Prefeitura RS Porto Alegre: Comprovante de Inscrição do ISSQN

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

Annotations already declare idempotent=true and readOnly=false; the description adds meaningful context about token lifetime ('non-expiring' vs 'session-only') and the browser login flow. It doesn't discuss failure modes or side effects, but the core auth behavior is 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 a bit run-on and mixes config setup with tool instructions, but the main behavior and token/no-token paths are front-loaded and every clause adds actionable detail. It could be tightened, but it is not padded.

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 auth tool with no output schema, the description covers the complete flow: browser login, token copy, config alternative, and session-only usage. It doesn't specify return format or error behavior, but those are less critical for this interactive 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?

Schema coverage is 0% for the single optional token parameter, so the description must compensate. It does: it explains the token is a JWT, that it can be pasted after browser login, and that omitting it triggers the login-link flow.

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 indicates the tool handles authentication for MCP.AI IDE agents, including how to log in and pass a token. It doesn't explicitly contrast with sibling tools like connect, but the verb-and-resource intent ('authenticate', 'login') is 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?

It explicitly distinguishes between a permanent config-header approach and a session-only token paste, and states when to call with { token } vs no args to obtain the login link. This is strong practical guidance for choosing the right invocation mode.

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 this as readOnly, idempotent, and non-destructive. The description adds useful behavioral context by explaining the conditional output: authenticated:true with empty pending[] when all providers are connected, and connect_url plus per-install URLs when credentials are missing. This goes beyond annotation-only information.

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 composed of two focused sentences that lead with the core action and then provide the key conditional output states. Every sentence adds value and 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?

Without an output schema, the description appropriately explains the main return conditions and fields: authenticated, pending[], connect_url, and per-install URLs. It is complete enough for a simple zero-parameter read-only tool, though it does not elaborate on the exact shape of the URLs.

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 there is no parameter burden for the description to carry. The input schema is empty and schema description coverage is effectively 100%, so the baseline of 4 applies; no further parameter 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?

The description uses a specific verb ('Returns') and identifies a clear resource ('connection status and URLs'). It describes the resource well enough to be distinguished from sibling tools like 'authenticate', though it does not explicitly name that sibling as a different operation.

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 the tool—when connection status or URLs are needed—by stating what it returns. However, it does not explicitly compare it to alternatives like 'authenticate' or state when not to use it, leaving usage context only implied.

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 key behaviors beyond annotations: invoke runs one-off without installing, may return connect/checkout links, install makes permanent, and writes require owner/admin. Annotations already indicate non-read-only (readOnlyHint false), but the description adds critical side-effect context and failures.

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 but organized around the core flow, with key points front-loaded. It is longer than typical but every sentence adds essential guidance. It could be slightly more structured with bullet points, but the paragraph form is acceptable.

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 complex tool with 23 parameters and no output schema, the description is remarkably complete: it covers all major actions, side effects, permission needs, and even the prompt library sub-feature. It leaves no major use case unexplained.

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?

Despite 0% schema coverage, the description explains the core parameter `action` thoroughly through the flow descriptions, and gives context for mcp_id, tool_id, and prompt-related parameters. However, it does not document all 23 parameters (e.g., arguments format, cancel_reason enums), leaving some gap, but the main driver is well-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 as the mcp.ai marketplace that catalogs and runs MCP tools, with a specific flow (search→describe→invoke) and distinguishes it from siblings by covering both discovery and execution. It uses specific verbs like 'search', 'describe', 'invoke', and 'install' with clear resource targets.

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 when-to-use guidance for each action, including when to prefer invoke over install ('prefer invoke for a single/occasional use'), permission requirements for writes, and how to handle connect/checkout links. It also gives concrete examples like 'find an MCP that does X'.

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, idempotentHint, and non-destructive nature, so the description correctly aligns with these. However, it adds useful context about payment via prepaid credits, absence of platform credentials, and LGPD responsibility, but lacks details on query behavior or limitations beyond that. The description doesn't contradict annotations, but it could disclose more about response structure or rate limits.

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 paragraph of moderate length, containing diverse information from purpose to legal notes. It is relatively concise and front-loaded with the tool's main function, but includes some extra context (payment details, LGPD) that could be seen as secondary. Still, it remains efficient without 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?

The description covers purpose, payment model, data source, and legal responsibility, but lacks parameter explanation and any details about the query process or results. Given 4 parameters and no output schema, a more complete description would include how the identifiers are used and what a response looks like. It is adequate but not fully complete for a complex data consultation 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 schema description coverage at 0%, the description is responsible for explaining parameters. It does not mention the four parameters (ie, cpf, cnpj, nire) at all, leaving the agent to infer that these are likely identifiers. It adds no detail on format, usage, or required combinations, which is a significant gap given 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 that the tool retrieves the official ISSQN enrollment certificate from the Porto Alegre city hall, distinguishing it as a specific government data query. Although it doesn't explicitly compare to siblings, the verb 'consultar' and the official source specificity provide a clear 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 explains that it queries official Brazilian sources available to citizens, and indicates it is not confidential data, giving context on when it is appropriate to use. It does not explicitly list exclusions or alternatives like sibling tools, but the clarity of scope (official non-confidential data) provides adequate 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 indicate the tool is idempotent, not read-only, and not destructive. The description adds the useful behavioral detail that the conversation array is needed for reproduction, but it does not disclose possible side effects, output behavior, or whether duplicate reports are filtered.

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: the first states the purpose, and the second gives the key usage hint. Every sentence earns its place, and there is no redundant information or verbose phrasing.

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, has no output schema, and the description covers purpose plus the critical reproduction requirement. However, it omits any detail about what the user should expect after reporting, such as confirmation or a ticket reference, and the optional 'context' parameter remains unexplained.

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 add meaning. It clarifies the 'conversation' parameter's purpose by saying to include recent messages for reproduction, but it does not explain the 'message' or 'context' fields beyond what their names imply. This is partial compensation but leaves gaps.

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 action: 'Report a bug, missing feature, or send feedback.' This uses a specific verb and resource, and no sibling tool covers a similar reporting function, so it is easy to distinguish.

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 explicitly defines when to use the tool (for bugs, missing features, or feedback) and provides a clear procedural instruction: include the conversation array for reproduction. It does not mention exclusions or alternatives, but none of the sibling tools overlap with this reporting purpose.

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 agent knows this is a safe read operation. The description adds minimal behavioral context via 'current' (suggesting live values) but does not disclose return format or any auth/connection requirements.

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 directly states the tool's purpose with no redundant or filler content.

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 tool with safety annotations, the description is nearly complete: it clearly names what the tool reports. It leaves minor gaps around return format and whether authentication/connection is required, but these are not critical for a simple version query.

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 zero parameters and schema description coverage is 100%, so there is nothing for the description to explain. The baseline score of 4 for zero-parameter tools applies.

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 a clear resource ('current MCP platform and adapter versions'), making the tool's function unambiguous. However, it does not explicitly distinguish this from sibling tools like toolkit_info, which could cover similar informational ground.

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 no guidance on when to use this tool versus alternatives such as authenticate or toolkit_info. It states only what the tool does, leaving usage context implied at best.

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 signal readOnlyHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral context about the exact contents of the returned state, and there is no contradiction with the 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 sentence with the main outcome front-loaded and a concise list of details. Every phrase adds value.

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?

This is a simple, parameterless status-read tool with strong annotations and no output schema. The description fully conveys what is returned and leaves no material gaps for an agent choosing or invoking 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?

The tool has zero parameters, so the schema provides all needed information. The baseline of 4 applies; the description does not need to explain parameter behavior.

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+resource ('Returns the current toolkit state') and lists concrete output components: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from siblings like authenticate, connect, 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 establishes a clear read-only informational use case: inspect toolkit state and connectivity. It does not explicitly name alternatives or exclusions, but the context is strong enough for an agent to select this tool over the sibling tools.

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