No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by trading212-labs · Agent Tool · ★ 114
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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Trading 212 API Agent Skills An AgentSkills plugin that wraps the Trading 212 API and exposes its capabilities in a tool-friendly format for AI assistants (e.g. OpenClaw, Claude Code, and others). The plugin provides skills that teach AI agents how to work with the API: retrieving portfolio and transaction history, placing and managing orders, querying instruments, and related operations—with consistent, schema-based inputs and outputs, authentication and error mapping, and rate-limit handling. Features Portfolio Management - View account summary, cash balance, and investment metrics Order Placement - Place market, limit, stop, and stop-limit orders Position Monitoring - Track open positions with P&L calculatio
| Stars | 114 |
| Forks | 8 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 74.4820740506466/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-08 |
| Created | 2026-02-03 |
| Platforms | node |
| Est. Tokens | ~5k |
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agent-skills is ✨ Supercharge your AI agent with the power of the Trading 212 API. It is categorized as a Agent Tool with 114 GitHub stars.
agent-skills is primarily written in TypeScript. It covers topics such as trading212.
You can find installation instructions and usage details in the agent-skills GitHub repository at github.com/trading212-labs/agent-skills. The project has 114 stars and 8 forks, indicating an active community.
agent-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-skills on Agent Skills Hub include claude-plugins, tutor-skills, repren. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: