SEFAZ CE: Emissão de DAE

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

Annotations already indicate idempotent and non-destructive behavior. The description adds value by explaining the permanent vs session distinction, the need for browser interaction, and the token handoff process. It does not contradict any annotations. It also reveals that calling with no args returns a login link, which is a useful behavior insight.

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 but well-structured with 'Best:' and 'Or' to delineate options. It is somewhat wordy but every sentence conveys necessary information: the login flow, the permanent header method, and the session token method. It front-loads the purpose and then explains both paths, making it easy to scan.

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 an authentication tool with one optional parameter and no output schema, the description adequately explains the process and outcomes. It covers the two login modes, what to do with the token, and the no-argument behavior. It does not mention return values, but given the tool's nature and lack of output schema, this is a minor omission. The description is complete enough for an agent to use it 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?

The input schema has an optional 'token' parameter with zero description (0% schema coverage). The description compensates by explaining the token's purpose: it is the JWT to be pasted for session-only login. It also explains the alternative of setting it as a header, providing full context for how the parameter is used. This goes beyond the schema's bare field definition.

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 authenticate with MCP.AI, specifically for IDE agents. It specifies the verb (log in, authenticate) and the resource (MCP.AI server), and it distinguishes itself from sibling tools like 'connect' by detailing the token-based authentication flow. It is unambiguous and directly names the tool's function.

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 instructions: it explains two modes (permanent via header config, and session-only by pasting token), and tells the user to call with no args to get the link. It does not explicitly mention when not to use it or compare to alternatives like 'connect', but the context is clear. The guidance is actionable and covers the primary use cases.

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, lowering the burden. The description adds useful behavioral detail about conditional return values: authenticated:true with empty pending[], or connect_url and per-install URLs when credentials are missing. This goes beyond the annotations but does not detail the meaning of 'pending' or 'per-install URLs.'

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, front-loaded with the core purpose, and contains no filler. Every sentence adds meaningful detail about 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?

For a zero-parameter, read-only status tool with strong annotations, the description is reasonably complete. It explains the primary return values and the missing-credentials case, though terms like 'providers' and 'per-install URLs' could be slightly clearer.

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 parameters and schema description coverage is 100%, so the baseline is 4. The description does not need to explain parameters, and it correctly focuses on output behavior instead.

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,' which is a specific verb and resource. It distinguishes itself from siblings such as authenticate by clarifying this is a read-only status/URL retrieval rather than an action, and provides concrete output scenarios.

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 by describing conditions ('When all providers are connected... When credentials are missing...'), but it does not explicitly compare to alternatives or state when not to use it. It lacks direct guidance such as 'use authenticate when credentials need to be established.'

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 discloses key behavioral traits not captured by annotations: invoke runs uninstalled MCPs one-off without bloating the tool list, auth and payment failures return connect/checkout links, write-like operations require owner/admin, and search/describe flag installed vs. workspace tooling. This gives the agent important expectations about side effects and prerequisites.

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 information-rich, but it is a long stream-of-consciousness paragraph with awkward wording ('pontualmente') and no clear structural separation between the main tool actions, write protections, and prompt library features. It would benefit from shorter sections or bullet-like clarity while keeping the same 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?

For a tool with 23 parameters and no output schema, the description covers a lot: the core flow, one-off invocation behavior, auth/payment handling, owner permissions, and the prompt library sub-commands. It is still incomplete on concrete request/return formats and several secondary parameters, but on the whole it gives an agent enough context to choose and drive the 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 carries most of the burden but only meaningfully explains the `action` concept and a few related terms (tool_id, arguments via profile, prompt fields). Many parameters such as `limit`, `immediate`, `tier_slug`, `request_name`, `cancel_reason`, and `report_context` are left undocumented.

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 defines the marketplace as the in-platform catalog and execution layer for MCP/tool discovery, profiling, and invocation. It explicitly explains the core action flow (search → describe → invoke), making it easy to distinguish from sibling tools like report_bug, show_version, 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?

It gives explicit usage guidance: use invoke for one-off runs, install only for permanent toolkit addition, list_tools for currently callable tools, request_mcp when nothing fits, and report_bug for feedback. It also states when write operations are allowed (workspace owner/admin), which clarifies when to call vs. defer.

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 idempotentHint=true, readOnlyHint=false, and destructiveHint=false, covering the basic safety profile. The description adds guidance about the conversation array but doesn't disclose additional behavioral traits such as response handling or rate limits. With annotations present, this is adequate but not rich.

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 with no wasted words. It front-loads the purpose and then provides a practical reproduction instruction, making it efficient and well-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?

For a simple 3-parameter bug-reporting tool with no output schema and annotations covering safety, the description is sufficient. It clearly states purpose and gives a specific reproduction hint. Minor gaps like the exact role of 'context' and post-submission behavior don't significantly detract from its completeness.

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 'conversation' as recent messages for reproduction and implies 'message' is the content of the report. However, 'context' remains unexplained, leaving some ambiguity. This partial compensation warrants a mid-range score.

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 'Report a bug, missing feature, or send feedback,' providing a specific verb and resource. This distinguishes it from sibling tools like authenticate, connect, and sefaz_ce_emissao_dae_consultar, which have entirely 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 gives clear context: use this tool to report bugs, missing features, or feedback, and instructs to include the conversation array for reproduction. It does not explicitly mention when not to use it, but the context is specific enough without needing exclusions.

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 clearly indicate this is a read-only, idempotent, non-destructive operation, and the description reinforces that without contradicting annotations. The description adds behavioral context: it is hosted by the platform, requires no platform credentials, is pay-per-query with prepaid credit, and returns non-confidential official data. It also mentions data controller responsibility, which is extra context. No contradiction detected.

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 of moderate length, but it front-loads the core purpose and then covers hosting, payment, and legal aspects. Each sentence adds value, though the LGPD sentence is somewhat tangential. It is not overly long, but could be more concise by removing legal boilerplate. It is structured with a logical flow from purpose to operational details.

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 (3 params, no output schema, annotations provide safety profile), the description is fairly complete. It explains the tool is a paid read-only query to official data, which addresses usage and behavioral aspects. However, it does not explain what the tool returns (output structure) or how the query works (e.g., one query per CPF/chassi), but with no output schema and simple params, this might be adequate. The legal warning adds context. It could be more complete by specifying the exact inputs needed, but it is not severely lacking.

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 provides three parameters (cpf, chassi, numero_inscricao) with no descriptions, and the description does not explain any of them. Since schema coverage is 0%, the description should compensate, but it does not. However, the parameter names are self-explanatory (CPF, chassis, registration number), and the required ones (cpf, chassi) are likely identifiers for the DAE query. The description could have elaborated on the meaning of each, but the names give some context. This is a baseline score for a description that adds no extra parameter details.

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 tool's purpose: to issue DAE (emission) and consult from official source, which is clear. However, it does not explicitly distinguish it from potential sibling tools (no direct siblings related to DAE are present, but the name is similar to other SEFAZ tools). The purpose is specific to a resource (DAE) and action (consult/issue), which is good, but it could be clearer that 'emissão' is a query for issuance information, not an actual creation.

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 that it should be used for consulting DAE information from official Brazilian sources, and mentions it is paid with prepaid credit, which gives context on when to use it (when needing official DAE data). It does not explicitly state when NOT to use it or provide alternatives. The mention of LGPD and controller responsibility is more legal than usage. Sibling tools are unrelated, so no explicit differentiation is needed.

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 tool's safety profile is covered. The description adds the specific scope (platform and adapter versions) but provides no additional behavioral details such as output format 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?

The description is a single, clear, well-structured sentence. It immediately states the tool's function 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?

This is a simple, parameterless version-information tool. The description fully conveys what the tool does and what it reports, and no output schema is needed because the output is self-describing as 'versions'.

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 the schema is complete, so the description need not explain parameter semantics. The baseline for zero-parameter tools is 4, and the description adds no conflicting or missing parameter information.

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 verb and resource: 'Show the current MCP platform and adapter versions.' This is specific and distinct from sibling tools such as authenticate or marketplace, which serve 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 makes its usage context clear: use it when you need to know the current platform and adapter versions. No exclusions or alternatives are mentioned, but for a simple informational tool this is sufficient.

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, covering safety. The description adds meaningful context by detailing the exact state information returned (MCPs, connection status, accounts, tool counts), which is beyond mere annotation repetition.

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 stating the purpose and then enumerating the specific data items delivered. No wasted words; every clause 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?

With no parameters and no output schema, the description carries the full burden of explaining return contents. It lists four distinct categories of information, making the tool's output predictable and complete for an info-only operation.

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% and the baseline is 4. The description appropriately focuses on the return payload rather than parameters, 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 identifies the exact resource ('current toolkit state'), then lists concrete components: installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it from siblings like show_version 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?

The description implies usage context—use this to inspect toolkit status—but does not explicitly state when to use it versus alternatives or provide exclusions. Clear context is present, but explicit guidance is missing.

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