QuantConnect MCP Server

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

Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description adds no behavioral traits beyond this—it doesn't mention pagination, rate limits, authentication needs, or what 'list all' entails (e.g., if it returns summaries or full details). With annotations covering safety, the description adds minimal value, scoring baseline for adequate but unenriched 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, efficient sentence with zero waste: 'List all the optimizations for a project.' It's front-loaded with the core action and resource, making it easy to parse quickly. No extraneous words or redundant information are present.

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 parameter, read-only per annotations, and an output schema exists), the description is minimally complete. It states the purpose but lacks details on usage, behavioral nuances, or parameter specifics. With annotations and output schema handling safety and returns, the description is adequate but leaves gaps in guidance and semantics.

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%, but the description implies a 'project' parameter without detailing it. The schema defines one parameter (projectId), but neither the schema nor description explains its format or constraints beyond the example. With low coverage, the description partially compensates by hinting at the parameter's role, but it's insufficient for full clarity, meeting the baseline for minimal viability.

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 'List all the optimizations for a project' clearly states the verb ('List') and resource ('optimizations'), but it's vague about scope and doesn't differentiate from siblings like 'read_optimization' (which reads a single optimization) or 'list_backtests' (which lists a different resource). It specifies 'for a project' which provides some context but lacks specificity about what 'optimizations' entails.

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 sibling tools like 'read_optimization' (for single optimization details) or 'create_optimization' (for creating new ones), nor does it specify prerequisites, exclusions, or typical use cases. The agent must infer usage from the tool name alone.

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