Prefeitura BA Salvador: Certidão Negativa de Débitos

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

Annotations already mark the tool as idempotent, non-read-only, and non-destructive. The description adds useful context: it returns a link when called with no args, accepts a JWT for session-only login, and notes that a config header provides a permanent connection. This clarifies the tool's behavior beyond the annotations without contradicting them.

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 run-on sentence that packs in product branding, instructions, and options. It is front-loaded with the core purpose but could be more streamlined. The two use cases (config vs. paste, token vs. no args) are muddled together, making it less scannable than ideal.

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 authentication helper, the description covers the primary flows: getting a link, using a token, and the recommended config approach. However, it does not mention response format, error handling, or what happens on failed authentication. Given the lack of an output schema, a bit more detail on return values 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?

Although the schema provides no description for the 'token' parameter, the prose description explains that it is a JWT pasted by the user and used for session-only login. This adds meaningful semantics that the schema lacks, effectively compensating for the 0% 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 a user for MCP.AI in IDE agents by either returning a login link or accepting a pasted token. It uses specific verbs like 'log in' and 'paste' and identifies the resource (access token). While it doesn't explicitly contrast with sibling 'connect', the authentication flow is distinct and understandable.

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 call with a token versus no arguments and recommends a config-based approach for permanent access, giving some usage context. However, it does not contrast this tool with sibling tools or mention any exclusions, leaving the 'when to use this vs alternatives' implicit.

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 establish read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral detail beyond annotations by specifying the two possible outcomes: authenticated:true with empty pending[], and missing credentials producing connect_url and per-install URLs.

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, no filler, with the most important behavioral distinctions front-loaded. Every sentence contributes useful information.

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, parameterless status tool, the description covers the key inputs and expected outputs: authenticated state, pending array, and URL fields under both connected and missing-credential scenarios. No output schema exists, so these behavioral details carry the necessary 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?

This tool has zero parameters, so the schema requires no semantic explanation. The baseline of 4 for zero-parameter tools applies here; the description cannot meaningfully add parameter information.

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 opens with a specific verb and resource: 'Returns connection status and URLs.' It clearly differentiates this from the sibling 'authenticate' tool by framing it as a state-check/status report rather than an action.

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 contextual guidance by describing what the user gets when providers are connected versus when credentials are missing. It does not explicitly name alternatives like 'authenticate', but the state-based behavior makes the intended use case 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?

The description goes well beyond the annotations by explaining that writes require workspace owner/admin, invoke performs a one-off install, and invoke returns connect or checkout links depending on credentials/wallet state. It also clarifies that search/describe flag installed_in_toolkit vs installed_in_workspace, and that published prompt links open without login. No contradictions with annotations exist.

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 dense and information-packed, with no filler, and front-loads the core purpose and flow. It is a single long paragraph rather than structured bullet points, but the logical progression from main flow to key invoke behavior to alternatives to prompt library keeps it navigable.

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 23-parameter, multi-action tool with no output schema, the description covers an impressive amount: core workflow, permissions, billing/credential edge cases, installed flags, and return-link behavior for prompts. Gaps remain around uninstall/resume semantics and a few action-specific parameters, but the overall behavioral landscape is well specified.

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, the description compensates by explaining the critical `action` parameter semantics: search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, and the prompt-library actions. It also adds meaning to `tool_id`, `prompt_vars`, and the prompt slug/link. However, some parameters like `immediate`, `tier_slug`, `cancel_reason`, and `conversation` remain unexplained, so coverage is strong but not complete.

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: a catalog of MCPs/tools plus the runtime to execute them. It explicitly names the core flow (search → describe → invoke) and distinguishes the tool from siblings by positioning it as the platform-level catalog/executor rather than a specific utility like authenticate or 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 gives explicit usage direction: use invoke for one-off execution when the MCP is not installed, use install only to make an MCP permanent, use list_tools to see what is callable now, and use request_mcp when nothing fits. It also covers credential/billing edge cases and tells the agent to retry after the user completes connect or 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?

The annotations already mark readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context: it is hosted, requires no platform credentials, is paid, queries official public (non-confidential) data, and imposes LGPD controller obligations on the client. This complements the annotations 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 extremely efficient—three sentences convey purpose, hosting/payment model, and LGPD context, all front-loaded with the certificate type. No filler or redundant repetition of annotations.

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 query tool with 2 optional parameters and no output schema, the description covers purpose, access, payment, and data handling. However, it does not describe the return format or potential errors, which are relevant in the absence of an output schema, so it is not fully 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 input schema provides only cpf and cnpj with zero descriptions (0% coverage). The description fails to explain which identifier to provide, accepted formats, or whether one or both are required. It offers no meaningful parameter semantics beyond what the schema already lists, so it does not compensate for the coverage 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's function: 'consulta em fonte oficial' for 'Certidão Negativa de Débitos' from Prefeitura BA Salvador. This specific verb+resource combination distinguishes it from generic 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?

It provides clear context on usage: hosted on the platform, no platform credentials required, pay-per-query via prepaid credit, and appropriate use under LGPD. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a full 5.

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 idempotentHint=true and destructiveHint=false, so the description doesn't need to repeat that. It adds context about including the conversation for reproduction, which implies the tool transmits data. No contradictions are present, and the description's minimal additional detail is sufficient for a simple feedback tool.

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, no fluff. The first sentence states purpose, the second gives actionable usage guidance. Perfectly front-loaded and concise.

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 3 parameters and no output schema, the description covers the essential purpose and the key usage hint (including conversation). The only gap is the lack of explanation for the 'context' parameter, which is a minor omission.

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 has 0% description coverage, so the description must compensate. It mentions the 'conversation array' but not its string format or the 'context' parameter. The 'message' parameter is implied but not explicitly explained. Some value is added, but not all parameters are covered.

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: 'Report a bug, missing feature, or send feedback.' This is a specific verb+resource combination that distinguishes it from sibling tools like authenticate or marketplace, which cover 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?

It provides clear usage context by stating when to use the tool ('Report a bug, missing feature, or send feedback') and gives an explicit instruction to 'Include the conversation array with recent messages for reproduction.' It does not mention exclusions or alternatives, but sibling tools are unrelated, so the guidance 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 indicate read-only, idempotent, and non-destructive behavior. The description aligns with these and adds that it retrieves current state, but does not provide extra detail on side effects (none expected).

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 a single, concise sentence that fully conveys the tool's purpose without unnecessary 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?

The description is complete for usage, though it does not specify the output format or structure. Given the simplicity and typical expectation of a version query, this is acceptable.

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 no parameters; schema coverage is complete, and no further explanation is 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?

Description clearly states the tool shows current MCP platform and adapter versions, with a specific verb and resource, making its 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 implies when to use it (when version info is needed), but it does not explicitly mention alternatives or when not to use it. Context is clear enough for a simple query 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 declare readOnlyHint=true and idempotentHint=true, so the description doesn't need to restate safety. It adds value by specifying exactly what data is returned (installed MCPs, connection status, accounts, catalog tool counts), which goes 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 concise and complete—one sentence with no fluff. It clearly enumerates the returned information without unnecessary 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?

For a no-parameter read-only tool, the description covers the essential aspects: what it does and what it returns. It doesn't mention edge cases like empty results, but that's not critical for such a simple tool. Overall, it is sufficiently complete given the annotations.

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 parametershare, so there is nothing to document. Schema coverage is 100% and there are no parameter details needed. The description sufficiently clarifies what the tool outputs.

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 the current toolkit state with specific components: installed MCPs, connection status, accounts, and catalog tool counts. This is a distinct purpose compared to sibling tools like authenticate or connect, which perform 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 usage for inspecting the toolkit's current state but does not explicitly contrast with alternatives. However, the tool name and description make it obvious that it is for information retrieval, not for performing actions.

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