SINTEGRA: RJ

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

While annotations already indicate idempotence and non-destructiveness, the description adds valuable behavioral details: it distinguishes a permanent (non-expiring) connection via config versus a session-only login via pasted token, and notes that calling with no args returns a link. This goes beyond the sparse 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, front-loaded with the purpose, and structured with clear alternatives ('Best' vs 'Or'). Every sentence adds value, avoiding fluff.

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 simplicity of the tool (one optional param, no output schema), the description covers the essential use cases: obtaining a link for browser login, pasting a token for session access, and the recommended permanent config method. It is complete for its scope.

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 only has an optional 'token' field with no description. The tool description compensates by explaining that the token is a JWT to be used for session-only login, and that omitting it returns the login link. This adds meaning beyond the raw 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 states the tool's purpose: to authenticate to MCP.AI for IDE agents. It specifies the action (log in in the browser, copy the access token) and differentiates it from sibling tools like 'connect' by focusing on the authentication flow.

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 recommends the permanent config method (adding a header to the server config) and explains the session-only alternative via pasting a token. It also tells when to call with no args (to get the link) versus with a token.

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. The description adds valuable behavioral details beyond these: it explains conditional return results (authenticated:true with empty pending[] when all connected, versus connect_url and per-install URLs when credentials are missing), giving the agent a clearer picture of runtime 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, front-loaded with the primary purpose ('Returns connection status and URLs') then elaborating on two key conditional outcomes. Every sentence earns its place; 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?

The description covers the all-connected case and the missing-credentials case, but does not explicitly address partial connectivity or other edge states. Since there is no output schema, this leaves some room for ambiguity, though the tool is simple enough that the provided detail is mostly sufficient.

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 behavior; there are no parameter semantics to document. Schema coverage is trivially 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 states 'Returns connection status and URLs' which is a specific verb and resource, and it clearly explains two distinct return states. This distinguishes it from sibling tools like authenticate, which would perform a connection action rather than report status.

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 this tool is for checking connection status, not performing authentication, but it does not explicitly say 'use this when' or name alternatives. It provides clear functional context without exclusions or explicit comparison to similar tools like authenticate.

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 sparse annotations (readOnlyHint:false, openWorldHint:true), the description discloses critical behaviors: 'invoke works even when the MCP is NOT installed', one-off execution, return of connect/checkout links, permission requirements ('Writes require workspace owner/admin'), and the prompt library distinction. This adds substantial non-obvious 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 a single dense paragraph. While information-rich and somewhat front-loaded with the core value proposition, it would benefit from bullets or sections given its length. The lack of formatting undermines scannability for an agent.

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 complexity (23 params, multiple action types, billing/auth edge cases, prompt library), the description covers every major flow and provides comprehensive operational guidance, including permissions, auth, billing, and fallback behaviors (connect/checkout links). No missing critical context is apparent.

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 burden. It explains the semantics of key actions (search, describe, invoke, install, list_tools, subscribe/cancel, report_bug, request_mcp, search_prompts, get_prompt, publish_prompt) and mentions auth/billing parameters indirectly. However, it does not systematically tie every parameter (e.g., limit, query, tier_slug, conversation) to its purpose, leaving some guesswork.

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 a precise statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It further clarifies scope with concrete examples of capability requests and the core flow (search → describe → invoke), clearly distinguishing it as the marketplace hub among siblings.

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?

Explicit when-to-use guidance is abundant: 'Use install only to make an MCP PERMANENT', 'prefer invoke for a single/occasional use', and 'list_tools lists what is callable right now.' It also explains when report_bug, request_mcp, and subscribe/cancel apply, effectively covering alternatives and exclusions.

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 non-read-only, idempotent, non-destructive behavior. The description adds no further behavioral context—no mention of side effects, output, auth requirements, or any limits. It only restates the purpose and gives a parameter hint, which is insufficient for a tool that presumably sends data somewhere.

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 conveys purpose and a key usage instruction with no filler. It is front-loaded and 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?

For a simple tool with one required parameter and annotations, the description covers basic selection and invocation. However, it lacks important context such as when to use it vs. other reporting mechanisms, what happens after submission, and clarification of the remaining parameters. It is minimally viable but not comprehensive.

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 partially explains the 'conversation' parameter ('array with recent messages for reproduction'), but the required 'message' parameter is not explicitly described, and 'context' is entirely undocumented. The description is too vague to fully guide correct invocation.

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: 'Report a bug, missing feature, or send feedback.' This is a specific verb plus resource, and it distinguishes the tool from its unrelated siblings (authenticate, connect, etc.). It leaves no ambiguity about what the tool does.

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 instruction to 'Include the conversation array with recent messages for reproduction' gives a concrete usage hint, and the tool's purpose is evident given unrelated siblings. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites.

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 safe read-only nature is clear. The description adds the specific output content (platform and adapter versions) but does not disclose any further behavioral details such as return format or error cases. 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 single, focused sentence with no filler. Every word contributes to the meaning, and it is front-loaded with the action verb.

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, the description is fully adequate. It explains what information is returned (MCP platform and adapter versions) without needing to document parameters or complex behaviors. The lack of an output schema is acceptable for such a simple operation.

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 description needs no parameter explanations. Baseline 4 applies, and the description aligns with the empty input 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 uses a specific verb ('Show') and clearly identifies the resource ('current MCP platform and adapter versions'). It is distinct from siblings like authenticate or report_bug, making the tool's 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 usage when version information is needed, but it does not explicitly state when to use this tool over alternatives or mention any exclusions. No sibling comparison is provided, so the guidance remains implicit 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, destructiveHint=false, and the description adds substantial behavioral context: it's hosted on the platform, doesn't require platform credentials, requires prepaid credits per query, and queries official non-confidential data. It also clarifies LGPD compliance and that the client is the data controller. This goes beyond the annotations by explaining the authorization/billing model and legal context, while not contradicting 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, information-dense paragraph in Portuguese that covers purpose, hosting, credentials, billing, data source, legal compliance, and data controller responsibilities. Every sentence earns its place, no fluff, and it's front-loaded with the tool's identity. While it's longer than the examples, it packs necessary compliance and operational info efficiently.

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 this is a read-only query tool with no output schema and only 3 optional params, the description fully satisfies completeness. It explains what data is queried, the legal basis, payment model, and who owns compliance responsibility—critical for a tool handling Brazilian personal data. The lack of output schema is fine because the description focuses on the query purpose; return value is inherently the SINTEGRA consultation result. For the tool's complexity, nothing is missing.

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 parameter names (ie, cpf, cnpj) with no descriptions or types beyond string. The description doesn't detail each parameter, but schema coverage is 0%, so the description was expected to compensate. The description's strength lies in context (SINTEGRA RJ, official source, LGPD) rather than parameter-level detail. However, given the parameters are self-explanatory Brazilian taxpayer IDs (CPF, CNPJ, IE) and the tool name indicates SINTEGRA consult, the semantics are partially implied. The description could have provided more explicit parameter guidance, so a 4 is fair given the strong contextual compensation.

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 consulting SINTEGRA RJ in an official source, specifying it queries information from official Brazilian sources. It distinguishes itself by noting it's hosted on the platform, requires no platform credentials, and is paid per query with prepaid credits, which differentiates it from sibling tools. However, it doesn't explicitly name a sibling alternative, so it doesn't fully distinguish from siblings like authenticate or marketplace, but the verb 'consultar' plus 'fonte oficial' provides specific action and resource.

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 context on when to use the tool: for consulting SINTEGRA RJ official data via the platform, with no need for platform credentials. It mentions it's the same data available to citizens and addresses LGPD compliance, implying appropriate use cases. It doesn't explicitly state when not to use this tool versus alternatives, nor name alternatives, but the context is clear enough for an agent to decide.

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 safe. The description adds the scope of the information returned, which is useful. However, it doesn't mention if the call is expensive or if it requires prior auth, but given annotations cover safety, this is adequate.

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 efficiently summarizes the tool's output. No fluff, front-loaded with 'Returns the current toolkit state', and 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?

The tool is simple with no parameters and thorough annotations. The description fully explains what the tool returns without needing to over-specify. However, it doesn't mention the output structure or format, but since there's no output schema and the outputs are self-explanatory ('installed MCPs', 'connection status'), this is sufficient.

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, and the schema correctly reflects that. The description explains what the output contains, which is the primary semantics for a tool with no inputs. Since the tool takes no params, the baseline is 4, and the description fully compensates.

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 what the tool does: returns the current toolkit state, listing installed MCPs, connection status, connected accounts, and catalog tool counts. This is specific and distinguishes it from siblings like 'marketplace' which likely manages the marketplace, and 'authenticate' which handles auth.

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 this is a status/info tool for when you need to know what's installed or connected, but it does not explicitly state when to use it vs alternatives like 'marketplace' or 'show_version'. Since there are siblings with overlapping themes, more explicit guidance would be helpful.

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