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Roundtable Debuts Codex Skill That Finds Bugs, Proves Them With Tests, and Pinpoints Root Cause

July 16, 2026 at 05:45 EDT

Software Dev & Coding
AI Agents
Open Source

A new debugging workflow built for OpenAI's Codex aims to move AI coding assistants beyond symptom-patching, surfacing likely bugs, reproducing them through automated tests, and identifying the exact root cause before a fix is applied. The skill was showcased in a video demo tied to Roundtable AI, a locally running orchestration layer for AI coding tools.

Codex Skill · Roundtable AI

Debugging that finds the root cause — before it patches the symptom

A new workflow for OpenAI's Codex surfaces likely bugs, reproduces them with automated tests, then traces each defect to its underlying source — replacing quick symptom-patching with disciplined root cause analysis.

The three-part debug loop

1 · DETECT

Surface probable defects across the codebase.

→

2 · REPRODUCE

Confirm each bug with a test that reproduces the failure.

→

3 · ROOT CAUSE

Trace to the underlying source, then fix — not the symptom.

AI assistants unified: Codex, Claude Code, Cursor, Gemini

Config required — auto-discovery, npx install

114

GitHub stars at time of reference

One layer, many models

Roundtable runs locally as an MCP server, orchestrating tools that otherwise work in isolation.

1 tool

standalone assistant

4 tools

coordinated via one layer

The case for it

Proving a bug with a reproducible test discourages guesswork, cuts speculative edits, and stops a cascade of ineffective fixes by targeting the real defect first.

The open question

Integration, API and config errors dominate real bugs. How much these skills cover varies by use case — and reviews so far rest on a demo, not broad hands-on reports.

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