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 tommy0103 · Codex Skill · ★ 512
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is obelisk safe to install? View the security audit →
Past Claude Code, Codex, and Kimi Code sessions -- queryable by your agent, browsable by you. Two sides of the same index Obelisk has two sides that share one SQLite index: Agent side — the CLI owns the local runtime, while a separate agent skill teaches coding agents how to search and query their session history. The agent writes JS queries, runs them locally, and answers in plain language. App side — an Electron desktop app for humans to browse sessions, manage memories, view usage stats, and see weekly recap cards. Both read from the same database. The indexer reads Claude Code transcripts from , Codex transcripts from , and Kimi Code sessions from (or ). Multi-provider support Obelisk indexes every provider into the same SQLit
| Stars | 512 |
| Forks | 36 |
| Language | JavaScript |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 65.4046141482901/100 |
| Open Issues | 54 |
| Last Updated | 2026-09-19 |
| Created | 2026-05-29 |
| Platforms | claude-code, cli, codex, node |
| Est. Tokens | ~16k |
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obelisk is Every past session, subagent, and workflow -- queryable by your agent, browsable by you. It is categorized as a Codex Skill with 512 GitHub stars.
obelisk is primarily written in JavaScript. It covers topics such as agent, agent-sessions, ai-agent.
You can find installation instructions and usage details in the obelisk GitHub repository at github.com/tommy0103/obelisk. The project has 512 stars and 36 forks, indicating an active community.
obelisk is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to obelisk on Agent Skills Hub include agf, ai-devkit, agent-sessions. 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: