Prefeitura MG Juatuba: Certidão Negativa de Débitos

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

Adds genuinely useful behavior beyond annotations: the tool fetches a link, supports permanent vs. session-only auth, and accepts a copied JWT. Consistent with idempotentHint=true (re-running login is safe). No contradiction with annotations — it never claims readOnly or destructive semantics.

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?

Every element delivers value and the info is dense rather than padded, but it's one long run-on string with colons and 'or' chains that could confuse a parser. A clearer sentence boundary (especially after 'Best:') would earn a 4.

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 low-complexity tool (1 optional param, no output schema), the description covers the essential flows: obtaining auth, three invocation modes, and session durability trade-offs. The main gap is no description of the actual return/link format, but with no output schema expected and the no-args behavior implied, this is largely 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?

Schema coverage is 0%, so the description carries the full burden — and it compensates well: it explains the token is a JWT, shows the exact object shape { token: "<jwt>" }, and clarifies the no-arg call returns the link. This meaningfully enriches the bare string 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 conveys the authentication purpose — browser login, copy token, get link — with specific call modes that make the tool's function evident. It stops short of a crisp 'authenticates the user/session' statement and the opening 'MCP.AI for IDE agents (Cursor, etc.)' reads more like app boilerplate, but the verb+resource is inferable and 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 gives a clear decision procedure: config-header setup for permanent auth, pass token for session-only, or no-args to get the link. Context and call-mode trade-offs are explicit, though no sibling alternatives (e.g., connect) are named to contrast against.

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 provides concrete behavioral details for two scenarios (all connected vs. missing credentials), going beyond the read-only annotation by specifying the exact return values and structure.

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 extremely concise, consisting of two sentences that are well-structured: it first states the general purpose, then details the two conditional outcomes. Every sentence adds value with no 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?

The description covers the main functionality and two important states, but it does not address partial connection scenarios or potential errors. For a simple tool with no parameters, this is sufficient but not exhaustive.

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, and the schema has no properties. According to the rubric, when schema coverage is high (vacuously true here), the baseline is 3. The description adds no parameter information because none 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 clearly states that the tool returns connection status and URLs, and it distinguishes itself from sibling tools like authenticate by focusing on status retrieval.

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?

While the purpose is clear, there is no explicit guidance on when to use this tool versus alternatives. It does not mention specific use cases or when to prefer another tool, though it is implied by its read-only nature.

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 sparse (only booleans), leaving the description to carry the burden. It discloses key behaviors: invoke runs tools without installation, returns connect/checkout links when auth or payment is needed, and that writes require owner/admin. It also clarifies the distinction between one-off and permanent installation, going beyond simple read/write hints.

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 lengthy but appropriately structured: it opens with the core purpose, then details the search/describe/invoke flow, clarifies the distinction between invoke and install, notes permission requirements, and finally introduces the prompt library. No sentence is redundant, though it could be tightened by splitting into bullet points. The front-loaded purpose helps quick scanning.

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 parameters, no output schema, multiple action modes), the description covers all major aspects: the discovery flow, one-off vs permanent execution, auth and payment handling, permission constraints, and the separate prompt library. It leaves no critical ambiguity about how to operate 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 0% schema coverage, the description must explain parameters itself. It does so for the critical ones: action (the enum is implied though not fully listed), mcp_id, tool_id, arguments, and prompt-related fields. It also covers the meaning of immediate, tier_slug, and others implicitly through the flow. However, some auxiliary parameters (e.g., limit, query, message) are not directly explained, but the overall context makes them self-evident.

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 marketplace and explains its dual role: cataloging MCPs and running them. It distinguishes its core flow (search→describe→invoke) and mentions the separate prompt library, making it easy to understand what this tool does and how it differs from sibling tools like 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 explicit guidance on when to use invoke vs install ('prefer invoke for a single/occasional use'), when to use install (permanent addition), and notes the difference between search/describe and list_tools. It also explains when to use prompt-related actions and lists permissions required for writes, giving clear decision criteria.

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 mark the tool as read-only and idempotent, and the description reinforces this with 'consulta'. It goes beyond by disclosing the financial cost per query, that data is not confidential, and the client's LGPD accountability—critical operational and legal traits not present in the annotations. No contradiction with structured data.

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 tight and front-loaded: the first clause states exactly what the tool does, followed by essential commercial and legal caveats. Every sentence carries weight—hosting, credentials, pricing, data classification, and compliance—without redundancy. It's a model of concise, informative tool documentation.

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 such a simple tool (2 optional strings, no output schema) and strong annotations, the description covers purpose, costs, credentials, and legality quite well. However, the total absence of parameter guidance means the agent cannot reliably construct a request. It's borderline adequate for a human familiar with CPF/CNPJ, but not fully complete for autonomous execution.

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 0% schema description coverage and no mention of 'cpf' or 'cnpj' in the description, the agent gets no help on how to fill the two required-for-use string fields. The description doesn't clarify whether both are needed, which takes precedence, or even hint at their meaning. Given the low coverage, the description fails to compensate for this gap.

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 queries 'Certidão Negativa de Débitos' from 'Prefeitura MG Juatuba' as an official source. The verb 'consulta' and the resource are explicit, and the sibling tools (authenticate, connect, etc.) are entirely unrelated, so this tool is well-differentiated. The purpose is unambiguous even without the title.

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 key usage context: pay-per-query with prepaid credit, no platform credentials needed, and it queries only official public data. This tells the agent when the tool is appropriate (free of auth, costs money) but doesn't explicitly name alternative tools, though the sibling list doesn't offer a direct competitor. The LGPD note also guides responsible use.

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 indicate non-read-only, non-destructive, and idempotent behavior. The description adds one useful behavioral detail: the conversation array is needed for reproduction. It does not disclose further side effects or submission outcomes, but with annotations present 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 short sentences, front-loaded with the action and resource, with no filler or repetition. Every clause 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 low-complexity tool with no output schema and partial annotations, the description gives the core purpose and a key usage requirement. However, it omits explanation of the required message parameter and the optional context parameter, and does not mention what happens after submission.

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 conversation parameter's role ('recent messages for reproduction') but leaves message and context semantically unaddressed. The required message parameter is only implied by the overall purpose, and context is not explained.

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: 'Report a bug, missing feature, or send feedback.' It uses a specific verb and resource, and is readily distinguishable from sibling tools like show_version and 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 gives clear use context (bug reporting, feature requests, feedback) and instructs to include the conversation array for reproduction. It does not explicitly state when not to use this tool or name alternatives, but the use cases are well-defined.

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 specificity by naming 'MCP platform and adapter versions', but does not mention output format or potential network behavior, which is acceptable given the simple read-only nature.

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?

One concise, front-loaded sentence communicates exactly what the tool does 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?

Given the zero-parameter schema, rich safety annotations, and simple read-only purpose, the description is fully sufficient. No output schema is needed, and the behavior is completely described for an agent.

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 is 4. The description adds no parameter details because none exist, which 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 uses a specific verb ('Show') and states the exact resource ('current MCP platform and adapter versions'), clearly distinguishing it from sibling tools focused on authentication, connection, or marketplace operations.

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 usage is implied by the nature of the tool: use it to display version information. It does not mention alternatives or when not to use it, but given its trivial scope, the context is clear and no exclusions are 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, destructiveHint=false, idempotentHint=true, and openWorldHint=false, so the behavioral safety profile is fully covered. The description adds context about what the tool returns (installed MCPs, connection status, accounts, catalog counts), which is beyond the annotations. It could mention that it doesn't modify state or require setup, but the annotations suffice, and the description adds useful detail on outputs.

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 concise and information-dense. It clearly enumerates the returned components without verbosity. It is front-loaded with the action and resource, and every part is relevant.

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 has no parameters, simple output (no output schema), and clear annotations, the description is complete. It fully describes the tool's purpose and what it returns, covering all key aspects. It covers all aspects. It does not add value beyond what's already provided, but the description adds all the value needed for a simple 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?

There are 0 parameters, so the description doesn't need to explain them. The baseline for 0 params is 4 per the rubric. The description appropriately describes what the tool returns, which is the main semantic value for a no-arg 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's function: returning the current toolkit state with specific components (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes itself from siblings like 'authenticate' and 'connect' by focusing on information retrieval rather than 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?

The description implies when to use this tool (to inspect toolkit status). It does not explicitly state when not to use it or mention alternatives, but given the tool's nature as an info-only tool and sibling names like 'show_version', it's reasonably clear. However, no explicit guidance on when to prefer this over 'show_version' is provided.

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