Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · AI
Q Kdb Code Review
AI-powered code review for Q/kdb+ — catch bugs in the most terse language in finance
skill openclawclawhub Free
AI-powered code review for Q/kdb+ — catch bugs in the most terse language in finance
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, config.example.toml, plugin.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- beee003
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
q-kdb-code-review
AI-powered code review for Q/kdb+ — catch bugs, performance issues, and security vulnerabilities in the most terse language in quantitative finance.
What it does
Reviews Q/kdb+ code with deep understanding of Q idioms, performance patterns, and common pitfalls. Built for quant developers, kdb+ DBAs, and trading infrastructure teams. Catches: Type errors in implicit casts (e.g., mixing longs and floats in comparisons) Rank errors from wrong argument counts in function calls Unescaped signals in protected evaluation Memory-inefficient queries (selecting all columns when only some are needed) Missing peach parallelism opportunities for embarrassingly parallel operations Unsafe eval/value usage on user-supplied strings (Q injection) Unlocked tables during concurrent inserts Missing `g# grouped attributes on high-cardinality join columns N-squared joins that should be aj (asof joins) or wj (window joins) Race conditions in timer callbacks (.z.ts) Unprotected IPC handlers (.z.pg, .z.ps) and exposed .z.pw Strictness modes: ModeWhat it checksstandardBugs, correctness, type errors, join semantics, null handlingstrictEverything in standard + performance (attributes, peach, vector ops) + stylesecurityEverything in standard + injection via string eval, unprotected IPC handlers, exposed .z.pw, port exposure Intelligent routing via Astrai: Complex algorithmic Q (custom signal generation, real-time CEP) routes to powerful models. Simple table operations (selects, inserts, schema definitions) route to cheaper, faster models. You get the best result at the lowest cost. BYOK (Bring Your Own Keys): Your provider API keys, your billing. Astrai routes to the best model among your configured providers.
Setup
Get a free API key at as-trai.com Set your API key: export ASTRAI_API_KEY="your_key_here" Optionally add provider keys for BYOK routing: export ANTHROPIC_API_KEY="sk-ant-..." export OPENAI_API_KEY="sk-..." Run /review-q on any .q file
Usage
/review-q Review current Q file /review-q --strict Strict mode: bugs + performance + style /review-q --focus security Security mode: eval injection, IPC, .z.pw /review-q --file tick.q Review a specific file
Example output
Reviewing tick.q (strict mode)... Model: claude-opus-4-6 via Astrai Found 3 issues: [CRITICAL] Line 12: Missing `s# attribute on time column `trade` table uses `aj` but `time` column lacks sorted attribute. Without `s#`, asof join scans linearly — O(n) instead of O(log n). Fix: trade: `trade upsert update `s#time from trade [WARNING] Line 34: Using `each` where vector operation suffices {x*y} each' (price;qty) can be replaced with price*qty Vector multiply is ~100x faster than each-both. [INFO] Line 45: Consider `peach` for independent symbol processing Processing each symbol sequentially. Since operations are independent, `peach` would utilize all cores. Fix: results: func peach syms Summary: 1 critical, 1 warning, 1 info. Focus on the missing sorted attribute — it will cause aj performance to degrade from microseconds to milliseconds at scale.
Environment Variables
VariableRequiredDescriptionASTRAI_API_KEYYesAPI key from as-trai.comANTHROPIC_API_KEYNoBYOK: Anthropic provider keyOPENAI_API_KEYNoBYOK: OpenAI provider keyGOOGLE_API_KEYNoBYOK: Google AI provider keyDEEPSEEK_API_KEYNoBYOK: DeepSeek provider keyMISTRAL_API_KEYNoBYOK: Mistral provider keyGROQ_API_KEYNoBYOK: Groq provider keyTOGETHER_API_KEYNoBYOK: Together AI provider keyFIREWORKS_API_KEYNoBYOK: Fireworks AI provider keyCOHERE_API_KEYNoBYOK: Cohere provider keyPERPLEXITY_API_KEYNoBYOK: Perplexity provider keyREVIEW_STRICTNESSNoDefault strictness: standard, strict, or security
External Endpoints
EndpointPurposeas-trai.com/v1/chat/completionsAstrai inference router — routes Q review requests to the optimal model
Security & Privacy
No code storage: Your Q code is sent to the selected AI provider for inference and is not stored by Astrai. BYOK: When you provide your own provider keys, requests go directly through Astrai's router to your provider account. Astrai does not store or log your provider keys beyond the request lifecycle. Transport: All communication uses HTTPS/TLS. No telemetry: The skill does not send analytics or telemetry data. Only the review request goes to Astrai. Local processing: File reading and result formatting happen entirely on your machine.
Why Q needs specialized review
Q is unlike any mainstream programming language: Extreme terseness: A single line of Q can express what takes 20 lines in Python. This density makes bugs nearly invisible during manual review. Implicit type coercion: Q silently coerces types in many operations. Comparing a long to a float, or joining on mismatched key types, can produce silently wrong results. 1000x performance gaps: The difference between idiomatic and naive Q is not 2x or 10x — it is often 1000x. Missing a sorted attribute on a time column turns an O(log n) asof join into O(n). Using each instead of vector operations adds interpreter overhead per element. Adverb complexity: Q's adverbs (/, \, ', /:, \:, ':) modify function behavior in powerful but subtle ways. +/ is reduce-add, +\ is scan-add, +' is each-both-add. Confusing these causes wrong results, not errors. Most AI models struggle: Without Q-specific prompting, general-purpose AI models treat Q code as line noise. This skill provides detailed system prompts that teach the model Q semantics, kdb+ internals, and finance-domain patterns.
Pricing
Uses Astrai's inference routing. Your costs depend on the models selected: PlanRateIncludesFree$01,000 requests/dayPro$49/mo50,000 requests/day, priority routingBusiness$199/moUnlimited requests, dedicated support With BYOK, you pay your provider directly at their rates. Astrai's routing is included in the plan price.
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts1 Files
- SKILL.md
- plugin.py
- config.example.toml