[2603.00822] ContextCov: Deriving and Enforcing Executable Constraints from Agent Instruction Files

Computer Science > Software Engineering arXiv:2603.00822 (cs) [Submitted on 28 Feb 2026] Title:ContextCov: Deriving and Enforcing Executable Constraints from Agent Instruction Files Authors:Reshabh K Sharma View a PDF of the paper titled ContextCov: Deriving and Enforcing Executable Constraints from Agent Instruction Files, by Reshabh K Sharma View PDF HTML (experimental) Abstract:As Large Language Model (LLM) agents increasingly execute complex, autonomous software engineering tasks, developers rely on natural language Agent Instructions (e.g., this http URL) to enforce project-specific coding conventions, tooling, and architectural boundaries. However, these instructions are passive text. Agents frequently deviate from them due to context limitations or conflicting legacy code, a phenomenon we term Context Drift. Because agents operate without real-time human supervision, these silent violations rapidly compound into technical debt. To bridge this gap, we introduce ContextCov, a framework that transforms passive Agent Instructions into active, executable guardrails. ContextCov extracts natural language constraints and synthesizes enforcement checks across three domains: static AST analysis for code patterns, runtime shell shims that intercept prohibited commands, and architectural validators for structural and semantic constraints. Evaluations on 723 open-source repositories demonstrate that ContextCov successfully extracts over 46,000 executable checks with 99.997% synt...