ara-compiler

Convert diverse research inputs into Agent-Native Research Artifacts with cognitive and physical layers.

20|25|Updated May 30, 2026
One-click install
npx skills add https://github.com/OpenCoven/coven-cave --skill ara-compiler
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ara-compiler
Source: https://github.com/OpenCoven/coven-cave/tree/main/marketplace/craft-sources/archivists-index/compiler
Command: npx skills add https://github.com/OpenCoven/coven-cave --skill ara-compiler

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The ara-compiler skill addresses the challenge of converting diverse research inputs—such as papers, code, logs, and notes—into structured, machine-executable knowledge artifacts called Agent-Native Research Artifacts (ARA).

Core Features & Use Cases

  • Research Input Compilation: Converts PDFs, code repositories, logs, and notes into ARAs.
  • Cognitive Layer Construction: Builds cognitive layers with claims, concepts, heuristics, and exploration graphs.
  • Physical Layer Construction: Creates physical layers with configurations, code stubs, and grounded evidence.
  • Use Case: Ideal for academic researchers or AI agents needing to organize complex research findings into a machine-readable format for analysis or decision-making.

Quick Start

To compile research from a PDF, use the ara-compiler skill with the input file 'research_paper.pdf'.

Frequently Asked Questions about ara-compiler

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

FAQPage Schema
How do I convert a research PDF into structured knowledge for AI agents?▼

To convert a research PDF into structured knowledge, you can use an epistemic protocol that transforms the input into an Agent-Native Research Artifact. This process builds cognitive layers containing claims and concepts alongside physical layers with code stubs and grounded evidence.

What is an Agent-Native Research Artifact and how does it organize research inputs?▼

An Agent-Native Research Artifact (ARA) is a structured, machine-executable knowledge format that organizes diverse research inputs. It enriches data by constructing cognitive layers with exploration graphs and heuristics, and physical layers with configurations and grounded evidence.

Can I compile code repositories and logs into a machine-readable research artifact?▼

Yes, you can compile code repositories, logs, and notes into a machine-readable research artifact. The compilation process extracts claims and concepts to build a cognitive layer, while generating code stubs and configurations for the physical layer.

Does the knowledge extraction process support both academic papers and codebase inputs?▼

The knowledge extraction process supports both academic papers and codebase inputs, alongside logs and notes. It utilizes an epistemic protocol to validate and structure these diverse inputs into a unified artifact with distinct cognitive and physical layers.

What is the best way to structure complex research findings for automated decision-making?▼

The best way to structure complex research findings for automated decision-making is to compile them into an Agent-Native Research Artifact. This format uses an epistemic protocol to map claims, concepts, and heuristics into machine-executable cognitive and physical layers.