arXiv Artificial Intelligence

View-oriented Conversation Compiler for Agent Trace Analysis

View-oriented Conversation Compiler for Agent Trace Analysis

Quick summary

arXiv:2603.29678v3 Announce Type: replace Abstract: We observe that an agent trace is a structured document. A coding agent session contains user turns, assistant text, chain of thought blocks, tool calls, tool results, subagent invocations, compaction boundaries, and harness injected directives, and may exceed ten thousand JSONL lines. Effective trace analysis requires a lossless record, a session level overview, and content retrieval with conversational roles. To this end, we propose VCC, namely View oriented Conversation Compiler, which lexes, parses, and lowers a raw JSONL log into three v

Key takeaways

  • arXiv:2603.29678v3 Announce Type: replace Abstract: We observe that an agent trace is a structured document.
  • A coding agent session contains user turns, assistant text, chain of thought blocks, tool calls, tool results, subagent invocations, compaction boundaries, and harness injected directives, and may exceed ten thousand JSONL lines.
  • Effective trace analysis requires a lossless record, a session level overview, and content retrieval with conversational roles.

Why it matters

This development shows AI moving deeper into everyday software. Productivity potential should be weighed against price, data permissions, exportability and the preservation of human control.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗