arXiv (All)
open access
The Role of Agentic Instruction Categories for Code Generation: A Study of Five Python Libraries
Agentic coding systems increasingly rely on repository-level agent files, such as AGENTS.md, to communicate project knowledge and developer intent. However, it remains unclear which categories of agent instructions enable efficient agent-file generation and accurate code generation. We evaluate five
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- The Role of Agentic Instruction Categories for Code Generation: A Study of Five Python Libraries#1348915
- Agentic Hardware Design as Repository-Level Code Evolution#319700
- Case Studies and Reflections on Agentic Software Engineering for Rapid Development of Digital Music Instruments#217809
- Case Studies and Reflections on Agentic Software Engineering for Rapid Development of Digital Music Instruments#187385
- A Systematic Evaluation of Trajectory Data Curation for LoRA Fine-Tuning of Code Agents#386968
Record · ID 1356757
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive