution hub for MCPs. It also distinguishes the prompt-library sub-domain. However, the tool is a 14-action dispatcher spanning search, install, billing, and prompts, so the single 'purpose' is somewhat diffuse across multiple sub-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?

Explicit guidance is abundant: the 'Core flow: action=search → describe → invoke' pipeline explains when each action is appropriate. It explicitly contrasts invoke ('prefer invoke for a single/occasional use') with install ('only to make an MCP PERMANENT'), and clarifies that list_tools reports what is callable right now. It also separates the prompt-library actions (search_prompts/get_prompt/publish_prompt) from MCP management.

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 indicate idempotency but do not clarify side effects (e.g., creating a ticket or sending a message). The description omits behavior details, leaving the tool's actual effect unclear.

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 with no fluff, directly stating the tool's purpose and one parameter hint.

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, but missing details about parameter usage and expected output or return value make it incomplete for full understanding, though basic usage is clear.

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?

Only 'conversation' is hinted at in the description; 'context' and 'message' lack any schema or description, leaving their purpose and format ambiguous.

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 reports bugs, missing features, or feedback, distinguishing 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?

It mentions when to use (reporting issues) but does not explicitly compare to alternatives or state when not to use it, though the purpose is sufficiently clear.

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 signal read-only/idempotent/non-destructive behavior. The description adds valuable context: the tool is hosted without platform credentials, charges per query, and is limited to information the citizen already has access to (not confidential data). It does not, however, disclose what the response looks like or whether external official credentials (e.g. e-CNPJ/certificate) are mandatory.

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 moderately concise, front-loading the main purpose in the first sentence. Subsequent sentences about LGPD and data controller obligations are relevant for compliance but take space away from missing functional guidance; no content is repeated from annotations, yet the legal phrasing could be shortened.

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 five undocumented parameters, no output schema, and no per-parameter explanation, the description is incomplete from a tool-invocation standpoint. It gives useful high-level context about the official source, prepaid billing, and platform login usage, but it does not provide enough operational detail for an AI to invoke the tool 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?

Schema description coverage is 0%, and the description provides no explanation of any of the five parameters. Parameters like 'login_cpf', 'login_senha', 'pkcs12_cert', 'pkcs12_pass', and 'ignora_nao_lidas' have only Portuguese labels, and the description does not compensate by explaining their meaning, format, or whether they are conditional, making correct invocation difficult.

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' (consultation) on 'Caixa Postal' from 'SEFAZ PR DEC' and is part of official Brazilian sources. This gives a clear verb and resource, distinguishing it from generic siblings like authenticate/report_bug, though 'Caixa Postal' as a mailbox service is not fully elaborated.

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 mentions payment via prepaid credits and the lack of platform credentials, which gives some usage context. However, it never explicitly states when to prefer this tool over alternatives, what qualifies as a valid query, or prerequisites such as possessing the required Brazilian official credentials represented by the input parameters.

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 known. The description adds specificity beyond annotations by clarifying exactly what versions are shown (platform and adapter), providing useful context. No contradictions exist.

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, direct sentence that front-loads the action ('Show') and specifies the exact content. Every word earns its place; there is no filler or repetition of schema fields.

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 informational tool with full annotation coverage, the description is complete. It fully communicates the tool's function without needing to explain return values or optional behaviors, as none exist.

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 zero properties, and the description adds no parameter details—correctly so, since there are no parameters to document. With 0 params, baseline is 4, as there is nothing for the description to compensate for.

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 clearly states the resource (MCP platform and adapter versions). This distinguishes it from sibling tools like authenticate, connect, or marketplace, which have 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 does not explicitly state when to use this tool or mention alternatives, but the purpose is self-evident for a version-reporting utility. Usage is implied (when you need the current MCP platform/adapter versions), but no exclusions or alternatives are provided, so it falls at the 'implied usage' level.

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, and the description is fully consistent with these. It adds behavioral value beyond annotations by specifying exactly what state data is returned, including connection statuses, accounts, and catalog tool counts, so an agent knows what to expect.

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 leads with the core action ('Returns the current toolkit state') and then uses a colon to list specific data elements. Every clause earns its place, and there is no fluff, repetition, or unrelated 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?

With zero parameters, strong annotations, and no output schema, the description fully covers desired usage context by enumerating the return contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This is sufficient for an agent to understand what the tool will do 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 tool takes zero parameters, so there are no parameter semantics to explain. As per the baseline for zero-parameter tools, the description appropriately focuses entirely on the return value and behavior, making additional parameter documentation unnecessary.

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') with a clearly defined resource ('current toolkit state') and lists the exact contents returned (installed MCPs, connection status, connected accounts, catalog tool counts). This scope distinguishes it from sibling tools like show_version, which would report version information rather than overall toolkit state.

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 makes the tool's purpose and output clear, so an agent can infer it is the right tool to inspect the current toolkit configuration and connections. It does not explicitly state when to prefer it over sibling tools or mention exclusions, but the clear context is sufficient given that no sibling tool claims the same function.

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