Action Converter

Convert open-loop signals into prioritized actions with observable deliverables.

Updated Jun 3, 2026
One-click install
npx skills add https://github.com/swarm-ai-research/aeon --skill action-converter-swarm-ai-research
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Action Converter
Source: https://github.com/swarm-ai-research/aeon/tree/main/skills/action-converter
Command: npx skills add https://github.com/swarm-ai-research/aeon --skill action-converter-swarm-ai-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts scattered open loops, memory items, and priorities into concrete, trackable actions ready for execution.

Core Features & Use Cases

  • Extracts open loops from memory, logs, topics, and cron-state data and scores them for feasibility and impact.
  • Produces a prioritized five-action plan, with observable deliverables and time-bound targets.
  • Handles bootstrap when context is incomplete and degrades gracefully when data sources are missing.

Quick Start

Run the action converter to transform your current open loops and topics into five concrete tasks for today.

Frequently Asked Questions about Action Converter

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

FAQPage Schema
How do I convert open loops from memory logs into prioritized tasks?

To convert open loops into prioritized tasks, the system applies a five-step pipeline that scores memory logs for feasibility and impact, generating a deterministic set of five concrete actions for today.

What is the best way to turn scattered topics and cron-state data into trackable actions?

The best way to turn scattered topics and cron-state data into trackable actions is using a conversion pipeline that gates actions based on available context and produces time-bound targets with observable deliverables.

Can I generate a daily action plan when my memory context is incomplete?

Yes, you can generate a daily action plan with incomplete memory context because the system handles bootstrap initialization and degrades gracefully when data sources are missing.

How does loop scoring work when prioritizing actions for today?

Loop scoring evaluates open-loop signals from your inputs to assess feasibility and impact, gating them through a deterministic pipeline to output a prioritized five-action plan with observable deliverables.

Do I need external dependencies to extract actions from PRs and memory logs?

No external dependencies are required to extract actions from PRs and memory logs; the system operates independently to process signals and generate a deterministic action set when context is available.