Prefeitura CE Caucaia: Certidão Negativa de Débitos

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

The description adds details about two authentication methods (permanent config vs session-only) and the expected token argument. It goes beyond the sparse annotations by explaining the login interaction flow, though it doesn't describe potential side effects or 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 relatively long and includes multiple clauses, mixing config instructions with call syntax. It could be tightened to front-load the essential purpose more clearly.

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 auth tool with one optional parameter and no output schema, the description covers the core usage: obtaining a link, passing a token, and permanent vs session-only. It lacks details on return values or error conditions, but overall it's reasonably complete.

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 explicitly explains the 'token' parameter by indicating it should contain the JWT pasted by the user, compensating for the schema's 0% description coverage. It also clarifies that calling with no arguments produces the login link.

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 this tool authenticates to MCP.AI for IDE agents, explaining the login flow with browser and token. It provides a specific verb and resource, though it doesn't explicitly compare with sibling tools like '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 explains when to use no arguments to get a login link versus passing a token for session login, and distinguishes between permanent header config and session-only auth. It gives clear context on usage but doesn't explicitly name alternatives.

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?

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds meaningful behavioral detail: it specifies exact return values for both connection states (authenticated:true with empty pending[], and connect_url plus per-install URLs). This gives a complete mental model of the output.

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, both purposeful: the first states the general purpose, the second covers the conditional output. No redundancy or filler, and key information is front-loaded.

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 low complexity, empty schema, and rich annotations, the description fully covers expected behavior in both possible connection states. No output schema is needed because the return values are explicitly described.

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 empty, so the description has nothing to add regarding parameters. Baseline for zero-parameter tools is 4, which is appropriate here.

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?

Description uses a specific verb 'Returns' with a clear resource ('connection status and URLs') and further details the two possible states. This distinguishes it from sibling tools like 'authenticate' which handles credential setup.

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 two concrete scenarios (all providers connected vs. credentials missing) that imply when to call the tool for status checks. It lacks an explicit 'when not to use' or direct reference to alternatives, but the context is sufficiently clear.

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 readOnlyHint=false, openWorldHint=true, and no destructive flag. The description adds valuable behavioral context: it discloses that writes require owner/admin, that invoke runs one-off without installing, and that it returns connect/payment links when needed. It does not contradict annotations and goes beyond them, though it could mention error handling or idempotency details.

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 well-structured: it opens with the core marketplace role, details the primary flow with punctuation and arrows, then separates the prompt library. Every section adds necessary context for a multi-action meta-tool. The length is justified given 14 possible actions, and the structure aids comprehension.

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 high complexity (23 parameters, 14 actions, no output schema), the description covers the essential workflow, auth requirements, payment behavior, and non-persistence of invoke. It explains return types for describe and list_tools but omits details on error responses or specific return formats for other actions like subscribe or publish_prompt. It is thorough but not exhaustive, which is acceptable for this scope.

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 description must compensate. It does explain the core parameters (action, mcp_id, tool_id, arguments) through the described flow and mentions prompt-related parameters in the prompt library section. However, it does not individually detail all 23 parameters, leaving some ambiguity for specialized actions like report_bug or subscribe. It compensates well for the main actions.

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.ai marketplace, explaining it serves as both a catalog and execution engine. It specifies the core flow (search → describe → invoke) and distinguishes from siblings like authenticate, connect, and toolkit_info. The purpose is highly specific 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 provides explicit guidance on when to use each action, notably differentiating invoke vs install ('prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'). It also explains the flow, mentions alternatives like request_mcp for new builds, and covers the prompt library actions. This is exemplary 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 mark it as read-only and idempotent. The description adds value by disclosing payment requirements (prepaid credit per query), lack of platform credentials, official non-sensitive data nature, and LGPD data controller responsibilities—details not captured in 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, well-structured paragraph that front-loads the purpose and then adds essential operational details. Every sentence contributes meaningful information 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?

While it covers purpose, payment, and data responsibility, it lacks explanation of the output (what the consultation returns) and does not clarify parameter selection (CPF vs CNPJ). Given no output schema, the description should indicate expected results, leaving incomplete 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?

The schema defines 'cpf' and 'cnpj' as strings with no description, and schema description coverage is 0%. The tool description does not mention these parameters at all, leaving the agent without guidance on which identifier to provide or expected formats. This is a critical 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 identifies the tool as a consultation for a negative debt certificate (Certidão Negativa de Débitos) from the Caucaia city hall, using the verb 'consultar' and specific resource. It is distinct from the generic sibling tools (authenticate, connect, etc.) which serve platform-level 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?

Provides context on when to use: for official Brazilian source queries, with prepaid credit and no platform credentials. It implies usage for CND verification but does not explicitly name alternatives or exclusions. Since no similar sibling tools exist, this is adequate context.

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=false and idempotentHint=true, covering some behavioral aspects. The description adds a key requirement about including the conversation array, which helps reproduction. However, it does not disclose side effects, permissions, or what happens after reporting. With annotations present, this is acceptable but not fully transparent.

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 filler. The first sentence states the purpose, the second gives an actionable instruction. Every word earns its place; it is appropriately sized for a simple tool.

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 three parameters, no output schema, and zero schema descriptions. The description explains the conversation parameter but leaves 'context' undocumented and does not explain return values or side effects. For a bug-reporting tool, this is a notable gap that could lead to incorrect usage.

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 must compensate. It explicitly mentions the 'conversation' parameter and its purpose, but it does not explain 'context' or 'message' fields. Since only one of three parameters is detailed, the description provides limited semantic value beyond the 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?

Description clearly states the tool's purpose: 'Report a bug, missing feature, or send feedback.' This is a specific verb ('Report') and resource (bug reports/feedback), and it distinguishes the tool from its siblings (none of which are bug-related). The name and title reinforce this clarity.

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 on how to use the tool ('Include the conversation array with recent messages for reproduction'), but it does not explicitly state when to use it versus alternatives. However, no sibling tool overlaps in function, so the implicit guidance is adequate. It lacks explicit exclusions but the purpose is unambiguous.

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, which covers the safety profile. The description adds 'Show' which aligns, but provides no extra behavioral context such as output format or latency. It is acceptable but not enriching beyond 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, straightforward sentence with no wasted words. It is front-loaded and to the point, exactly as concise as needed for such a simple tool.

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 parameterless read-only operation with full annotation coverage, the description is mostly sufficient. It states what versions are shown (MCP platform and adapter). However, it does not describe the return format or structure, which could be useful, but given the simplicity and annotation richness, it is adequate.

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, the schema trivially covers 100%. The description mentions the subject (versions) but does not need to explain params. The baseline for 0 params is 4, and the description offers sufficient clarity about what is being shown, so it meets the standard.

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?

Description clearly states the tool shows MCP platform and adapter versions with a specific verb ('Show') and resource. It is not tautological, but it does not differentiate from sibling 'toolkit_info' which could also provide version info. Still, it names the exact subject matter, so it's clear.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions. The description simply states what it does, leaving the agent to infer 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=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds useful context about the return content (installed MCPs, status, accounts, catalog counts) but does not disclose additional behaviors such as auth requirements, rate limits, or potential slowness. This is adequate given the annotation coverage.

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, front-loaded sentence that lists all key output facets without any filler. Every word contributes meaning, and the colon-delimited list is easy to parse.

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 no-parameter, read-only informational tool, the description covers the essential return dimensions (MCPs, status, accounts, catalog tool counts). It lacks an example response or error scenarios, but no output schema exists and complexity is low, so the description is reasonably complete.

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 an empty input schema, so there is nothing for the description to add semantically. Baseline for 0 params is 4; the description appropriately focuses on return value rather than nonexistent inputs.

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') with enumerated components: installed MCPs, connection status, accounts, and catalog tool counts. This clearly differentiates it from siblings like show_version (version info) and connect (establishing connections).

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 tool when you need an overview of toolkit state, including MCP connections and accounts. However, it does not explicitly state when NOT to use it or point to alternatives among the sibling tools, so the guidance remains implicit.

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