datachain — security grade SAFE, quality 62/100

Security audit verdict: SAFE · quality 62/100

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 datachain-ai · Codex Skill · ★ 2.8k

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

🔒 Is datachain safe to install? View the security audit →

About datachain

DataChain - Data Context Layer for Object Storage DataChain is a data context layer for object storage. It gives AI agents and pipelines a typed, versioned, queryable view of your files - what exists, what schema it has, what's already been computed - without copying data or loading it into memory. Metadata queries across 100M+ files execute in milliseconds against a backend database Pipelines checkpoint - re-running the same script resumes compute without duplicating expensive LLM-call or ML scoring makes re-runs incremental — only new or changed files are processed Every registers a named, versioned dataset with schema and lineage A generated knowledge base () reflects the operational layer as markdown for agents to read before writing code Works with S3, GCS, Azure, and local filesystems. bash pip

ai-agentsclaude-codecodexdata-context-layerdata-processingharness-engineeringknowledge-basemlopsmultimodalpydantic

Quick Facts

Stars2,820
Forks157
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score62.3698151356239/100
Open Issues101
Last Updated2026-09-18
Created2024-06-25
Platformsclaude-code, codex, python
Est. Tokens~16k

Compatible Skills

These tools work well together with datachain for enhanced workflows:

  • nexent — semantic(0.23)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)
  • dlt — semantic(0.47)+complementary+same_lang+similar_pop+shared_platform (62%)
  • hive — semantic(0.19)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • DataDesigner — semantic(0.44)+complementary+same_lang+similar_pop+shared_platform (60%)
  • datagouv-mcp — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (59%)

datachain alternative? Top 6 similar tools

Looking for a datachain alternative? If you're comparing datachain with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • OpenContext by 0xranx · ⭐ 729

    A personal context store for AI agents and assistants—reuse your existing coding agent CLI (Codex/Claude/OpenC

  • cursor-talk-to-figma-mcp by grab · ⭐ 7.0k

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  • pilot-shell by maxritter · ⭐ 2.1k

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  • claude-codex-settings by fcakyon · ⭐ 1.1k

    Battle-tested Claude Code, OpenAI Codex, Cursor configs, plugins, hooks and agents with Kimi, MiniMax and GLM

  • pydantic-deepagents by vstorm-co · ⭐ 1.0k

    Open-source, self-hosted Claude Code - a terminal AI assistant and the Python framework behind it. Tool-callin

  • codexia by milisp · ⭐ 915

    Lightweight Agent Workstation for Codex CLI + Claude Code — with task scheduler, git worktree & remote control

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Frequently Asked Questions

What is datachain?

datachain is The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure. It is categorized as a Codex Skill with 2.8k GitHub stars.

What programming language is datachain written in?

datachain is primarily written in Python. It covers topics such as ai-agents, claude-code, codex.

How do I install or use datachain?

You can find installation instructions and usage details in the datachain GitHub repository at github.com/datachain-ai/datachain. The project has 2.8k stars and 157 forks, indicating an active community.

What license does datachain use?

datachain is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to datachain?

The top alternatives to datachain on Agent Skills Hub include OpenContext, cursor-talk-to-figma-mcp, pilot-shell. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

View on GitHub → Browse Codex Skill tools