QoderAI's Better Harness Grades the Workflow Your Coding Agent Ignores
QoderAI's Better Harness plugs into Claude Code, Codex, Cursor and Copilot to audit how your coding agents actually work, not just what they ship.
PRO- QoderAI released Better Harness, MIT-licensed workflow analysis for coding agents.
- Grades five Agent Work Loop dimensions: Task Understanding, Controlled Execution, Change Validation, Reliable Delivery, Learning Capture.
- Ten host adapters, six verified: Claude Code, Codex, Qoder, Cursor, Qwen Code, GitHub Copilot CLI.
- Produces self-contained HTML plus Markdown reports; Qoder and Cursor use native Canvas output.
- Missing evidence stays explicit rather than being inferred, per the official site.
- Each finding includes evidence, impact, bounded repair, and acceptance checks reviewable in-agent.
Everyone is shipping code faster with coding agents, but almost nobody is measuring whether the workflow around those agents holds up. Better Harness, a new MIT-licensed project from QoderAI, treats that gap as its own engineering discipline. It plugs into the coding agent you already use, ingests project and session evidence, and produces a report that scores five parts of the agent's work loop and hands you scoped fixes.
The framing is deliberately narrow. Reviewing only the final diff misses system-level problems, so Better Harness analyzes the workflow around the diff by gathering project evidence, evaluating five connected dimensions, and turning gaps into prioritized findings tied to evidence, expected outcome, repair boundary, and validation route. If a signal isn't observed, the tool refuses to invent a score for it.
The five-part loop it grades
Better Harness models agent-assisted delivery as what it calls the Agent Work Loop, then evaluates each stage against concrete artifacts in your repo and session logs:
- Task Understanding: does the agent know the goal, backed by
AGENTS.md, specs, andDESIGN.md. - Controlled Execution: is work happening on repeatable paths through Skills, commands, MCP tools, and sandbox boundaries.
- Change Validation: is there real evidence the change works, via tests, lint, Hooks, and diagnostics.
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