by saidsurucu · Agent Tool · ★ 163
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yargi-cli CLI tool for Turkish legal databases. Designed for AI agents and programmatic use. Origin: This project is the CLI counterpart of yargi-mcp, a Python-based MCP server that provides access to Turkish legal databases. While yargi-mcp serves LLM applications via the Model Context Protocol, yargi-cli provides the same capabilities as a standalone command-line tool — JSON output, pipe-friendly, zero authentication. 🌍 Türkçe README Why? AI agents (LLM tool-use, autonomous coding agents, RAG pipelines) need a simple, predictable interface to query Turkish court decisions. yargi-cli provides: JSON-only output — every command writes structured JSON to stdout Pipe-friendly — chain with , , or any Unix tool Rich — parameter descriptions, search operators, output schemas, and examples are embedded in help text so agents can self-discover the API No auth, no config — just install and call Supported Databases Currently implements the Bedesten module (bedesten.adalet.gov.tr): Extraordinary Appeals (Kanun Yararına Bozma
| Stars | 163 |
| Forks | 22 |
| Language | TypeScript |
| Category | Agent Tool |
| Quality Score | 71.1275285328609/100 |
| Last Updated | 2026-05-08 |
| Created | 2026-02-23 |
| Platforms | cli, node |
| Est. Tokens | ~5k |
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yargi-cli is CLI tool for Turkish legal databases. Designed for AI agents and programmatic use. TypeScript, JSON output, pipe-friendly.. It is categorized as a Agent Tool with 163 GitHub stars.
yargi-cli is primarily written in TypeScript.
You can find installation instructions and usage details in the yargi-cli GitHub repository at github.com/saidsurucu/yargi-cli. The project has 163 stars and 22 forks, indicating an active community.
The top alternatives to yargi-cli 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.
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