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Hft Quant Expert

Checked
kasyap1234·vlatest·data

This AI simulates a High-Frequency Trading (HFT) quantitative analyst, providing insights and strategies for algorithmic trading optimization.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add kasyap1234/delta-go --skill hft-quant-expert -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

kasyap1234

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Only contacts known or declared hosts: github.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    github.comsource host

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned kasyap1234/delta-go at 4b83866719.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
4b83866719
Manifest
.agent/skills/hft-quant-expert/SKILL.md
Scanned
2 files, 237 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill empowers AI agents to execute high-frequency trading (HFT) strategies with ultra-low latency by leveraging the delta-go framework. It enables rapid market data ingestion, order execution, and risk management tailored for nanosecond-level decision-making in financial markets.

When to use it

  • Building automated trading bots that require sub-millisecond response times.
  • Analyzing real-time market microstructure data for arbitrage opportunities.
  • Implementing complex quantitative strategies involving statistical arbitrage or market making.
  • Testing algorithmic trading logic against simulated live market feeds.

Key capabilities

  • Integration with the delta-go engine for high-performance Go-based execution.
  • Real-time processing of streaming financial market data.
  • Automated order placement and cancellation with minimal latency overhead.
  • Customizable risk parameters to prevent excessive exposure during volatile conditions.

Example prompts

  • "Deploy an HFT bot on the S&P 500 futures contract using current volatility metrics."
  • "Analyze the last 10 minutes of tick data for potential mean-reversion signals in EUR/USD."
  • "Configure risk limits to cap daily losses at 2% while maximizing throughput on a crypto exchange."

Tips & gotchas

Ensure your local environment has low-latency network connectivity and compatible Go runtime versions. This skill is not suitable for long-term investment strategies or markets requiring human discretion due to its purely algorithmic, speed-optimized nature.