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codex-ab

Run an A/B codex review experiment — holistic codex review vs 3 focused dimension passes (security, ecto, liveview) on the branch diff, classify findings, report a panel-value verdict

Install / Use

npx skills add oliver-kriska/claude-elixir-phoenix --skill codex-ab

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

87/100

Category

Security

Supported Platforms

OpenAI Codex

Our assessment of codex-ab

codex-ab scores 87/100 on our quality scale, 613th of 1,086 Security skills we index.

Its SKILL.md is 3.8 KB long, well organised into 11 sections with 4 code examples: a solid amount of guidance for an agent.

It has 560 GitHub stars, a meaningful sign that others use it.

Substance
26/30
Structure
20/20
Description
15/15
Adoption
12/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 2 days ago, so codex-ab is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

codex-ab compared with similar skills

All 4 of these similar skills score higher than codex-ab; compare them before choosing.

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codex-ab (this skill)by oliver-kriska875602d agoSKILL.md
algorithmic-artby anthropics100177.9k11d agoSKILL.md
pptxby anthropics100177.9k11d agoSKILL.md
designby nextlevelbuilder100130.2k12d agoSKILL.md
ui-ux-pro-maxby nextlevelbuilder100130.2k12d agoSKILL.md

Frequently asked questions

How do I install codex-ab?
Run npx skills add oliver-kriska/claude-elixir-phoenix --skill codex-ab. The install tabs above show the steps for each supported agent.
Which AI agents does codex-ab work with?
It is written for OpenAI Codex, as a SKILL.md file. Other agents that read the same format can often use it too.
Is codex-ab safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is codex-ab still maintained?
The repository was last updated 2 days ago, so codex-ab is actively maintained.

name: codex-ab description: Run an A/B codex review experiment — holistic codex review vs 3 focused dimension passes (security, ecto, liveview) on the branch diff, classify findings, report a panel-value verdict. Use when the branch is fresh, before any codex review runs. effort: medium argument-hint: "[base-branch]"

Codex Panel A/B (contributor instrument — verdict decided)

Answer one question with evidence: do dimension-focused codex passes find real issues that one holistic codex exec review misses? Runs both on the same diff, then classifies every focused finding against the holistic pass.

DECIDED 2026-07-10 after 4 runs (2 fresh): panel KILLED. Fresh-only 1 real miss / 1 false positive plus one zero-value run at 4× cost — real misses did not outnumber FPs. Kept as contributor tooling (NOT distributed) for one possible retest: a UI-heavy diff with a single extra liveview-focused pass (2× cost). Scoreboard: .claude/research/2026-07-03-codex-review-integration.md §7.

Usage

/codex-ab            # A/B against main (~5 min, 4 codex runs)
/codex-ab develop    # explicit base branch

Iron Laws

  1. FRESH DIFF ONLY — ask the user to confirm this branch has NOT been codex-reviewed yet (cloud or /phx:codex-loop). A drained diff returns NO FINDINGS everywhere and proves nothing — wasted quota
  2. Verify every REAL MISS in the code before counting it — a focused finding only scores if the issue actually exists at that file:line
  3. Read ONLY the findings .md files — streams are diverted to .log files; never cat a log into context (10k+ lines each)
  4. Exactly 4 codex runs, never re-run dimensions — bounded quota
  5. Persist the verdict — an unrecorded experiment is wasted quota

Workflow

Step 1: Preflight

Run command -v codex — missing → STOP with install hint. Then:

  • git status --short dirty → warn (codex flags local dirt as findings)
  • Ask: "Has codex already reviewed this branch (PR review or codex-loop)?" If yes → STOP, explain the fresh-diff requirement (Iron Law 1)

Step 2: Run the A/B (background, ~5 min)

bash ${CLAUDE_SKILL_DIR}/scripts/codex-panel-ab.sh {base} \
  .claude/reviews/codex-ab-$(date +%Y-%m-%d-%H%M)

Use run_in_background — it runs 1 holistic codex exec review + 3 focused codex exec workers (security / ecto / liveview) in parallel, all streams redirected. Do other work or wait; never poll.

Step 3: Classify

Read the 4 findings files (holistic.md, security.md, ecto.md, liveview.md — small). For EACH focused finding:

| Class | Meaning | Test | |-------|---------|------| | DUPLICATE | Holistic already found it | Same file + same defect | | REAL MISS | Genuine issue holistic missed | Read the code at file:line — defect confirmed (Iron Law 2) | | FALSE POSITIVE | Manufactured, pre-existing, or wrong | Code check fails, or issue exists on base branch too |

Step 4: Verdict

Present:

## Codex Panel A/B — {branch} vs {base}
| dimension | findings | duplicate | real miss | false positive |
Holistic-only findings: {n}
Verdict this run: {REAL MISS count} real miss vs {FP count} false positive
Decision rule: build --codex-panel only if real misses outnumber false
positives across 2-3 fresh branches.

Write the verdict table to .claude/reviews/codex-ab-{date}/VERDICT.md. Suggest repeating on the next 1–2 fresh branches before deciding.

Integration

fresh branch → /codex-ab (YOU ARE HERE) → verdict logged
   ├─ real misses win across runs → build /phx:review --codex-panel
   └─ duplicates/FPs win → keep holistic /phx:codex-loop, drop panel idea
       └─ OUTCOME 2026-07-10: this branch won — panel dropped

References

  • ${CLAUDE_SKILL_DIR}/scripts/codex-panel-ab.sh — the 4-run harness
  • Related: /phx:codex-loop (holistic fix loop), /phx:review --codex

Related Skills

View on GitHub
GitHub Stars560
CategorySecurity
Updated2d ago
Forks44

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions