cyrnel

Orchestrate multi-step tool chains in a sandboxed runtime for external APIs.

15|4|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/actelos/cyrnel --skill cyrnel
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cyrnel
Source: https://github.com/actelos/cyrnel/tree/main
Command: npx skills add https://github.com/actelos/cyrnel --skill cyrnel

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

Cyrnel solves the complexity of connecting AI applications to diverse external services by providing a modular, secure, and standardized docking station for any protocol or tool.

Core Features & Use Cases

  • Unified Orchestration: Discover, chain, and invoke tools from multiple services within a single, secure sandboxed runtime.
  • Efficient Data Handling: Filter and transform API responses directly in the sandbox to minimize context window bloat and reduce costs.
  • Use Case: If you need to fetch data from a CRM, process it through a custom TypeScript sandbox, and then update a project management tool, Cyrnel handles the entire workflow in one efficient, chained process.

Quick Start

Use the cyrnel skill to discover available tools and execute a chained process that fetches data from an external service and filters the result.

Frequently Asked Questions about cyrnel

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate LLMs with external APIs for multi-step workflows?

You can integrate LLMs with external APIs by using a secure, sandboxed runtime environment to orchestrate and execute multi-step tool chains. This approach facilitates discovery and chaining across heterogeneous protocols for complex automated workflows.

What is the best way to reduce context window bloat when processing API responses in LLM applications?

To reduce context window bloat, filter and transform API responses directly within a sandboxed runtime before returning them to the LLM. This minimizes unnecessary data processing and reduces operational costs.

Can I orchestrate chained API calls across heterogeneous protocols in a single runtime?

Yes, you can orchestrate chained API calls across heterogeneous protocols within a single unified runtime. The sandboxed environment securely handles service discovery, invocation, and data transformation across diverse external services.

How do I execute a workflow that fetches CRM data, processes it, and updates a project management tool?

You can execute this workflow by chaining tools within a sandboxed runtime environment. The orchestration layer fetches data from the CRM, processes it through a custom sandbox, and updates the project management tool in one efficient process.

Do I need a sandboxed runtime to securely connect AI applications to diverse external services?

A sandboxed runtime provides a standardized, secure docking station for any protocol or tool. It ensures secure service communication and isolated execution, which is critical when connecting AI applications to diverse external services.