arscontexta: Claude Code plugin that generates individualized knowledge systems from conversation

by agenticnotetaking · Claude Skill · ★ 3.5k

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

Featured in: Knowledge Base & RAG · Obsidian for Claude Code & AI Agents

How to install arscontexta

/plugin marketplace add agenticnotetaking/arscontexta
/plugin install arscontexta@agenticnotetaking

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

Security audit verdict: SAFE · quality 74/100

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.

claude-codeclaude-code-pluginknowledge-baseknowledge-managementmarkdownsecond-brain

Quick Facts

Stars3,487
Forks226
LanguageShell
CategoryClaude Skill
LicenseMIT
Quality Score74/100
Open Issues35
Last Updated2026-02-24
Created2026-02-15
Platformsclaude-code, cli
Est. Tokens~60k

About arscontexta

Ars Contexta A second brain for your agent. A Claude Code plugin that generates complete knowledge systems from conversation. You describe how you think and work. The engine derives a cognitive architecture -- folder structure, context files, processing pipeline, hooks, navigation maps, and note templates -- tailored to your domain and backed by 249 research claims. No templates.

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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:

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