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QuantConnect

Official
by QuantConnect

check_syntax

Read-only

Validate code syntax for Python and C# files to detect errors before execution in QuantConnect's algorithmic trading platform.

Instructions

Check the syntax of a code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoState of the syntax check.
payloadNoCode completion suggestions.
versionNoVersion of the response.
payloadTypeNoType of the payload.
Behavior3/5

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

Annotations provide readOnlyHint=true, indicating this is a safe read operation. The description doesn't contradict this but adds minimal behavioral context beyond what annotations already cover. It doesn't describe output format, error handling, or performance characteristics that would be helpful for an agent.

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 at just 5 words, with no wasted language. It's front-loaded with the core purpose. However, this conciseness comes at the cost of completeness.

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?

Despite having an output schema (which reduces the need to describe return values), the description is inadequate for a tool with 1 complex parameter (a nested object with language and files). With 0% schema description coverage and no parameter guidance in the description, the agent lacks sufficient context to use this tool effectively.

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 parameters are undocumented in the schema. The description provides no information about parameters, not even mentioning that code and language inputs are required. This leaves the agent with no semantic understanding of what inputs to provide.

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 'Check the syntax of a code' clearly states the verb ('Check') and resource ('syntax of a code'), making the purpose understandable. However, it doesn't differentiate from potential siblings like 'complete_code' or 'enhance_error_message' that might involve code analysis, and the phrasing 'a code' is slightly awkward.

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. It doesn't mention prerequisites, timing, or how it differs from other code-related tools like 'complete_code' or 'check_initialization_errors' in the sibling list.

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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