DataFlow-Harness: A Grounded Code-Agent Platform for Constructing Editable LLM Data Pipelines
The paper’s claim is that grounding a coding agent in a live DAG platform can turn LLM-built data workflows into editable artifacts, not just scripts.
DataFlow-Harness steers the agent through typed, incremental pipeline mutations using skills, MCP access to operator/state context, and a synchronized web UI. On a 12-task benchmark, it reports a 93.3% observed end-to-end pass rate. Compared with Vanilla Claude Code, the authors report 72.5% lower measured cost and 49.9% lower generation latency. HF Daily Papers' note
DataFlow-Harness steers the agent through typed, incremental pipeline mutations using skills, MCP access to operator/state context, and a synchronized web UI. On a 12-task benchmark, it reports a 93.3% observed end-to-end pass rate. Compared with Vanilla Claude Code, the authors report 72.5% lower measured cost and 49.9% lower generation latency. HF Daily Papers' note
score 5