DataFlow-Harness builds editable LLM data pipelines with MCP and code agents
_akhaliq · x · 2026-07-23
DataFlow-Harness uses a code agent to build editable LLM data pipelines
The paper introduces DataFlow-Harness, a grounded code-agent platform for constructing persistent, editable data pipelines instead of one-off scripts.
Key pieces include:
- DataFlow-Skills for procedural guidance
- an MCP layer exposing the live operator registry and pipeline state
- DataFlow-WebUI for syncing conversation-based authoring with a visual DAG editor
On a 12-task data-engineering benchmark, it reports a 93.3% observed end-to-end pass rate. Compared with Vanilla Claude Code, it claims 72.5% lower monetary cost and 49.9% lower generation latency, while staying within 0.9 percentage points of the Context-Aware Claude Code baseline in observed pass rate.
Related event: DataFlow-Harness: An Editable LLM Data Pipeline Platform(3 posts)→
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