View-oriented Conversation Compiler for Agent Trace Analysis

• URL: http://arxiv.org/abs/2603.29678v2
• Date: Wed, 01 Apr 2026 13:52:38 GMT
• Title: View-oriented Conversation Compiler for Agent Trace Analysis
• Abstract summary: This paper presents VCC (View-oriented Conversation Compiler) that transforms raw agentL logs into a family of structured views.<n>In an experiment on AppWorld, replacing only the reflector's input format, from rawL to VCC-compiled views, leads to higher pass rates across all three model configurations.<n>These results suggest that message format functions as infrastructure for context engineering, not as an incidental implementation choice.
• Score: 32.00791796013423
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Agent traces carry increasing analytical value in agentic systems and context engineering, yet most prior work treats conversation format as a trivial implementation detail. Modern agent conversations, however, contain deeply structured content, including nested tool calls and results, chain-of-thought reasoning blocks, sub-agent invocations, context-window compaction boundaries, and harness-injected system directives, whose complexity far exceeds that of simple user-assistant exchanges. Feeding such traces to a reflector or other analytical mechanism in plain text, JSON, YAML, or via grep can materially degrade analysis quality. This paper presents VCC (View-oriented Conversation Compiler), a compiler (lex, parse, IR, lower, emit) that transforms raw agent JSONL logs into a family of structured views: a full view (lossless transcript serving as the canonical line-number coordinate system), a user-interface (UI) view (reconstructing the interaction as the user actually perceived it), and an adaptive view (a structure-preserving projection governed by a relevance predicate). In a context-engineering experiment on AppWorld, replacing only the reflector's input format, from raw JSONL to VCC-compiled views, leads to higher pass rates across all three model configurations tested, while cutting reflector token consumption by half to two-thirds and producing more concise learned memory. These results suggest that message format functions as infrastructure for context engineering, not as an incidental implementation choice.

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