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by QuantConnect

read_live_algorithm

Retrieve live algorithm details by providing a project ID. Access real-time status, metrics, and configuration of your QuantConnect strategy's active deployment.

Instructions

Read details of a live algorithm.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNoError message.
deployIdNoUnique live algorithm deployment identifier (similar to a backtest id).
statusNoState of the live deployment.
cloneIdNoThe snapshot project Id for cloning the live development's source code.
launchedNoDatetime the algorithm was launched in UTC.
stoppedNoDatetime the algorithm was stopped in UTC, null if its still running.
brokerageNoBrokerage
securityTypesNoSecurity types detected in the algorithm.
datacenterNoName of the datacenter where the algorithm is physically located.
isPublicStreamingNoFlag to indicate if public streaming is enabled.
publicNoFlag to indicate if the algorithm is public.
filesNoFiles present in the project that contains the algorithm.
runtimeStatisticsNoRuntime banner/updating statistics in the title banner of the live algorithm GUI. It can be empty if the algorithm is not running.
chartsNoChart updates for the live algorithm since the last result packet.
projectNameNoName of the project the live algorithm is in.
successNoIndicate if the API request was successful.
errorsNoList of errors with the API call.
Behavior2/5

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

The description does not disclose behavioral traits beyond the basic read operation. Annotations are minimal (only a title) and do not include readOnlyHint or other safety cues. The tool is likely non-destructive, but the description fails to confirm this or mention any other behavioral aspects like authentication needs or rate limits.

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 at one sentence, which is generally positive. However, it is under-specified to the point of being unhelpful. Conciseness should not sacrifice completeness, and here the brevity results in missing essential details.

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

Completeness2/5

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

Given the tool's simplicity (one required parameter) and the presence of an output schema (reducing need for return value explanation), the description should provide context about what 'details' includes, error conditions, or prerequisites. It fails to do so, leaving the tool's behavior underdefined for an AI agent.

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?

The input schema has 0% description coverage, and the description adds no information about the parameters. The only parameter ('model') is an object containing 'projectId', but the description does not explain its role, format, or how to use it. This leaves the agent without critical context for correct invocation.

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

Purpose4/5

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

The description clearly states the action ('Read details') and the resource ('live algorithm'), matching the tool name. However, it does not differentiate this tool from sibling read tools like 'read_live_chart' or 'read_live_orders', which also read aspects of live algorithms. The purpose is specific enough for the agent to understand the general function but lacks contrast with alternatives.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus other read tools or alternatives. There is no mention of prerequisites, typical use cases, or exclusions. The agent receives no contextual cues to decide between this and similar tools.

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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