SEFAZ: Certidão Negativa de Débitos Estaduais

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

Annotations indicate idempotentHint=true and destructiveHint=false, which the description aligns with. The description adds context about the token being non-expiring for config-based auth and session-only for pasted tokens, which is useful behavioral info beyond annotations. It doesn't contradict 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 and front-loaded with the tool's purpose. It packs a lot of information into two sentences, but the second sentence is a bit dense with multiple clauses. Still, every sentence earns its place.

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 (1 optional param, no output schema), the description is fairly complete. It covers the two auth methods, the token parameter, and the no-args behavior. It could mention what the response looks like, but that's minor given the lack of 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 description coverage is 0%, so the description must compensate. It explains the 'token' parameter as a JWT to paste for session-only login, and clarifies that calling with no args returns the link. This adds meaning beyond the bare schema.

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 by logging in via browser and obtaining an access token. It distinguishes itself from siblings by focusing on authentication, while siblings like 'connect' and 'marketplace' serve different functions.

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 guidance: it explains two methods (permanent config header vs. session-only token), when to use each (permanent vs. session), and how to call the tool (with token or no args). It also mentions the alternative of adding the token to config, which is a clear alternative to using this tool.

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, idempotent, and non-destructive properties. The description adds value by explaining the two return cases (authenticated true with empty pending vs. connect_url outputs), but does not fully address partial connection scenarios.

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 main purpose, and provides essential details without verbosity. Every sentence earns its place.

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 read-only tool with no parameters and good annotations, the description sufficiently explains what the tool returns in different states and is complete for its intended use.

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, so the baseline is 4. The description correctly focuses on output behavior rather than parameter details, which is appropriate for a parameterless tool.

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 specific behavior for both connected and missing-credential states. This distinguishes it from siblings like authenticate, which handles authentication flows.

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 its output for different connection states, giving clear context. However, it does not explicitly mention alternatives or situations where another tool would be preferred.

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 well beyond the annotations by disclosing that invoke works even when an MCP is not installed, returns connect links for missing credentials, returns checkout links for insufficient wallet balance, and that writes require owner/admin access. It also explains the installed_in_toolkit vs installed_in_workspace distinction, which adds meaningful context beyond readOnlyHint/destructiveHint.

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 information-dense: every sentence adds distinctive behavior or selection guidance. It is front-loaded with the core flow, then clarifies edge cases like uninstalled MCPs, credential/payment handling, installation, and the prompt library. Minor structure issues include long compound sentences, but there is almost no wasted content.

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 and annotations are minimal, the description does an unusually thorough job: it explains return-like artifacts such as MCP profiles, connect links, checkout links, prompt text, and shareable prompt URLs. It still leaves some sub-actions underspecified, such as the exact output of subscribe/cancel and list_tools, but overall the description is adequate for a multi-action tool of this complexity.

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 adds significant meaning for the main action parameter and the conceptual parameters like mcp_id, tool_id, prompt_slug, prompt_vars, and request_name, and it explains the search→describe→invoke data flow. However, with 23 parameters and 0% schema coverage, many parameter meanings remain implicit or undocumented, such as limit, immediate, tier_slug, message, conversation, cancel_comment, and the full prompt_* set. It partially compensates but not comprehensively.

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 marketplace catalog, the way to run MCPs, and the core search→describe→invoke flow. It also distinguishes this from sibling-like functionality such as report_bug, request_mcp, and list_tools. However, the tool is a facade over many sub-actions, so its overall purpose remains intentionally broad and not as singularly focused as a one-operation tool.

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 explicit workflow guidance: use action=search to discover, describe to inspect, and invoke to run. It explicitly says to prefer invoke for one-off use and install only when an MCP should be permanent, and it distinguishes report_bug, request_mcp, list_tools, and prompt-library actions. This is strong, actionable guidance for tool selection.

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 state readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds the behavioral guidance that the conversation array should be included for reproduction, but it does not explain response behavior, whether the report triggers side effects, or how the submission is processed. It does not contradict 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 clear sentence that concisely conveys the primary purpose and key usage note. It could be slightly expanded to resolve parameter ambiguity, but there is no wasted text or irrelevant 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?

The tool is relatively simple and the description covers the core purpose and one important usage detail. However, since the schema does not describe any parameters and there is no output schema, the description alone leaves the user uncertain about the meaning of 'context' and what the response (if any) will be. The annotations also fail to describe safety or auth requirements, so additional context would improve 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 for all parameters, but it only addresses the 'conversation' parameter explicitly via 'Include the conversation array with recent messages for reproduction.' The 'message' and 'context' parameters receive no direct explanation, leaving meaningful ambiguity about how to use them correctly.

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 with an explicit verb 'Report' and lists the accepted categories: 'bug, missing feature, or send feedback.' It is distinct from sibling tools such as authenticate, connect, or sefaz_certidao_debitos_consultar, all of 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 implies the intended use cases (bug reports, feature requests, feedback) and gives direct instruction on what to include: 'the conversation array with recent messages for reproduction.' It does not explicitly exclude alternative tools, but the scoped list of use cases provides clear context for when this tool should be selected.

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, destructiveHint=false, aligning with the query nature described. The description adds genuinely useful behavior context beyond annotations: the cost model ('pague por consulta com crédito pré-pago' - pay per query with prepaid credits), data source nature ('a mesma disponível ao cidadão, não é dado sigiloso'), and LGPD data-controller responsibility. This enriches the agent's understanding of side effects (costs) without contradicting the safe read-only annotations. No contradiction found.

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 structured as 4 sentences, front-loading the core purpose first (good) and placing the LGPD statement last (reasonable). However, there is redundancy: 'fonte oficial' is repeated as 'fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso', which could be condensed. The sentence is structured as several loosely connected clauses, and the legal/hosting details could be trimmed for a tighter, more scannable description.

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 handles the compliance/security angle well (LGPD controller responsibility, non-confidential data) which is contextually relevant given the PII parameters (CPF, CNPJ, PKCS12 certs). However, given there is no output schema and no description of return values, format, or failure modes (e.g., what happens when debts are found vs. not), the agent lacks completeness. The tool also handles authentication material (pkcs12_cert, login_senha) without any operational caution, which in combination with the zero output schema weakens 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?

With 11 parameters and 0% schema description coverage, the description was expected to compensate but provides zero parameter guidance. While names like 'cpf', 'cnpj', 'uf' are self-evident, critical ambiguities remain unexplained: the distinction between 'login_cpf'/'login_senha' and 'cpf' as identity parameters, the format of 'pkcs12_cert', the meaning of 'preferencia_emissao', and when to use 'ie' vs 'cpf' vs 'cnpj'. The description's perfunctory mention of 'sources and official organs' does not help an agent correctly populate any of these 11 fields.

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 tool name is highly descriptive ('sefaz_certidao_debitos_consultar') and the description confirms 'Certidão Negativa de Débitos Estaduais, consulta em fonte oficial' (query for negative state debt certificates in official sources). This clearly conveys the verb+resource. However, the core purpose is diluted within commercial (pay per query, credits), hosting, and LGPD legal boilerplate, and it doesn't explicitly distinguish itself from a sibling beyond the generic sibling set.

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 explicit guidance on when to use this tool versus alternatives. The description mentions it queries official Brazilian sources with citizen-level access, which implies scope, but fails to state prerequisites (e.g., what data must be provided: CPF vs CNPJ vs IE), when NOT to use it, or any alternative tools. The LGPD disclaimer is legal context, not usage guidance.

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 well-covered. The description adds the specific scope (platform and adapter versions) but does not disclose any additional behavioral traits such as output format or potential side effects. Since annotations cover the main behavioral aspects, a score of 3 is appropriate.

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 that directly states the tool's function. There is no wasted wording, and it is front-loaded with the action verb. This is an example of efficient, minimal description.

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, clear annotations), the description is complete enough. It tells the agent exactly what the tool does. The only minor gap is that it doesn't specify the output format, but since there is no output schema, the description could have mentioned what the version information looks like. However, for a simple version-check tool, this is sufficient.

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 schema description coverage is 100% (vacuously). The description does not need to explain parameters because there are none. The baseline for zero parameters is 4, and the description is clear about what it does, so this score is justified.

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: showing current MCP platform and adapter versions. It uses a specific verb ('Show') and resource ('MCP platform and adapter versions'), which is clear and distinguishes it from siblings like 'toolkit_info' which likely provides broader 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?

The description implies usage for checking version information, but does not explicitly state when to use this tool versus alternatives like 'toolkit_info'. Given the sibling context, there is no explicit guidance on when to prefer this tool over others, but the purpose is clear enough that an agent can infer appropriate 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds value by detailing the exact content of the returned state (installed MCPs, connection status, accounts, tool counts), going beyond a generic 'returns state.' It does not contradict annotations and provides useful context without requiring additional disclosure.

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, information-dense sentence that front-loads the purpose ('Returns the current toolkit state') followed by a concise list of included data. Every word earns its place; 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?

The tool has no parameters and no output schema, but the description fully specifies what will be returned (MCPs, connection status, accounts, catalog tool counts). Given the low complexity and absent schema, this is sufficient for an agent to understand the tool's output and decide when to invoke it.

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 correctly focuses on return value rather than inputs, and no parameter explanations 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 clearly identifies the resource ('current toolkit state') with a detailed enumeration of what is included: installed MCPs, connection status, accounts, and catalog tool counts. This establishes a distinct purpose that differentiates it from siblings like show_version and 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?

The description implies usage as a read-only status inspection tool but does not explicitly state when to use it versus alternatives like show_version or connect. There are no exclusions or 'if you need X, use Y' guidance, leaving the context implied rather than explicit.

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