superset — security grade SAFE, quality 74/100

Security audit verdict: SAFE · quality 74/100

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 superset-sh · Codex Skill · ★ 14.5k

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

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About superset

The Terminal for Coding Agents Download for macOS  •  Documentation  •  Changelog  •  Discord Why Superset? Superset is a turbocharged terminal that allows you to run any CLI coding agents along with the tools to 10x your development workflow. Run multiple agents simultaneously without context switching overhead Isolate each task in its own git worktree so agents don't interfere with each other Monitor all your agents from one place and get notified when they need attention Review changes quickly with buil

adeagentagent-orchestrationai-agentsai-codingclaude-codeclicodexcoding-agentscursor-agent

Quick Facts

Stars14,540
Forks1,303
LanguageTypeScript
CategoryCodex Skill
Quality Score74.2487838215405/100
Open Issues762
Last Updated2026-09-23
Created2025-10-21
Platformsclaude-code, cli, codex, node
Est. Tokens~16k

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Frequently Asked Questions

What is superset?

superset is Superset is an agentic IDE to orchestrate 100+ coding agents in parallel. Run any agent with your own subscription.. It is categorized as a Codex Skill with 14.5k GitHub stars.

What programming language is superset written in?

superset is primarily written in TypeScript. It covers topics such as ade, agent, agent-orchestration.

How do I install or use superset?

You can find installation instructions and usage details in the superset GitHub repository at github.com/superset-sh/superset. The project has 14.5k stars and 1303 forks, indicating an active community.

What are the best alternatives to superset?

The top alternatives to superset on Agent Skills Hub include cmux, codeg, claude_codex_bridge. 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:

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