SINTEGRA: PA

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

Annotations indicate idempotentHint=true and destructiveHint=false, which the description does not contradict. The description adds behavioral context: it explains that the token can be stored permanently in config or used session-only, and that calling with no args returns a link. It does not mention side effects like browser interaction, but the annotations cover safety. The description adds value beyond annotations by explaining the two modes and the token handling.

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 front-loaded with the main purpose. It uses two sentences to convey the key information, with no fluff. However, it could be slightly more structured (e.g., separating the two methods clearly), but overall it is efficient and readable.

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 (one optional param, no output schema), the description is fairly complete. It explains the two authentication flows and the token handling. It could mention what the response looks like (e.g., success message) but that is not critical. The description covers the essential usage scenarios and is adequate for an agent to invoke the tool correctly.

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 one optional parameter 'token' with no description (0% coverage). The description explains that the token is a JWT to be passed after the user pastes it, and that calling with no args gets the link. This adds meaning beyond the schema, but it does not specify the token format or validation. Since the schema is minimal, the description partially compensates, but could be more detailed about the token's role.

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: to authenticate the MCP.AI server for IDE agents by logging in and obtaining an access token. It distinguishes itself from siblings by focusing on authentication, while siblings like 'connect' and 'marketplace' serve different functions. However, it could be more explicit about the resource being authenticated (the server) and the exact action (obtaining a token).

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 usage guidance: it explains two methods (permanent via config header, session-only via token argument) and when to use each. It also tells the agent to call with no args to get the link, and with a token after the user pastes it. This clearly differentiates from alternatives and gives actionable steps.

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 destructiveHint, covering safety. The description adds valuable context on return states: when all providers are connected, it returns authenticated:true and empty pending[]; when credentials are missing, it returns connect_url and per-install URLs. This goes beyond what annotations alone provide.

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, front-loaded with the primary function, and every sentence contributes meaningful information about behavior. No superfluous content or repetition of the tool name/title.

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 read-only status tool with no parameters and no output schema, the description covers the two relevant return scenarios. It could be more complete by defining 'providers' or elaborating on per-install URLs, but these are minor gaps given the tool's simplicity and strong 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 parameters, so the baseline is 4. The description correctly focuses on return states rather than parameter details, which are nonexistent. Schema coverage is trivially 100%, so no additional 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 clearly states the tool's function: 'Returns connection status and URLs.' It uses a specific verb and resource, and distinguishes itself from siblings like 'authenticate' by focusing on status rather than performing authentication. The two-mode explanation adds further specificity.

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 checking connection status and determining next steps (e.g., when credentials are missing, it returns connect_url). However, it does not explicitly state when to use this tool versus alternatives like 'authenticate' or 'toolkit_info'. No exclusions or named alternatives are provided.

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 only give readOnlyHint=false and openWorldHint=true. The description adds substantial behavioral context beyond these: the invoke-runs-without-install semantics ('runs the tool pontualmente (one-off), without adding the MCP to the toolkit'), auth-required link behavior, empty-wallet checkout links, workspace-owner/admin permission requirements, and the retry-after-user-action flow. No contradiction with annotations (readOnlyHint=false is consistent with the described writes/mutations).

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 information-dense — it front-loads the core value proposition, uses a 'KEY:' marker to highlight the most important nuance about invoke, and organizes content logically (marketplace flow → permissions → prompt library). It avoids filler and every sentence carries meaning for a tool with 23 params and 14 actions. It loses a point for being a dense wall of text with the minor 'pontualmente' oddity and some redundancy around invoke's behavior.

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 complexity (23 params, 14 enum actions, no output schema), the description covers the conceptual model well: discovery/execution distinction, persistence semantics, billing/auth states, role-based permissions, and the secondary prompt-library feature. Some gaps remain: no error handling guidance, no response shape hints (especially relevant with no output schema), and no mapping of all action/params combinations. Still, it is notably complete for the main workflows.

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 carries the full burden, and it does add meaning for several key params (action=search/describe/invoke, 'pick the right tool_id', arguments via '{{variables}} filled', prompt_vars for the prompt flow, cancel_reason enumerations implicitly for subscription cancellation). However, 23 params exist and many (limit, immediate, tier_slug, conversation, request_details, cancel_reason codes) are never mentioned. The narrative provides strong semantics for the core flow but leaves the long tail undocumented.

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 is explicit about the specific verb+resource: it is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It clearly differentiates the core flows (search → describe → invoke), contrasts invoke vs install, and even notes the secondary prompt-library feature. The description meaningfully distinguishes this omni-tool from potential siblings by laying out its action-based scope.

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: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use', and contrasts invoke vs list_tools and search_* vs get_prompt. It explicitly names internal alternatives with clear routing logic (e.g., 'request_mcp asks us to build a NEW MCP when nothing fits'). This meets the bar for explicit when/when-not/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 include idempotentHint=truecker, destructiveHint=false, and readOnlyHint=false, indicating a safe, non-mutating operation, which the description does not contradict. Since no annotations are provided for behavior like rate limits or data sensitivity, the description adds the instruction to include conversation data, which hints at the need for context. However, it does not disclose what happens after submission (e.g., no confirmation), but given the safety profile, a baseline of 3 is fair.

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: two sentences that cover the main purpose and a critical usage detail. It is front-loaded with the action, and every word earns its place. No fluff or 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?

For a simple feedback tool with 3 parameters, a required field, and no output schema, the description provides essential guidance (include conversation array) and clear purpose. The absence of output schema is acceptable since the tool likely reports success/failure. The description is sufficient for an agent to use the tool correctly for reporting bugs/feedback, so a 4 is justified.

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%, meaning the schema provides only parameter names and types, with no additional meaning. The description mentions the 'conversation' parameter (the conversation array) and its importance, adding some semantics beyond the schema. However, it does not explain the 'context' parameter or the format of 'conversation' beyond being a string (likely JSON). With 0% coverage, the description should compensate more, but it does partially, so a 3 is appropriate.

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: to report bugs, missing features, or send feedback. It also specifies a key requirement (include the conversation array) for reproduction, which adds value beyond the name. However, it does not explicitly distinguish itself from the sibling tool 'show_version' or other potential feedback channels, but given the sibling list, none are directly similar, so a 4 is appropriate.

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 reporting bugs/feedback) and gives a critical instruction (include conversation array). It does not explicitly state when not to use it or mention alternatives, but the context is fairly clear from the purpose. This is adequate but lacks explicit exclusions or alternative guidance, so a 3 is suitable.

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 destructiveHint, so the safety profile is covered. The description adds the specific scope (platform and adapter versions) but no additional behavioral traits such as return format or latency expectations.

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 with no filler or redundancy. Every word contributes to understanding the tool's purpose.

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 trivial zero-parameter version query. Annotations cover safety and idempotency, and the description clearly states what information will be shown. No additional context is necessary.

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 baseline is 4. There is nothing to explain beyond the schema, which is already fully covered at 100%.

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') with a clear resource ('current MCP platform and adapter versions'). This distinguishes it from all sibling tools, none of which relate to version reporting.

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 about when to use this tool versus alternatives, or any exclusions. While the tool is simple, the description gives no explicit context about when it is appropriate to call.

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 valuable context: it is hosted by the platform, requires no platform credentials, charges per query with prepaid credit, and clarifies data is not confidential and the client is data controller under LGPD. This 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 a single, dense paragraph that front-loads the purpose and includes key operational details (payment, hosting, LGPD). It is concise but could be slightly more structured; however, every sentence 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?

Given the tool has no output schema and three undocumented parameters, the description provides some context (official source, payment model, LGPD) but lacks critical information about how to use the parameters, whether they are mutually exclusive, and what the response contains. It is adequate for a simple query tool but leaves gaps.

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%, and the description does not explain the three parameters (ie, cpf, cnpj) beyond their names. The description mentions consultation of official sources but does not clarify that these are likely identifiers (Inscrição Estadual, CPF, CNPJ) or that at least one is required. With zero coverage, the description should compensate but does not.

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 performs a SINTEGRA PA consultation from an official source, specifying the state (PA) and the nature of the data (official Brazilian sources, not confidential). It distinguishes from siblings by being the only consultation tool among generic platform tools (authenticate, connect, etc.), though it doesn't explicitly name 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 usage for querying official Brazilian data with prepaid credits, and mentions the client is responsible for legitimate purpose under LGPD. However, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites beyond payment.

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 destructiveHint, which cover safety. The description adds value by specifying the exact content returned (installed MCPs, connection status, accounts, catalog tool counts), which goes beyond the annotations and clarifies the tool's behavior.

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, concise sentence that front-loads the primary action ('Returns the current toolkit state') and then specifies the includes. No excess words or redundant phrasing; every element contributes to clarity.

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 (no parameters, no output schema, and annotations providing safety context), the description adequately covers what the tool does and what it returns. It is sufficient for an agent to invoke the tool correctly without further documentation.

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 are no parameter semantics to describe. Per the rubric, the baseline is 4 for tools with no parameters; no explicit parameter information 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 clearly states the tool returns the current toolkit state and enumerates specific data included (installed MCPs, connection status, connected accounts, and catalog tool counts). This distinctively separates it from siblings like show_version or connect, which have different purposes.

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 the tool is for retrieving toolkit state, but it does not explicitly mention when to use it versus alternatives (e.g., when debugging connections or before using connect/authenticate). No exclusions or alternative tools are referenced, so usage guidance is only implied.

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