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 rivet-dev · Agent Tool · ★ 6.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is actors safe to install? View the security audit →
Rivet Actors are the primitive for stateful workloads. Built for AI agents, collaborative apps, and durable execution. Quickstart • Documentation • Changelog • Discord • X What is Rivet? Rivet Actors are long-running, lightweight processes designed for stateful workloads. State lives in-memory with automatic persistence. Create one per agent, per session, or per user — with built-in workflows, queues, and scheduling. Backend typescript const agent = actor({ // In-memory, persisted state for the actor state: { messages: [] as Message[] }, // Long-running actor process run: async (c) = { // Process incoming messages from the queue for await (const msg of c.queue.iter()) { c.state.messages.push({ role: "user", content: msg.body.text }); const response = streamText({ model: openai("gpt-5"), messages: c.state.messages }); // Stream realtime events to all conne
| Stars | 6,160 |
| Forks | 253 |
| Language | Rust |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 65.7749502242352/100 |
| Open Issues | 287 |
| Last Updated | 2026-09-23 |
| Created | 2023-06-16 |
| Platforms | rust |
| Est. Tokens | ~25k |
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actors is Rivet Actors are the primitive for stateful workloads. Built for AI agents, collaborative apps, and durable execution.. It is categorized as a Agent Tool with 6.2k GitHub stars.
actors is primarily written in Rust. It covers topics such as actor, actors, cloudflare.
You can find installation instructions and usage details in the actors GitHub repository at github.com/rivet-dev/actors. The project has 6.2k stars and 253 forks, indicating an active community.
actors is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to actors on Agent Skills Hub include yomo, opcode, mcp-for-beginners. 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: