Prefeitura GO Goiânia: Certidão Negativa de Débitos

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

Annotations already indicate idempotentHint=true and destructiveHint=false, but the description adds valuable behavioral context: it discloses that a token can be stored permanently via config header or used session-only, and that calling with no args returns a link for browser login. It does not contradict any annotation and enhances understanding of side effects beyond the schema.

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 but not overly terse—it packs the essential workflow into two sentences, front-loading the target audience and primary action. The options are clearly separated, and no redundant information 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?

With no output schema and only one optional parameter, the description fully covers the expected inputs, behaviors, and outcomes (either a link or session authentication). It explains the permanent vs. session modes and the recommended config approach, making the tool self-sufficient for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only defines 'token' as an optional string with no description. The tool description fully compensates by explaining what the token is (JWT) and when it is used (after pasting), and also clarifies that omitting it triggers the link generation flow. This gives agents complete parameter semantics despite zero schema coverage.

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 the MCP.AI server for IDE agents. It specifies the verb 'log in' and the resource (access token), and distinguishes itself from all sibling tools (which handle connectivity, marketplace, bug reports, etc.) by focusing solely on authentication.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance: it explains the two workflows (permanent via config header vs. session via token argument) and instructs to call with no args first to get the login link. This provides clear alternatives and prerequisites, effectively guiding agent invocation.

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 provide readOnlyHint=true年代 and idempotentHint=true, so the safe read-only nature is covered. The description adds value by explaining the two output states (authenticated vs. requires connection), which is behavioral context beyond annotations. It doesn't describe rate limits or side effects, but with readOnly annotations, that's less critical. Given annotations carry the safety disclosure, this is adequate.

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 sentences, front-loaded with the core purpose ('Returns connection status and URLs'), then conditional details. Every sentence adds value with zero fluff. The structure is clear: main behavior first, conditional sub-behaviors second.

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 this tool has no parametershare, the description fully explains what it returns in both main states (all connected vs. missing credentials). It covers the connection status and URL details. No output schema, but the description provides the key return fields (authenticated, pending[], connect_url, per-install URLs). Complete for a simple status check 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?

The input schema has no properties (0 parameters), so the description doesn't need to explain parameters. The description focuses entirely on return behavior, which for a no-parameter tool is the key information. Baseline for 0 params is 4, and the description meets that by explaining what the tool returns without needing parameter context.

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+resource. It distinguishes itself from sibling tools like authenticate by explicitly covering connection status rather than authentication. The two scenarios (all connected vs. missing credentials) add precision to the purpose.

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 this tool (to check connection status and get URLs when credentials are missing) by describing conditional behavior. It doesn't explicitly name alternatives or say when not to use it, but the scenarios provide clear context for when the tool is relevant.

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 are minimal but the description adds significant behavioral context: invoke runs without installation, returns connect/checkout links on failure, writes require admin, and search/describe flag installation 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?

Description is long but well-organized into core flow, key notes, and prompt library segment. Every sentence adds value given the tool's complexity (14 actions, 23 params). Slightly dense but justifiably so.

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?

Covers all major aspects: actions, permissions, installation semantics, prompt library, and error handling. For a tool with no output schema and rich input schema, this is near-complete 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?

Schema covers 0% of parameters, so description must compensate. It explains the action parameter's enum values and the flow (search/describe/invoke), but many other parameters (limit, query, message, prompt_*, etc.) are only implied via action descriptions, not individually explained. Meaningful but incomplete compensation.

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 it is the mcp.ai marketplace catalog and runner, listing all actions (search, describe, invoke, install, etc.) and their role. It distinguishes from siblings by covering the full marketplace scope, including prompt library actions.

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?

Provides explicit when-to-use guidance: prefer invoke for one-off use, use install for permanent toolkit addition, lists permission requirements (owner/admin for writes), and explains credential/payment edge cases (connect/checkout links).

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 falseUTE. The description adds transparency about payment ('pague por consulta com crédito pré-pago'), data nature ('não é dado sigiloso'), and legal responsibility (LGPD). It also clarifies the source is official. This goes beyond the structured fields, though it doesn't detail response formats or potential errors.

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 but concise, front-loading the purpose. It includes necessary context (payment, credentials, legal). It's not overly verbose, though the multiple clauses could be streamlined. Overall, it is efficient and to the point.

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 purpose, payment, data source, and compliance. However, it does not explain expected output (e.g., the certificate format), which CPF/CNPJ to use, or any potential reasons for failure. For a simple query tool, this is acceptable but incomplete without 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?

The input schema lists two string parameters 'cpf' and 'cnpj' with no descriptions (0% schema coverage). The description does not mention these parameters or explain how they are used (e.g., one must be provided, or both are optional). Given the tool's purpose, parameters likely correspond to Brazilian tax IDs, but the description fails to clarify their semantics, leaving the agent without sufficient guidance.

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: 'Certidão Negativa de Débitos, consulta em fonte oficial' (Negative Debt Certificate, query in official source) from 'Prefeitura GO Goiânia' (Goiânia City Hall). This is a specific verb+resource (consult + certificate) and distinguishes it from generic siblings 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?

The description provides context: it is a paid consultation using prepaid credits, hosted by the platform, and accesses official Brazilian sources. It mentions 'sem credenciais da plataforma' (no platform credentials) and LGPD data control. However, it does not explicitly state when to prefer this tool over alternatives, though siblings are maintenance tools and not direct competitors.

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 idempotentHint=true and destructiveHint=false, which align with the description's non-destructive purpose. The description adds context about including a conversation array for reproduction, but doesn't disclose any side effects or limitations beyond that.

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 (two sentences) and front-loaded with purpose. It doesn't waste words, though it could be more structured with parameter 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?

With no output schema and low parameter documentation, the description is incomplete. It doesn't explain what the tool returns, how to format the conversation array, or any prerequisites. For a bug-report tool, more guidance on expected input format is needed.

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 explain parameters. It mentions 'message' but doesn't clarify 'context' or 'conversation' semantics beyond a vague hint. It adds minimal value over the schema 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 description clearly states the tool reports bugs, missing features, or feedback, with a specific verb and resource. It is distinct from siblings like marketplace or show_version, though it doesn't explicitly differentiate from them.

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 it (for reporting issues/feedback), but does not explicitly state when not to use it or mention alternatives. It gives a hint on including conversation for reproduction, which is helpful but not exhaustive.

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 readOnly, idempotent, and non-destructive behavior. The description adds that it returns platform and adapter versions, which clarifies the output scope, but does not elaborate on potential side effects or error conditions—though none are expected for a read-only version query.

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 with no wasted words, effectively conveying the tool's purpose 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?

Given the simplicity of the tool and absence of an output schema, the description sufficiently indicates what information is returned (MCP platform and adapter versions). It does not specify the exact format, but that is not critical for a version-checking 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?

The tool has no parameters, so schema coverage is trivially 100%. The description adds no parameter-related information, but none is needed; thus a baseline score of 3 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's function with a specific verb ('show') and resource ('current MCP platform and adapter versions'), distinguishing it from sibling tools like 'authenticate' or 'report_bug'.

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 no guidance on when to use this tool versus alternatives, nor any context about typical use cases. It only states what it does, leaving the agent to infer appropriate invocation scenarios.

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 destructiveHint, covering the safety profile. The description adds value by disclosing the exact content of the returned state (installed MCPs, statuses, accounts, tool counts), which goes beyond the annotations. No contradiction exists.

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, well-structured sentence with a clear main clause and a colon-separated list of returned data. Every word earns its place; there is 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?

For a zero-parameter read-only info tool, the description fully explains what is returned and is consistent with the read-only annotation. While it lacks details like caching behavior, the simplicity of the tool and the presence of annotations make this a minor gap.

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 baseline of 4 applies. The description correctly implies no inputs are needed, and with no schema coverage burden, it sufficiently communicates the lack of required arguments.

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 verb 'Returns' and the resource 'current toolkit state', then enumerates specific data (installed MCPs, connection status, accounts, catalog tool counts). This specificity differentiates it from sibling tools like show_version or marketplace.

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 (to inspect toolkit state) but does not explicitly state when to use this over alternatives or provide exclusions. It could be improved by naming sibling tools and contrasting their purposes.

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