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i-dream-of-ai

QuantConnect MCP Server

create_live_algorithm

Deploy a compiled trading algorithm to live markets by configuring brokerage connections and data providers for real-time execution.

Instructions

Create a live algorithm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
liveNoSummary of the algorithm created.
errorsNoList of errors with the API call.
sourceNoSource of the API call.
successNoIndicate if the API request was successful.
deployIdNoId of the live deployment.
projectIdNoId of the project deployed.
versionIdNoId of the LEAN version deployed.
responseCodeNoResponse code of the request.
Behavior2/5

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

Annotations provide destructiveHint=false, but the description adds no behavioral context beyond the basic 'create' action. For a tool that likely deploys trading algorithms with real financial implications, the description should mention authentication requirements, rate limits, what 'live' means operationally, or any side effects. With minimal annotations, the description carries most of the burden and fails to provide necessary behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise - just three words. While technically efficient, this represents under-specification rather than optimal conciseness. For such a complex tool with significant financial implications, this brevity is inadequate. However, it is front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's high complexity (financial algorithm deployment), rich input schema with 0% description coverage, no output schema information provided in context signals, and minimal annotations, the description is completely inadequate. It fails to explain what the tool actually does, what inputs are required, what the output represents, or any operational considerations for live trading algorithms.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the complex CreateLiveAlgorithmRequest structure (with 5 required properties and extensive nested brokerage/data provider configurations) is completely undocumented in the schema. The description provides zero parameter information - it doesn't mention any of the required inputs like projectId, compileId, nodeId, or brokerage settings. This leaves the agent with no semantic understanding of what parameters are needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create a live algorithm' is a tautology that restates the tool name without adding specificity. It mentions the verb 'create' and resource 'live algorithm' but provides no details about what a live algorithm entails, what it does, or how it differs from other creation tools like create_backtest or create_optimization.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides absolutely no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like needing a compiled project), when this would be appropriate versus creating a backtest, or any contextual constraints. The agent receives zero usage direction.

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

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