On the Use of Agentic Coding Manifests: An Empirical Study of Claude Code
On the map: LLM agents and tool use → Software engineering coding agents
Abstract (arXiv)
Agentic coding tools receive goals written in natural language as input, break them down into specific tasks, and write/execute the actual code with minimal human intervention. Key to this process are agent manifests, configuration files (such as Claude.md) that provide agents with essential project context, identity, and operational rules. However, the lack of comprehensive and accessible documentation for creating these manifests presents a significant challenge for developers. We analyzed 253 Claude.md files from 242 repositories to identify structural patterns and common content. Our findings show that manifests typically have shallow hierarchies with one main heading and several subsections, with content dominated by operational commands, technical implementation notes, and high-level architecture.
Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 12 of its 16 references that are in the map. First posted on arXiv 18 Sep 2025.
Builds on
12 of 16 references.
Closest ancestors · 1
Same direction, newest first
Other references · 11
- 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,434
- 2024The Prompt Report: A Systematic Survey of Prompt Engineering Techniquescited by 121
- 2024Can LLMs Replace Manual Annotation of Software Engineering Artifacts?cited by 42
- 2024AutoDev: Automated AI-Driven Developmentcited by 24
- 2024On the Impacts of Contexts on Repository-Level Code Generationcited by 22
- 2018Categorizing the Content of GitHub README Filescited by 18
- 2025Conversational AI as a Coding Assistant: Understanding Programmers' Interactions with and Expectations from Large Language Models for Codingcited by 11
- 2025Towards an Understanding of Context Utilization in Code Intelligencecited by 10
- 2025Knowledge Graph Based Repository-Level Code Generationcited by 4
- 2025The Introduction of README and CONTRIBUTING Files in Open Source Software Developmentcited by 3
- 2023Exploring the intersection of Generative AI and Software Developmentcited by 2
Built on by
Citing papers per year: 2025: 2; 2026: 12.
14 papers.
Sort:
- 2025Agent READMEs: An Empirical Study of Context Files for Agentic Codingcited by 23
- 2026AgentHazard: A Benchmark for Evaluating Harmful Behavior in Computer-Use Agentscited by 18
- 2025Agentsway -- Software Development Methodology for AI Agents-based Teamscited by 14
- 2026A Practical Guide to Agentic AI Transition in Organizationscited by 5
- 2026Codified Context: Infrastructure for AI Agents in a Complex Codebasecited by 5
- 2026Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Developmentcited by 4
- 2026From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintainedcited by 2
- 2026Configuration Smells in AGENTS.md Files: Common Mistakes in Configuring Coding Agentscited by 1
- 2026Evidence-Calibrated Runtime Reconstruction for Agent Skills Across Heterogeneous Coding Agentscited by 1
- 2026AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agentcited by 0
- 2026Can Open-Source LLM Agents Replace Static Application Security Testing Tools? An Empirical Assessmentcited by 0
- 2026From Agent Behaviour to Agent-Friendly Documentation: An Empirical Study of How Coding Agents Discover, Read, and Write Technical Documentationcited by 0
- 2026Specifying and Maintaining Agentic Workflows: An Empirical Study of GitHub Agentic Workflows23 Sep 2026
- 2026On the Maintenance and Co-evolution of Agent Plugins: An Empirical Study of Claude Code Plugin Marketplaces28 Aug 2026
- 2026From Agent Behaviour to Agent-Friendly Documentation: An Empirical Study of How Coding Agents Discover, Read, and Write Technical Documentation20 Aug 2026
- 2026Evidence-Calibrated Runtime Reconstruction for Agent Skills Across Heterogeneous Coding Agents9 Aug 2026
- 2026From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintained1 Jul 2026
- 2026Configuration Smells in AGENTS.md Files: Common Mistakes in Configuring Coding Agents14 Jun 2026
- 2026Can Open-Source LLM Agents Replace Static Application Security Testing Tools? An Empirical Assessment10 Jun 2026
- 2026AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent7 Apr 2026
- 2026AgentHazard: A Benchmark for Evaluating Harmful Behavior in Computer-Use Agents3 Apr 2026
- 2026Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Development16 Mar 2026
- 2026Codified Context: Infrastructure for AI Agents in a Complex Codebase24 Feb 2026
- 2026A Practical Guide to Agentic AI Transition in Organizations27 Jan 2026
2 more
- 2025Agent READMEs: An Empirical Study of Context Files for Agentic Codingcited by 23
- 2026AgentHazard: A Benchmark for Evaluating Harmful Behavior in Computer-Use Agentscited by 18
- 2025Agentsway -- Software Development Methodology for AI Agents-based Teamscited by 14
- 2026A Practical Guide to Agentic AI Transition in Organizationscited by 5
- 2026Codified Context: Infrastructure for AI Agents in a Complex Codebasecited by 5
- 2026Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Developmentcited by 4
- 2026From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintainedcited by 2
- 2026Configuration Smells in AGENTS.md Files: Common Mistakes in Configuring Coding Agentscited by 1
- 2026Evidence-Calibrated Runtime Reconstruction for Agent Skills Across Heterogeneous Coding Agentscited by 1
- 2026AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agentcited by 0
- 2026Can Open-Source LLM Agents Replace Static Application Security Testing Tools? An Empirical Assessmentcited by 0
- 2026From Agent Behaviour to Agent-Friendly Documentation: An Empirical Study of How Coding Agents Discover, Read, and Write Technical Documentationcited by 0
12 most cited of 14 All 14 (JSON)
- 2026Specifying and Maintaining Agentic Workflows: An Empirical Study of GitHub Agentic Workflows23 Sep 2026
- 2026On the Maintenance and Co-evolution of Agent Plugins: An Empirical Study of Claude Code Plugin Marketplaces28 Aug 2026
- 2026From Agent Behaviour to Agent-Friendly Documentation: An Empirical Study of How Coding Agents Discover, Read, and Write Technical Documentation20 Aug 2026
- 2026Evidence-Calibrated Runtime Reconstruction for Agent Skills Across Heterogeneous Coding Agents9 Aug 2026
- 2026From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintained1 Jul 2026
- 2026Configuration Smells in AGENTS.md Files: Common Mistakes in Configuring Coding Agents14 Jun 2026
- 2026Can Open-Source LLM Agents Replace Static Application Security Testing Tools? An Empirical Assessment10 Jun 2026
- 2026AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent7 Apr 2026
- 2026AgentHazard: A Benchmark for Evaluating Harmful Behavior in Computer-Use Agents3 Apr 2026
- 2026Knowledge Activation: AI Skills as the Institutional Knowledge Primitive for Agentic Software Development16 Mar 2026
- 2026Codified Context: Infrastructure for AI Agents in a Complex Codebase24 Feb 2026
- 2026A Practical Guide to Agentic AI Transition in Organizations27 Jan 2026
12 newest of 14 All 14 (JSON)
Similar, not cited
Close in wording, no citation either way
- 2025Decoding the Configuration of AI Coding Agents: Insights from Claude Code Projects
- 2026Harness Engineering for Agentic AI Coding Tools: An Exploratory Study
- 2026An Exploratory Study of Agent Plans for Agentic AI Coding Tools in Open-Source Software
- 2025On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub
- 2026Dive into Claude Code: The Design Space of Today's and Future AI Agent Systems
- 2025Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
- 2026A Dataset of Agentic AI Coding Tool Configurations
- 2025Agentic Refactoring: An Empirical Study of AI Coding Agents