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Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents?

Evaluating AGENTS.md: Are Repository-Level Context Files Helpful for Coding Agents?\n\n

Paper: 2602.11988\n Authors: Thibaud Gloaguen, Niels Mündler, Mark Müller, Veselin Raychev, Martin Vechev\nVechev Published: February 2026\n\n##2026

Summary\n\nThis

Summary

This paper evaluates whether repository-level context files (like AGENTS.md)) actually help coding agents perform better on real-world software engineering tasks.\n\n##

Key Findings\n\n###Findings

Performance Impact\n-Impact

  • LLM-generated context files: Decrease task success rates by ~3% on average\n-average
  • Developer-provided context files: Marginally improve performance by ~4% on average\n-average
  • No context files: Baseline performance\n\n###performance

Cost Impact\n-Impact

  • Context files increase inference costs by over 20% on average\n-average
  • More steps required to complete tasks (2.45-3.92 additional steps)\n\n###

Behavioral Changes\n-Changes

  • More testing and exploration: Agents run more tests, search more files, read more files\n-files
  • Instruction following: Agents generally follow instructions in context files\n-files
  • Redundant documentation: Context files are often redundant with existing documentation\n-documentation
  • No effective overviews: Context files don't provide useful repository overviews\n\n##overviews
    • AGENTBENCH\n\nThe

AGENTBENCH

The authors created a new benchmark called AGENTBENCH consisting of:\n-

  • 138 unique instances from 12 repositories\n-repositories
  • Real GitHub issues (bug-fixing and feature addition tasks)\n-
  • Developer-written context files\n-files
  • Python software engineering tasks\n\nAGENTBENCHtasks

AGENTBENCH complements SWE-BENCH LITE (which uses popular repositories without context files).\n\n##

Experimental Setup\n\n###Setup

Coding Agents Evaluated\n-Evaluated

  • CLAUDE CODE with SONNET-4.5\n-5
  • CODEX with GPT-5.2 and GPT-5.1 MINI\n-MINI
  • QWEN CODE with QWEN3-30B-CODER\n\n###CODER
    • Datasets\n-

Datasets

  • SWE-BENCH LITE: 300 tasks from 11 popular Python repositories (no context files)\n-
  • AGENTBENCH: 138 tasks from 12 repositories with developer-provided context files\n\n###files

Settings Evaluated\n1.Evaluated

  1. NONE: No context files\n2.files
  2. LLM: LLM-generated context files (using agent-developer recommendations)\n3.
  3. HUM: Developer-provided context files\n\n##files

Key Insights\n\n###Insights

1. Context Files Make Tasks Harder\nInstructionsHarder

Instructions in context files increase reasoning tokens by 14-22%, suggesting tasks become more complex.\n\n###

2. Context Files Are Redundant\nWhenRedundant

When documentation files are removed from repositories, LLM-generated context files actually improve performance by 2.7% on average.\n\n###

3. Stronger Models Don't Generate Better Context Files\nUsingFiles

Using GPT-5.2 to generate context files improves SWE-BENCH LITE performance by 2% but degrades AGENTBENCH performance by 3%.\n\n###

4. Context Files Encourage Exploration\nAgentsExploration

Agents use more repository-specific tools (e.g., uv,, repo_tool)) and run more tests when context files are present.\n\n##

Recommendations\n\n1.

Recommendations

  1. Omit LLM-generated context files for now, contrary to agent-developer recommendations\n2.recommendations
  2. Include only minimal requirements in context files (e.g., specific tooling to use)\n3.
  3. Human-written context files should describe only essential information\n4.information
  4. Future work: Improve automatic generation of concise, task-relevant guidance\n\n##guidance
    5. Limitations\n\n-

Limitations

  • Evaluation focused heavily on Python (a language well-represented in training data)\n-
  • Context files are a recent development (August 2025)\n-
  • Popular repositories used in benchmarks may not be representative of most codebases\n\n##codebases
  • SWE-BENCH: Repository-level coding agent evaluation\n-evaluation
  • AGENTBENCH: New benchmark for context file evaluation\n-evaluation
  • Context files: AGENTS.md, CLAUDE.md, README files for agents\n\n##agents
    • Conclusion\n\nContext

Conclusion

Context files have only a marginal effect on coding agent behavior. While they encourage broader exploration and instruction following, they don't provide effective repository overviews and often make tasks harder. The authors recommend omitting LLM-generated context files and including only minimal requirements in human-written ones.\n\n---\n

Tags: #agents #context-files #evaluation #SWE-bench #LLM-agents

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