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 growthxai · Claude Skill · ★ 438
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is output safe to install? View the security audit →
Output The open-source TypeScript framework for building AI workflows and agents. Designed for Claude Code — describe what you want, Claude builds it, with all the best practices already in place. One framework. Prompts, evals, tracing, cost tracking, orchestration, credentials. No SaaS fragmentation. No vendor lock-in. Everything in your codebase, everything your AI coding agent can reach. ▶ Watch a complete example of using Output to build a newsletter pipeline Why Output Every piece of the AI stack is becoming a separate subscription. Prompts in one tool. Traces in another. Evals in a third. Cost tracking across five dashboards. None of them t
| Stars | 438 |
| Forks | 13 |
| Language | JavaScript |
| Category | Claude Skill |
| License | Apache-2.0 |
| Quality Score | 72.9531581437436/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-22 |
| Created | 2026-03-13 |
| Platforms | claude-code, node |
| Est. Tokens | ~15k |
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output is The open-source TypeScript framework for building AI workflows and agents. Designed for Claude Code describe what you want, Claude builds it, with all the best practices already in place.. It is categorized as a Claude Skill with 438 GitHub stars.
output is primarily written in JavaScript. It covers topics such as agents, ai, ai-agents.
You can find installation instructions and usage details in the output GitHub repository at github.com/growthxai/output. The project has 438 stars and 13 forks, indicating an active community.
output is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to output on Agent Skills Hub include agents, studio, mesh. 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: