emdash
Emdash reduces time-to-market for agentic systems by enabling parallel agent execution across multiple LLM providers, eliminating vendor lock-in and avoiding…
Emdash is the Open-Source Agentic Development Environment (🧡 YC W26). Run multiple coding agents in parallel. Use any provider.
- Ask Claude to generate boilerplate code across multiple service modules simultaneously.
- Automate parallel code generation tasks using different AI providers for comparison.
- Run independent coding agents on separate microservices without manual coordination overhead.
Emdash reduces time-to-market for agentic systems by enabling parallel agent execution across multiple LLM providers, eliminating vendor lock-in and avoiding single-provider bottlenecks that slow development cycles.
Engineering teams building multi-agent AI systems who need provider flexibility and parallel execution without custom orchestration infrastructure.
https://github.com/generalaction/emdash
By generalaction
How to Get It
claude plugins install generalaction/emdash
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Generate boilerplate code across multiple service modules simultaneously
Trust Signals Auto-scanned
Community Pulse Active
Discussed on Hacker News
- Show HN: Emdash – Open-source agentic development environment — Hacker News · 206 pts
- Show HN: OS layer for running multiple Codex agents in parallel — Hacker News · 7 pts
- Emdash: Open-Source Agentic IDE for Orchestrating Multiple Coding Agents — Hacker News · 2 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 5,893 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 5,893 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.