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QuantConnect

QuantConnect

Official
by QuantConnect

list_backtests

Read-only

Retrieve all backtests for a QuantConnect project to review historical strategy performance and analyze trading algorithm results.

Instructions

List all the backtests for the project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of backtest summaries retrieved in the response.
errorsNoList of errors with the API call.
successNoIndicate if the API request was successful.
backtestsNoCollection of backtest summaries for a project.
Behavior3/5

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

The annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds minimal behavioral context beyond this - it specifies 'all the backtests' which implies comprehensive listing, but doesn't mention pagination, sorting, filtering capabilities, or what format the output takes. With annotations covering the safety profile, this earns a baseline score.

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

Conciseness5/5

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

The description is extremely concise - a single sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration. It's appropriately sized for a simple listing operation and front-loads the essential information.

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

Completeness3/5

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

Given that there's an output schema (which handles return values), annotations provide readOnlyHint, and the tool has only one parameter, the description is minimally adequate. However, it doesn't address when to use this versus other backtest-related tools, and provides no parameter guidance despite 0% schema description coverage, leaving significant gaps in contextual understanding.

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

Parameters3/5

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

Schema description coverage is 0%, but the description provides no parameter information whatsoever. The schema shows there's a required 'model' parameter containing projectId and includeStatistics, but the description doesn't mention these at all. Since schema coverage is 0%, the description should compensate but fails to do so, resulting in the minimum viable score.

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 ('List all the backtests') and the target resource ('for the project'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential siblings like 'read_backtest' or 'search_quantconnect', which might also retrieve backtest information in different ways.

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?

The description provides no guidance on when to use this tool versus alternatives. There are multiple sibling tools that interact with backtests (create_backtest, read_backtest, delete_backtest, update_backtest), but the description doesn't indicate this is specifically for listing all backtests versus reading a specific one or using search functionality.

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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