Prefeitura MG Santa Vitória: Certidão Negativa de Débitos

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

Adds meaningful behavioral context beyond annotations, such as requiring browser login, the need to copy tokens, and the option to call with or without arguments. It complements the idempotent and non-destructive hints without contradiction.

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 well-structured with clear steps and a logical flow (purpose, best method, alternative). While slightly verbose, it remains concise enough to be easily understood.

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?

Effectively covers the authentication process, usage scenarios, and parameter details. Although it does not describe return values or error handling, the output schema is unspecified, making the description adequate for the tool's purpose.

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 token parameter is fully explained: its purpose (access token for authentication), its optionality (can be omitted to get a link), and its usage in the two authentication methods. This adds significant meaning beyond the schema's simple string type.

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?

Clearly states the purpose is authentication for IDE agents, with explicit instructions for logging in and using tokens. It distinguishes itself from potential sibling tools by specifying its target audience.

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 usage guidelines: two distinct methods (permanent via config, session-only via token) and when to call with no arguments to get a link. It clearly explains when to use each approach.

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 description doesn't need to repeat those. It adds value by explaining the behavior when credentials are missing (returns connect_url for toolkit and per-install URLs), which is beyond what annotations provide. It gives a good sense of what the response looks like.

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 that efficiently convey the tool's purpose and two distinct behavior states. Every word earns its place, with zero fluff. The sentences are front-loaded with the key information ('Returns connection status and URLs'), then add conditional 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 simple (no params, no output schema), and annotations cover safety. The description explains the two relevant states (all connected vs missing credentials), which is likely sufficient for an agent to know what to expect. It could possibly mention the behavior when some providers are connected but not all, but given the description already notes 'When all providers are connected' and 'When credentials are missing', it implies there's a middle ground. However, the description is complete enough for a simple status 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 zero parameters, and schema description coverage is 100% (vacuously). The description goes beyond the schema by explaining what the tool does without parameters. Since there are no parameters to describe, the description appropriately focuses on behavior. This score reflects the baseline for tools with no params.

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 details about behavior under different conditions (all connected vs missing credentials). This distinguishes it from siblings like authenticate and toolkit_info, though it could be slightly more explicit about what makes it different from show_version.

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: to check connection status and obtain URLs. It doesn't explicitly say when not to use it or name alternatives, but the context is clear given the sibling tool names (authenticate, toolkit_info). It provides clear context on what it returns in two states.

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 critical non-obvious behaviors: invoke runs tools even when the MCP is not installed, does not bloat the tool list, returns a connect link for missing credentials, returns a checkout/top-up link for unpaid tools and instructs the agent to retry after the user acts. It also notes that writes require workspace owner/admin. These go well beyond the sparse 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 one dense block, but nearly every sentence contributes distinct information about actions, flow, permissions, or payment behavior. It is long, yet the complexity of a 14-action hub justifies the length. More structure (separating marketplace vs prompt library) would improve readability, but it is not wasteful.

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 of this scope, the description covers a lot: discovery, one-off invocation, installation, billing, auth/payment retry flows, permissions, and a separate prompt library. Gaps remain around return values/output shapes of each action and some edge-case actions like resume and immediate, but the overall operational picture is strong.

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% across 23 parameters, so the description carries the burden. It explains the central action parameter and gives context for mcp_id, tool_id, and prompt_slug via the workflow, but many parameters (immediate, arguments, cancel_comment, prompt_targets, prompt_vars, conversation) receive no explicit semantic explanation. The workflow narrative partially compensates but does not fully document the parameter surface.

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 mcp.ai marketplace: a catalog and execution layer for MCPs, plus the prompt library. It names the core actions (search, describe, invoke) and distinguishes them, though it covers so many sub-capabilities that a single sharp 'verb+resource' statement is missing.

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?

Excellent usage guidance: it spells out the intended core flow (search → describe → invoke), explicitly advises when to prefer invoke over install ('prefer invoke for a single/occasional use'), when to use install for permanence, and when to use request_mcp for new capability requests. It also covers billing actions and the prompt library separately.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable context beyond annotations: the payment model ('pague por consulta com crédito pré-pago'), that no platform credentials are needed, and LGPD data responsibility. It does not contradict annotations and enriches transparency.

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 (about 40 words) and every sentence contributes relevant information: purpose, hosting, pricing, data privacy. However, it is a single run-on sentence that could be better structured with clear separation of purpose and usage details. Still, it is appropriately sized and not wasteful.

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, the description should explain what the tool returns (e.g., the certificate status or result format), but it does not. It also does not clarify the parameter requirements (e.g., one of cpf or cnpj must be provided). The description is sufficient for a basic query tool but lacks essential details needed for correct invocation, making it incomplete.

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 two optional string parameters (cpf, cnpj) with no descriptions (schema coverage 0%). The tool description does not explain these parameters, their format, or whether at least one is required. The inference that cpf is for individuals and cnpj for companies is reasonable from domain knowledge, but the description itself adds no parameter semantics, so the burden falls on the user.

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 explicitly states the tool's function: 'Certidão Negativa de Débitos, consulta em fonte oficial' (query negative debt certificate from official source). It uses a specific verb (consultar) and resource (certidão negativa de débitos). It clearly differentiates from siblings which are generic (authenticate, connect, marketplace, etc.) and unrelated.

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 clear context: it is for querying a municipality's tax debt certificate and mentions it is hosted by the platform with prepaid credit. It implies usage for checking a person's or company's debt status, but does not explicitly state when to use it versus alternatives. Since no alternative tools exist in the sibling list, this is adequate.

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 disclose readOnly=false, destructive=false, and idempotent=true. The description adds the behavioral nuance that conversation is used for reproduction, but does not elaborate on side effects or submission confirmation. 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?

Two concise sentences front-load the purpose and deliver a specific usage hint. Every word earns its place, with no redundancy or fluff.

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 is brief but not fully complete: it ignores the 'message' and 'context' parameters and contains a parameter type mismatch. With no output schema, a bit more detail about the result would have helped, though annotations cover the safety profile.

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 mentions the conversation parameter but calls it an 'array' while the schema declares it as a string, creating a mismatch. It also omits the required 'message' parameter and the optional 'context' parameter.

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 with a specific verb ('Report') and names the resource types (bug, missing feature, feedback). It is distinct from sibling tools, though it does not 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?

It provides clear usage context: use this tool to report issues or feedback, and include the conversation for reproduction. It does not mention when not to use it or name alternatives, but siblings are unrelated.

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 non-destructive behavior. The description adds that it shows 'MCP platform and adapter versions,' which gives a specific sense of what information is returned. No contradiction. It doesn't describe output format, but since no output schema exists, the description could clarify what format the version info takes, though the bar is lowered by the strong 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 one sentence, clear and front-loaded with the verb 'Show.' It is appropriately sized for a simple informational tool with no parameters. 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 tool's simplicity (no parameters, no output schema), the description is reasonably complete. It states what the tool shows. However, it could mention the return format or how the version info is structured, but with high annotation coverage, this is adequate for a minimal version 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 zero parameters, and schema coverage is 100% (vacuously). The description doesn't need to explain parameters. Baseline for zero parameters is 4. The description adds nothing about parameters but doesn't need to.

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 shows current MCP platform and adapter versions. It distinguishes from siblings like connect, authenticate, and report_bug, which have different purposes. However, it doesn't explicitly differentiate from toolkit_info, which might also return version 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?

The description implies when to use it (when you need version info) but provides no explicit guidance on when not to use it or alternatives. Given the sibling tools, it doesn't mention that toolkit_info could be an alternative. No context about typical 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=true, destructiveHint=false, and idempotentHint=true. The description complements this by adding behavioral context: it reveals what the tool does (returns state), and notably the annotation openWorldHint=false is interesting context that might suggest a closed world assumption. However, the description goes beyond the annotations by specifying what kind of state is returned (installed MCPs, connection status, accounts, catalog counts), and it implicitly confirms a read-only, non-destructive operation. Since annotations already cover the read-only and non-destructive aspects, the description's added value is in detailing the content of the output state, which is valuable.

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, information-dense sentence that front-loads the purpose and enumerates the key data points. Every element earns its place—no fluff, no redundancy. The colons and commas make it scannable, and the list of output categories is directly useful. This is a model of concise, effective 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 a zero-parameter, read-only tool with clear annotations and a comprehensive description, the context is complete. The description tells the agent exactly what to expect without needing to make an API call. The tool's simplicity is matched by an appropriately simple, complete description. There is no missing information about inputs, outputs, or side effects.

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 zero parameters and a schema description coverage of 100%, the description has little to add regarding parameters. The baseline for 0-param tools is 4, which is appropriate here. The description does an excellent job of explaining what the tool returns, making up for the lack of parameters. The description adds context beyond the schema by explaining what 'toolkit state' means in concrete terms (installed MCPs, connection status, accounts, catalog counts), which is exactly what an agent needs to know.

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 what the tool does: returns the current toolkit state, listing installed MCPs, their connection status, connected accounts, and catalog tool counts. The verb 'Returns' is specific, and the resource (toolkit state) is clearly defined. While sibling tools like 'connect' and 'authenticate' are distinct, the description's specificity makes the 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 clearly implies when to use this tool: whenever an agent needs an overview of the current toolkit state, such as which MCPs are installed, their connection status, and connected accounts. It doesn't explicitly mention when not to use it or name alternatives, but given the sibling list (connect, authenticate, marketplace, etc.), the use case is clear and distinct. A small deduction for not explicitly stating 'use this when you need to see the current state before taking actions like connecting or authenticating.'

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