QuantConnect MCP Server

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

Annotations only provide a title ('Read live algorithm'), which doesn't cover behavioral traits. The description adds that it reads 'details' but doesn't disclose what those details include, whether it requires specific permissions, rate limits, or error conditions. It doesn't contradict annotations, but provides minimal behavioral context beyond the basic operation.

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 no wasted words. It's front-loaded with the core action and resource, making it immediately clear what the tool does. Every word earns its place, though more content could enhance utility without sacrificing conciseness.

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 has an output schema (which should define return values), the description doesn't need to explain outputs. However, with no annotations covering behavioral traits and 0% schema description coverage for the single parameter, the description is minimal. It states the basic purpose but lacks context on usage, parameter meaning, or detailed behavior, making it adequate but incomplete for optimal agent 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?

Schema description coverage is 0%, meaning the single parameter 'projectId' has no description in the schema. The tool description doesn't mention parameters at all, failing to compensate for the schema gap. However, with only one parameter and a straightforward naming convention ('projectId'), the baseline is 3 as the agent can infer meaning from context, though explicit guidance would improve this.

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 'Read details of a live algorithm' clearly states the verb ('read') and resource ('live algorithm'), but it's vague about what 'details' specifically include. It distinguishes from obvious siblings like 'create_live_algorithm' or 'stop_live_algorithm', but doesn't differentiate from similar read operations like 'read_live_chart' or 'read_live_insights' that might provide more specific details.

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. With siblings like 'list_live_algorithms' (for listing) and other 'read_live_*' tools (for specific aspects), there's no indication of when this general 'details' tool is appropriate versus more specialized ones. No prerequisites or exclusions are mentioned.

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