SINTEGRA: PB

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

The description goes beyond annotations by explaining the behavioral difference between permanent (config header) and session-only (passed token) authentication, and that calling with no arguments returns a link. Annotations already indicate it is idempotent and not destructive; the description adds meaningful context about how authentication state is managed.

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 compact, front-loaded with the tool's purpose, and each sentence conveys necessary operational detail. It avoids filler while covering the permanent config, session token, and no-argument cases.

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 no output schema, the description covers the main invocation paths and prerequisites. It doesn't specify return values or error cases, but the core flow is sufficiently complete for an agent to select and call 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?

Schema coverage is 0%, but the description fully explains the single `token` parameter: it is a JWT that the user pastes, it is optional, and omitting it triggers the link-generation behavior. This compensates completely for the bare 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?

The description clearly identifies the tool's purpose: authenticating to MCP.AI for IDE agents by logging in, copying an access token, and either configuring it permanently or passing it for a session. It distinguishes this from other tools by specifying the exact auth flow and the token/link behavior.

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 and how-to-use instructions: add a permanent Authorization header via config, or call with { token } for session-only login, or call with no args to receive the login link. It also contrasts the permanent and session-only approaches, which is effective 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?

Beyond the readOnlyHint, destructiveHint:false, and idempotentHint annotations, the description adds valuable behavioral detail by describing the two main result states, the authenticated flag, and the returned connection URLs. This gives the agent concrete expectations about 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 two sentences long, front-loaded with the core purpose, and contains no wasted words. It efficiently communicates the normal success state and the credential-missing fallback state.

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 zero-parameter read-only status tool, the description covers the key success and failure scenarios and the relevant returned fields. There is no output schema, but the text compensates for the important return values; it could still be more explicit about partial connection states.

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 takes zero parameters, so there are no parameter semantics for the description to clarify. The baseline 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 clearly states the operation as returning connection status and URLs, making it a read-only status check. It is specific but does not explicitly differentiate itself from the sibling authenticate tool.

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 through conditions ('When all providers are connected... When credentials are missing...'), but it never explicitly says when to use this tool versus authenticate or how to react to the returned URLs. The usage guidance is conveyed by the return-value conditions rather than direct instructions.

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, the description discloses substantial behavioral context: writes require workspace owner/admin, invoke runs one-off without bloating the toolkit, missing credentials return a connect link, unpaid usage returns a checkout/top-up link, and prompt share links open without login. These details go well beyond the generic readOnlyHint/openWorldHint annotations and present no 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 long and dense, but nearly every clause adds real behavioral or routing value, and it front-loads the core purpose and flow. It is structured as one run-on block, which hurts scanability, but given the tool's 14-action surface, the length is justified.

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 breadth and the absence of an output schema, the description covers discovery, invocation, installation, billing, bug reporting, MCP requests, and the prompt library. It explains connect/checkout retry flows and permission requirements, though it does not detail return shapes, error cases, or how this tool relates to sibling tools like authenticate/connect. This is strong but not exhaustive.

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 and 23 parameters, the description carries the parameter-semantics burden but only partially handles it. It explains the action enum values and names key identifiers like tool_id and mcp_id, but most parameters—arguments, immediate, tier_slug, prompt_body, report_context, request_details, etc.—are not individually explained. The agent gets strong action-level semantics but weak parameter-level detail.

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 — the in-platform catalog of every MCP/tool, AND the way to run them.' It names the core search → describe → invoke flow and distinguishes marketplace from sibling tools by covering discovery, execution, installation, billing, and prompt-library actions. This is a specific, resource-anchored purpose statement with strong sibling differentiation.

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 routing guidance: 'prefer invoke for a single/occasional use' vs. 'Use install only to make an MCP PERMANENT,' and defines list_tools as 'what is callable right now.' It also explains when to retry after a connect/checkout link and when to use request_mcp ('asks us to build a NEW MCP when nothing fits'). This is clear when-to-use versus when-not-to-use 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 declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true, covering safety and idempotency. The description adds the requirement to include conversation for reproduction, which is valuable behavioral context. However, it does not disclose side effects (e.g., sending data externally) or any other operational details beyond what annotations provide. With annotations present, the description adds some value but is not rich.

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, the second gives a key usage hint. It is front-loaded, concise, and every word earns its place. There is no fluff or repetition, making it highly efficient.

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 only 3 parameters and no nested objects or output schema, so complexity is low. The description covers purpose and a critical usage hint, but it omits details on the required 'message' parameter and the format of the 'conversation' string (which defaults to '[]' but could be a JSON array). Given the annotations and simplicity, it is adequate but leaves room for improvement. The agent would likely need to guess on message content.

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 mentions the 'conversation array' (corresponding to the 'conversation' parameter) but does not explain the required 'message' parameter or the optional 'context'. The description lacks critical guidance on what to put in the required field, leaving the agent to infer from the tool name. This is a significant gap given the schema provides no descriptions.

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's purpose: 'Report a bug, missing feature, or send feedback.' This is a specific verb+resource, and no sibling tools perform a similar function, so it clearly distinguishes itself. The name and description align perfectly.

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 a clear usage instruction: 'Include the conversation array with recent messages for reproduction.' This tells the agent how to use the tool effectively. However, it does not explicitly mention when to use it vs. alternatives or when not to use it, though sibling tools are unrelated, making differentiation less critical. The guidance is practical but not exhaustive.

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. The description adds useful context by specifying that it shows both platform and adapter versions, clarifying the exact scope of the read operation.

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?

A single, front-loaded sentence with no wasted words. It states the action and the object clearly and completely.

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 version tool with no output schema, the description is fully adequate. It tells the agent exactly what information will be returned without unnecessary detail.

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, which earns the baseline 4. The description correctly implies no inputs are needed, and there is nothing else to compensate for.

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 names a clear resource ('current MCP platform and adapter versions'). It distinguishes itself from siblings like toolkit_info by focusing specifically on version information.

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 use when the user needs version details, but it does not explicitly state when to use this tool versus alternatives. Given the simplicity of the tool, no exclusions are stated, but this still falls short of explicit 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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, but the description adds substantial context: no platform credentials needed, prepaid per-query billing, data is the same available to citizens, and the client is data controller under LGPD. This goes well beyond the annotations and clarifies cost, auth, and legal responsibility.

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 front-loaded with the core purpose and each sentence adds useful information: official source, hosting/credentials, pricing, data classification, and LGPD responsibility. There is no filler or redundant repetition of the tool name.

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 billing, auth, data classification, and legal context well. However, for a tool with three undocumented optional parameters and no output schema, it omits how the parameters should be used and what kind of result the agent should expect, leaving meaningful 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 roles of 'ie', 'cpf', or 'cnpj', whether they are alternatives, or whether at least one is required. The bare property names hint at Brazilian identifiers, but the description adds no real 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?

The description opens with 'SINTEGRA: PB, consulta em fonte oficial', using a specific verb ('consulta') and a specific resource (SINTEGRA PB official source). It further clarifies that it queries official Brazilian sources, which clearly distinguishes it from unrelated sibling tools like authenticate, connect, and 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?

The description provides clear operational context: the tool is hosted by the platform, requires no platform credentials, is paid per query with prepaid credit, and queries official non-confidential data. It does not explicitly state when not to use it or name alternatives, but the sibling tools are so unrelated that confusion is unlikely.

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 readOnly=true, idempotent=true, destructive=false, covering safety traits. The description adds value by detailing what the returned state includes (MCPs, connection status, accounts, catalog counts), which is beyond the annotations and helps set 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 that is front-loaded with the action ('Returns the current toolkit state') and then lists the key contents. No fluff or redundancy; every word adds 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 informational tool with no parameters and no output schema, the description fully specifies what the agent can expect. It enumerates the major components of the returned state, making the tool's functionality self-contained and clear.

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 factually, so schema coverage is trivially 100%. The description adds no param information because none exists; the baseline of 4 is appropriate because the description focuses on the output rather than parameters.

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 starts with 'Returns the current toolkit state' and enumerates specific items (installed MCPs, connection status, accounts, catalog tool counts). This clearly differentiates it from sibling tools like show_version, which likely reports only a version string.

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?

While the description does not explicitly mention when to use this tool versus alternatives, it clearly states the tool returns a comprehensive state overview. An agent can infer usage context (e.g., inspecting installed MCPs or connectivity) without ambiguity, though no exclusions are noted.

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