mlsanityData to 7 Oct 2026

An Exploratory Study of Agent Plans for Agentic AI Coding Tools in Open-Source Software

arXiv 2608.04661 ↗First posted 5 Aug 2026cs.SEcited by 1

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Repository-level configuration artifacts allow developers to provide guidance for agentic AI coding tools, such as Claude Code, Gemini, etc. Although prior research has examined repository-shared context files that capture project-level instructions and conventions (e.g., AGENTS.md files), little is known about more task-oriented artifacts such as Agent Plans. We present an exploratory study of Agent Plans in open-source software repositories, examining how plan files are preserved, which development activities they support, and what information they provide to guide agent execution. We screened 36,710 GitHub repositories belonging to engineered software projects and identified 85 Markdown plan files from 10 repositories. Within this highly concentrated corpus, Agent Plans supported several kinds of software engineering work, including maintenance, design, construction, quality-related work, and process support. They also provided task-oriented execution guidance, most commonly through implementation steps, concrete files and locations, and testing and validation information. Overall, repository-preserved Agent Plans under these tool-specific directories appear to be a narrow but informative artifact for studying task intent and execution guidance in human-agent workflows.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 9 of its 23 references that are in the map. First posted on arXiv 5 Aug 2026.

Builds on

9 of 23 references.

Closest ancestors · 7

Same direction, newest first

  1. 2026A Dataset of Agentic AI Coding Tool Configurations8 May
  2. 2026AIDev: Studying AI Coding Agents on GitHub9 Feb
  3. 2026On the Impact of AGENTS.md Files on the Efficiency of AI Coding Agents28 Jan
  4. 2026Are We All Using Agents the Same Way? An Empirical Study of Core and Peripheral Developers Use of Coding Agents27 Jan
  5. 2026Agentic Much? Adoption of Coding Agents on GitHub26 Jan
  6. 2025Agent READMEs: An Empirical Study of Context Files for Agentic Coding17 Nov
  7. 2025On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub18 Sep

Other references · 2

  1. 2025A Study of LLMs' Preferences for Libraries and Programming Languagescited by 20
  2. 2025Context Engineering for AI Agents in Open-Source Softwarecited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

Similar, not cited

Close in wording, no citation either way

  1. 2026Harness Engineering for Agentic AI Coding Tools: An Exploratory Study
  2. 2025Decoding the Configuration of AI Coding Agents: Insights from Claude Code Projects
  3. 2025On the Use of Agentic Coding Manifests: An Empirical Study of Claude Code
  4. 2025Agentic Refactoring: An Empirical Study of AI Coding Agents
  5. 2026Scanning the Harness: A Repository Study of Configuration Exposures in AI Coding Agents
  6. 2026From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintained
  7. 2026Specifying and Maintaining Agentic Workflows: An Empirical Study of GitHub Agentic Workflows
  8. 2026Agentic AI in the Software Development Lifecycle: Architecture, Empirical Evidence, and the Reshaping of Software Engineering