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codex-autoresearch

Skill Development Solid

A codex plugin for running optimization loops inside a codebase. It is useful when you have a measurable target and many possible changes to try: test runtime, build speed, bundle size, model loss, Lighthouse scores, memory use, query latency, or any other metric you can print from a script.

783 starsApache-2.0 (commercial OK)FreeQuick setup

Automates systematic performance tuning across measurable metrics, eliminating manual trial-and-error and reducing optimization cycle time from days to hours.

Engineering teams optimizing runtime, build speed, bundle size, or any quantifiable performance metric.

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https://github.com/TheGreenCedar/codex-autoresearch

By TheGreenCedar

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install TheGreenCedar/codex-autoresearch

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars783Last updated2026-06-21LicenseApache-2.0 (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-06-22 · scanner v1

Community Pulse New

No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 783 GitHub stars; contributors unknown; last commit 1d ago; license Apache-2.0.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
4/5
Versatility
4/5
Reliability
3/5
Security
3/5
Overall score3.60 / 5.00 SolidEvaluatedJun 2026
Scored from trust signals (evidence-eval-v1): 783 GitHub stars; contributors unknown; last commit 1d ago; license Apache-2.0.

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