SINTEGRA: MT

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

Annotations are minimal (no readOnly, not destructive), so description carries the burden. It explains the tool's behavior in detail—initiating a login flow, accepting a token, returning a link, and supporting permanent vs session-only auth—adding significant context 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?

Concise but information-dense, covering purpose, two usage modes, and invocation details in two sentences. Well-structured with no filler; each clause 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?

For an authentication tool with no output schema, the description provides sufficient context: what to expect (link or token acceptance), how to use each method, and the overall workflow. It addresses all practical aspects for an IDE agent.

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 has no parameter descriptions (0% coverage), but the description fully explains the 'token' parameter (a JWT) and the behavior of calling without it (returns link). This entirely compensates for the missing schema docs.

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: authenticating to MCP.AI for IDE agents. It specifies the exact flow (browser login, copy token) and distinguishes it from siblings like 'connect' by focusing on authentication.

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 explicit usage instructions: two methods (permanent via config header, or session via token parameter), and distinguishes when to use each. Also explains how to call with no args to get the link, leaving no ambiguity about invocation.

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 read-only, idempotent, and non-destructive behavior. The description adds useful conditional details about authenticated:true with empty pending[] versus connect URLs when credentials are missing, going beyond the structured 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?

Two concise sentences that front-load the primary purpose and then provide state-dependent details. No filler or redundant 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 zero-parameter status tool with strong annotations, the description covers the key behaviors and return states. It could be slightly more exhaustive about the exact response shape, but it is sufficient for selecting and invoking 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 tool has zero parameters, so there is no parameter information to provide. The baseline of 4 applies because the description does not need to compensate for any undocumented inputs.

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 connection status and URLs, using a specific verb and resource. It also distinguishes itself from siblings like authenticate by focusing on status/URL output rather than 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 gives clear context for when this tool is useful—checking connection status—and describes behavior in two relevant states. It does not explicitly name alternatives or exclusions, but the conditional logic implies when it should be used.

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?

Despite annotations providing only readOnlyHint/openWorldHint/idempotentHint/destructiveHint flags, the description discloses key side effects: invoke runs even uninstalled MCPs without bloating the tool list, returns connect or checkout links when needed, and writes require workspace owner/admin. This is rich behavioral context beyond what annotations 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 a single dense paragraph that front-loads its purpose but mixes MCP discovery, invocation, installation, permissions, and the prompt library without clear section breaks. Every sentence carries value, but the lack of structure makes it harder to scan and parse 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?

The description covers the core flows, permissions, and edge cases (auth/payment), and even details the prompt library. However, it omits the 'resume' action entirely and does not describe what each action returns or the meaning of several parameters. For a 23-param, 14-action tool, it is strong but not fully complete.

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 description explains the action parameter thoroughly (search, describe, invoke, install, etc.) and gives meaning to mcp_id/tool_id via the describe flow. However, with 23 parameters and 0% schema coverage, many parameters remain unexplained (e.g., limit, immediate, arguments, conversation, prompt_vars, resume). The partial coverage is helpful but does not fully compensate for the schema void.

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 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them,' immediately establishing a specific verb and resource. It clearly distinguishes itself from siblings like toolkit_info and sintegra_mt_consultar by being the meta-level catalog and execution engine, and it details the search → describe → invoke 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?

Provides explicit when-to-use guidance: 'prefer invoke for a single/occasional use' vs 'Use install only to make an MCP PERMANENT', 'list_tools lists what is callable right now', and 'report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits.' This gives clear alternatives and decision criteria.

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 goes slightly beyond the annotations by mentioning the inclusion of conversation data, implying that data is sent. However, it does not disclose what happens after reporting (e.g., ticket creation, storage, or transmission details), so transparency is limited.

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 primary purpose, followed by a brief usage note. It avoids unnecessary detail and is easy to scan.

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?

While the tool is simple, the description does not fully explain the expected content of message or context, and there is no output schema or mention of return values. This leaves the agent with incomplete information for proper 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?

Of the three parameters (message, context, conversation), the description only clarifies the role of conversation (for reproduction). It does not explain what message or context should contain, leaving significant gaps in parameter understanding given the low 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 the tool's purpose: to report a bug, missing feature, or send feedback. This is specific and distinct from the sibling tools (authenticate, connect, etc.), which serve different functions.

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 what the tool is for and includes a specific usage instruction to include the conversation array for reproduction. It does not explicitly mention alternatives, but the purpose is unambiguous given the sibling set.

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 declare readOnlyHint=true and destructiveHint=false, already signaling a safe operation. The description adds value by specifying exactly what versions are returned (MCP platform and adapter), which is useful. It could mention output format or failure modes, but it's adequate for this simple tool.

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?

One sentence, zero waste. Every word contributes to understanding the tool's purpose. Perfectly sized for what it is.

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 0-parameter tool with clear annotations (readonly, non-destructive), the description is complete. There's no output schema to worry about, no parameters to document, and the sibling tools are all distinct. 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?

There are 0 parameters and schema description coverage is at 100%, so the baseline is 4 as per the rubric. The description doesn't need to explain parameters that don't exist, and the 0-param nature is self-evident.

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 shows MCP platform and adapter versions, with a specific verb ('show') and resource ('MCP platform and adapter versions'). It doesn't explicitly distinguish from siblings, but given the sibling tools perform entirely different functions, the purpose 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?

The description implies when to use it (when you need version info). While it doesn't explicitly state when-not-to-use or name alternatives, the sibling tools (authenticate, connect, marketplace, etc.) are clearly distinct in function. The description provides sufficient context for basic usage.

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. The description adds valuable context beyond annotations: payment model, lack of platform credentials, data not being confidential, and LGPD-related responsibilities. This gives the agent a clear picture of the tool's behavior and constraints.

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 well-structured, with four short sentences each adding meaningful information: what it does, how access works, what data is returned, and legal responsibility. No filler 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?

While the description covers purpose, access, and legal context well, it omits critical operational details: parameter semantics, required inputs, constraints on combinations (e.g., IE vs CPF vs CNPJ), and expected output. Without an output schema or parameter documentation, the agent is left guessing how 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?

Schema has three parameters (ie, cpf, cnpj) with 0% description coverage, and the description does not mention them at all. It does not explain which identifier to use, whether at least one is required, or how they map to the query. With no parameter guidance from either schema or description, the agent cannot reliably select and fill 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 clearly states the tool performs a query ('consulta') against SINTEGRA MT, an official Brazilian source, and specifies it returns information from official sources. It is distinct from the siblings, which are platform-level tools like authenticate and connect.

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 clear context for use: it is a hosted, pay-per-query service with prepaid credit, requires no platform credentials, and is for querying official non-confidential data. It does not explicitly name alternatives or exclusions, but the context is sufficient given the generic sibling list.

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, destructive=false, and idempotent=true, so the safety profile is covered. The description adds meaningful context about the specific data returned (MCPs, statuses, accounts, catalog counts), which goes beyond annotations and helps set expectations. No contradictions.

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 states the action and enumerates the returned items. Every word adds value, with no fluff or repetition.

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, the description fully specifies what the tool returns, covering the key dimensions of toolkit state. For a simple read-only informational tool, this is complete and 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 schema fully covers them (trivially). According to the rubric, 0 params baseline is 4. The description doesn't need to add parameter information, and it doesn't.

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: returning the toolkit state with specific items (installed MCPs, connection status, accounts, and catalog tool counts). It distinguishes itself from sibling tools like show_version (version info) and authenticate/connect (actions) by focusing on the overall state snapshot.

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 implicitly conveys when to use it: when you need an overview of the current toolkit installation and connectivity. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an informational tool, and it doesn't mislead.

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