Agent Context Impact Analyzer

DAIR.AI 288-Run Benchmark
📝 Repository Prompt Context (AGENTS.md / CLAUDE.md) 342 Tokens
🎯 Injection Strategy Strategy
Full AGENTS.md File Inject complete repo instructions verbatim into context.
Modular On-Demand Include architecture & test rules only for active file scope.
System Prompt Direct Core constraints injected directly as system message.
Minimal Baseline Strip all formatting/style guidelines; retain core logic.
🔍 Rule Category Toggles & Noise Diagnostics

Toggle categories off to simulate context optimization. High formatting overhead produces zero accuracy lift.

Total Prompt Tokens 342 Context overhead
Signal / Noise Ratio 38.5% 210 noise tokens
Primary Bottleneck Formatting & Style 61.4% total noise
📊 Token Category Distribution Breakdown
Context Token Allocation by Rule Type
🧪 Simulated Task Correctness vs Context Overhead
Strategy Tokens Claude Code Codex Acc Delta

* Based on 288 gold-test evaluation runs. Correctness does not move statistically between full context and minimal baseline (+0.3-0.5%).

✅ Active Optimization Proof
Signal Ratio 38.5%
Redundant Tokens 210
Claude Delta +0.5%
🚀 Optimized AGENTS.md Output
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