claude-trading-skills: 67 trading, DeFi, and quantitative finance Agent Skills

by agiprolabs · Codex Skill · ★ 338

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install claude-trading-skills

/plugin marketplace add agiprolabs/claude-trading-skills
/plugin install trading-skills@agiprolabs-claude-trading-skills

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars338
Forks67
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score63/100
Open Issues3
Last Updated2026-09-03
Created2026-03-11
Platformsclaude-code, cli, codex, gemini, python
Est. Tokens~19k

About claude-trading-skills

Claude Trading Skills A comprehensive collection of 67 ready-to-use trading, DeFi, and quantitative finance Agent Skills. Works with Claude Code, Cursor, Codex, Gemini CLI, and 30+ other tools. Transform your AI agent into a trading analyst capable of executing complex multi-step workflows across market data analysis, on-chain research, backtesting, risk management, tax compliance, and more.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools