Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Reviews Q/kdb+ code for type errors, performance antipatterns, and security vulnerabilities. Routes requests through Astrai's inference router, which selects models based on query complexity. Supports three strictness modes: standard, strict, and security.
General-purpose AI models treat Q's terse syntax as noise and miss finance-domain patterns like attribute gaps, adverb misuse, and asof join semantics, which this skill addresses through Q-specific prompting and kdb+ internals knowledge.
When to use it
- Catching implicit type coercion bugs before production deployment
- Finding missing sorted attributes on asof join time columns
- Auditing .z.pg and .z.pw handlers for injection vulnerabilities
- Replacing each loops with vector operations in time-series calculations
- Detecting race conditions in .z.ts timer callbacks
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Review tick.q in strict mode
- 1Read tick.q from disk
- 2Construct review prompt with strict mode parameters and Q semantics context
- 3Route request to Astrai inference router for optimal model selection
- 4Parse model response and categorize findings by severity
- 5Format output with line numbers, explanations, and suggested fixes
Issues labeled CRITICAL, WARNING, or INFO, each with the affected line, explanation, and a concrete fix, followed by a count summary
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.