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 landing-ai · Agent Tool · ★ 2.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ade-cli safe to install? View the security audit →
ade-cli Agentic Document Extraction (ADE), from your terminal. Run to turn documents with tables, figures, and charts into grounded Markdown and elements, and to pull schema-shaped fields with page-and-box evidence. Both save to a local store at , so re-running an identical command consumes no credits. CLI documentation · Playground · Get an API key Install Each release ships self-contained binaries for macOS, Linux, and Windows (arm64 and x8664). No Python or needed. macOS / Linux Windows (PowerShell) Windows (CMD) To develop or install from source, see CONTRIBUTING.md. First run Log in once per machine, parse a document, then extract the fields you want from it. The parse summary prints the job it
| Stars | 2,418 |
| Forks | 255 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 74.4150244000431/100 |
| Open Issues | 11 |
| Last Updated | 2026-08-19 |
| Created | 2025-03-12 |
| Platforms | cli, python |
| Est. Tokens | ~14k |
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ade-cli is The official CLI for Agentic Document Extraction (ADE) by LandingAI — parse documents and extract schema-shaped data from your terminal. It is categorized as a Agent Tool with 2.4k GitHub stars.
ade-cli is primarily written in Python. It covers topics such as agentic-document-extraction, cli, document-extraction.
You can find installation instructions and usage details in the ade-cli GitHub repository at github.com/landing-ai/ade-cli. The project has 2.4k stars and 255 forks, indicating an active community.
ade-cli is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to ade-cli on Agent Skills Hub include ExtractThinker, pdf-reader-mcp, latex-document-skill. 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: