Prefeitura SP São Paulo: Emissão Parcela Simples Nacional

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

The annotations (readOnly: false, idempotent: true) are complemented by the description explaining that the token can be permanent (config header) or session-only (passed directly), and that it initiates a browser login flow. It discloses the need for user interaction and the difference between the two modes, adding value beyond the minimal 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 three sentences, front-loaded with the core purpose and then detailing usage options. While slightly verbose, every part serves a purpose—no filler. It could be tightened but remains efficient and well-structured.

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 simple nature of the tool (one optional parameter, no output schema), the description covers the essential behavior: how to authenticate permanently or temporarily, and how to get the login link. It does not explicitly state what the response looks like after token submission (e.g., success/failure), but this is a minor gap for such a focused 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 compensates well by explaining the `token` parameter: it expects a JWT string and is used for session-only login. It also implies that calling without arguments yields a login link. This provides full meaning for the sole parameter beyond its raw schema definition.

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: authentication for MCP.AI IDE agents via browser login and token acquisition. It distinguishes itself from sibling tools like 'connect' and 'marketplace' by focusing specifically on token-based authentication with two usage modes (permanent config vs session-only). The verb 'authenticate' is specific and the resource is well-defined.

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 clear instructions on when to use each mode: best practice is adding the token to server config for permanent access, or pasting it for session-only login. It also explains the no-args call to get the link. However, it does not explicitly state when not to use this tool (e.g., if already authenticated), 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 read-only, idempotent, non-destructive. Description adds detail on conditional returns, enhancing 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?

Concise two-sentence description, 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?

Given no output schema, description explains return values with scenarios. Could specify more but sufficient for 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?

No parameters exist; schema coverage is 100%, so baseline of 3 applies. Description adds no parameter info.

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 tool returns connection status and URLs, and distinguishes from siblings by specifying conditions.

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: to check connection status, with scenarios for all providers connected vs missing credentials. No explicit alternative comparison, but it's 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 discloses key behavioral traits beyond annotations: writes 'require workspace owner/admin', invoke returns a connect link if credentials are needed, and returns a checkout/top-up link if the wallet is empty. It also clarifies that invoke does not bloat the tool list. This is consistent with readOnlyHint=false and adds useful operational context.

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 front-loaded with the core flow, and the length is largely justified given the 14 actions and prompt library coverage. However, it is a single long paragraph with complex clauses; a structured list or bulleted action breakdown would improve scannability.

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 high-complexity tool with no output schema, the description covers the primary flows, permission requirements, auth/payment edge cases, and the prompt library. It is not a 5 because it omits details about list_tools output shape and several parameter behaviors, which would be valuable for fully correct invocation.

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% across 23 parameters, so the description must compensate. It does explain the meaning of action, tool_id, mcp_id, prompt_slug, and prompt_vars through the workflow narrative. However, many parameters like limit, query, immediate, tier_slug, conversation, cancel_reason, and report_context remain unexplained in both the schema and the description, leaving 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 opens by clearly defining the tool as the 'official mcp.ai marketplace' and explains the core search → describe → invoke flow, giving a specific verb+resource scope. It also distinguishes itself from sibling tools by covering both the MCP catalog and the prompt library as distinct capabilities.

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 when-to-use guidance, especially around invoke vs install: 'KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente...' and 'prefer invoke for a single/occasional use.' It also explains when to use subscribe/cancel, report_bug, request_mcp, and the prompt actions, providing clear 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds context beyond annotations by mentioning that it is a paid service ('pague por consulta com crédito pré-pago') and that no platform credentials are needed. It also states the data is not confidential and the client is responsible for legitimate use. This adds some behavioral context, though it does not detail response formats, error behavior, or rate limits. 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?

The description is a few sentences and front-loads the core purpose. It includes necessary compliance and payment details without excessive verbosity. The structure is logical: purpose first, then operational and legal notes. It is efficient and avoids redundancy, though the compliance sentence could be trimmed without losing 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?

Given the tool has three parameters and no output schema, the description should at least explain what data is returned and how to use the input fields. It does not describe the return value, what a successful query looks like, or how to construct a valid request (e.g., required fields, optional fields). The legal and operational context is helpful, but the lack of parameter and output details leaves the agent under-informed for a successful invocation.

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 three parameters (cnpj, numero_acordo, numero_parcela) with zero schema description coverage. The description does not explain any of these parameters, their purpose, format, or necessary combinations. It only alludes to the general topic (Simples Nacional installments) without linking to the specific fields. This is a complete lack of parameter information, forcing the agent to guess at expected values.

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: querying Simples Nacional installments (Parcela Simples Nacional) from the São Paulo city hall through an official source. The verb 'consultar' and resource 'Parcela Simples Nacional' are specific, and the description distinguishes it from sibling tools, which are unrelated (authentication, marketplace, etc.). The purpose is 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 context on usage: it's hosted by the platform, requires no platform credentials, and payment is per query with prepaid credit. It also clarifies the legal side (client is data controller, LGPD). However, it does not explicitly mention when to use this tool versus alternatives or any exclusion criteria. Given the uniqueness of the tool, the lack of explicit alternatives is acceptable, but the guidance could be more direct.

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 convey readOnlyHint=false and destructiveHint=false, so the safety profile is covered. The description adds useful reproduction context but does not disclose what happens after submitting (e.g., whether a ticket is created, if duplicate reports occur), and idempotentHint=true sits oddly with the implied side effect of creating a bug report, though not a direct 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 two sentences with no filler. It front-loads the purpose and then gives one actionable instruction for reproduction. Every word 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?

Given the simple schema (three string parameters, no output schema) and available annotations, the description covers the core use case and the one non-obvious requirement (conversation). It is incomplete on parameter semantics and does not describe expected results, but it is minimally sufficient for a straightforward feedback 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 description coverage is 0%, so the description must compensate. It only explains the 'conversation' parameter ('Include the conversation array with recent messages'), but even that is misaligned with the schema, which declares conversation as a string, not an array. It gives no guidance for the required 'message' parameter or 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 uses a specific verb ('Report') and names the resources: 'a bug, missing feature, or send feedback'. It is clear and distinct from sibling tools like authenticate or show_version, though it does not explicitly contrast itself with alternatives.

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 ('Report a bug, missing feature, or send feedback') and adds reproduction guidance ('Include the conversation array with recent messages'). However, it provides no explicit when-not-to-use guidance or alternatives, leaving usage context implied rather than explicit.

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 safety profile is clear. The description adds value by specifying what kind of version data is exposed (MCP platform and adapter), which is relevant behavioral context beyond the raw 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 that fully defines the tool's purpose without any wasted words. It front-loads the verb and specifies the exact object of the action.

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, idempotent tool with no output schema, the description is complete. It tells the user exactly what information will be shown, and nothing more is required to invoke or reason about 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 and the schema is entirely described (100% coverage), so there is nothing for the description to clarify. The baseline for no-parameter tools is 4, and no additional parameter semantics are 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 ('Show') and a specific resource ('current MCP platform and adapter versions'), making the tool's purpose immediately clear. It differentiates itself from siblings like toolkit_info by naming exactly which versions are returned.

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 context is implied by the zero-parameter, self-contained nature of the tool: call it when you need current platform or adapter version information. It does not explicitly name alternatives or exclusions, but no complex decision is needed for a simple version query.

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 destructiveHint=false, so the agent knows it's a safe read. The description adds that it returns connection status and accounts, but does not mention response format, error cases, or permission requirements. With annotations covering safety, the description provides moderate additional clarity.

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 efficiently lists the tool's return content: installed MCPs, connection status, connected accounts, and catalog tool counts. No wasted words, front-loaded with 'Returns'.

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 is read-only with no parameters and no output schema, the description adequately explains what it returns. It doesn't mention edge cases like no MCPs installed, but for a simple state query, it's complete enough. Sibling tools include authentication and connectivity tools, so the description covers the tool's role.

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)Skip. According to guidelines, 0 params = baseline 4. Since there are no parameters to document, the description doesn't need to add anything. It correctly omits 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 explicitly states the tool returns the current toolkit state, listing the key data items (installed MCPs, connection status, accounts, catalog tool counts). This is precise and unambiguous, leaving no doubt about the tool's function.

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 does not indicate when an agent should call this tool (e.g., before performing marketplace operations or troubleshooting). It only describes what it returns, without guidance on scenarios like checking connectivity after a failed operation. There is no mention of prerequisites or recommended usage context.

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