QuantConnect MCP Server

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

Annotations only provide a title ('Read live insights'), so the description carries the burden of behavioral disclosure. It adds valuable context: the snapshot updates about every 10 minutes, which informs the agent about data freshness and potential delays. This goes beyond what annotations provide, though it could be more detailed (e.g., on permissions or error handling).

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 brief and front-loaded with the core purpose in the first sentence. The second sentence adds useful behavioral context without redundancy. However, it could be more structured by explicitly addressing parameters or usage scenarios.

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 (involves live algorithm insights with parameters) and the presence of an output schema (which handles return values), the description is partially complete. It covers the purpose and a key behavioral trait but lacks parameter explanations and usage guidelines, making it adequate but with clear gaps for effective tool selection.

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%, meaning parameters are undocumented in the schema. The description does not mention any parameters, failing to compensate for this gap. It should explain the 'model' parameter (which includes start, end, and projectId) to help the agent understand what inputs are needed and why.

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 the tool 'Read[s] out the insights of a live algorithm,' which clarifies the verb (read) and resource (insights of a live algorithm). However, it does not differentiate from sibling tools like 'read_backtest_insights' or 'read_live_logs,' leaving ambiguity about when to use this specific tool versus other read operations on live algorithms.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions snapshot updates every 10 minutes, but this is a behavioral trait rather than usage context. There is no mention of prerequisites, alternatives, or exclusions, leaving the agent to 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.