QuantConnect MCP Server

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

Annotations indicate readOnlyHint=true, confirming this is a non-destructive read operation. The description adds minimal behavioral context beyond this—it doesn't mention performance characteristics, rate limits, or authentication needs. Since annotations cover the safety profile, the description meets a baseline but lacks enrichment about what the estimation entails or potential limitations.

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 extremely concise—a single, well-structured sentence that front-loads the core purpose without unnecessary details. Every word contributes directly to understanding the tool's function, making it efficient and easy to parse.

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 complexity (1 parameter with nested objects, 0% schema coverage) and the presence of an output schema, the description is insufficient. It doesn't clarify parameter semantics or behavioral nuances, relying too heavily on the output schema for return values. For a tool with undocumented parameters, more context is needed to guide effective use.

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 0% description coverage, meaning parameter details are entirely undocumented in the schema. The description only vaguely references 'specified parameters' without explaining what they are, their purposes, or how they affect the estimation. This fails to compensate for the schema gap, leaving parameters semantically unclear.

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: 'Estimate the execution time of an optimization with the specified parameters.' It provides a specific verb ('Estimate') and resource ('execution time of an optimization'), making the function unambiguous. However, it doesn't differentiate from sibling tools like 'create_optimization' or 'read_optimization', which would require explicit comparison.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing optimization setup), contrast with sibling tools (e.g., 'create_optimization' for actual execution), or specify scenarios where estimation is appropriate (e.g., planning or resource allocation). Usage is implied but not articulated.

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