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i-dream-of-ai

QuantConnect MCP Server

check_syntax

Read-only

Validate code syntax for algorithmic trading strategies in C# or Python to identify errors before execution.

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 adds minimal behavioral context beyond this - it implies analysis without modification but doesn't describe what the check entails (e.g., whether it returns errors, warnings, success status). No contradiction with annotations exists.

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 6 words with no wasted language. It's front-loaded with the core purpose. However, this conciseness comes at the cost of completeness rather than being optimally informative.

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?

For a tool with 0% schema description coverage, no output schema details provided in context, and annotations only covering read-only status, the description is inadequate. It doesn't explain what the tool returns, how to interpret results, or provide necessary parameter context. The existence of an output schema doesn't compensate for the description's minimalism.

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

Parameters2/5

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

With 0% schema description coverage for the single parameter 'model', the description provides no parameter information. It doesn't explain that 'model' requires language specification and file content, nor does it clarify the structure expected. The description fails to compensate for the schema's lack of parameter descriptions.

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

Purpose3/5

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

The description 'Check the syntax of a code' states the basic purpose (verb+resource) but is vague about scope and lacks specificity. It doesn't distinguish this tool from potential syntax-checking siblings (though none are explicitly listed among siblings) and uses generic terms like 'a code' rather than specifying it analyzes programming language syntax.

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 alternatives. The description doesn't mention prerequisites, appropriate contexts, or exclusions. While there are no obvious syntax-checking siblings, the tool exists among many code-related tools (e.g., complete_code, enhance_error_message) without differentiation.

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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