Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Shell out to OpenAI Codex CLI for headless code generation, analysis, and question-answering. Optimized for code tasks. Requires OPENAI_API_KEY env var.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Headless wrapper for OpenAI Codex CLI. Passes prompt as positional arg to codex exec "PROMPT".
Optimized for code generation and analysis. Requires OPENAI_API_KEY.
node .claude/skills/omega-codex-cli/scripts/ask-codex.mjs "Implement a Redis caching layer for Express"
node .claude/skills/omega-codex-cli/scripts/ask-codex.mjs "Refactor this module" --timeout-ms 120000
node .claude/skills/omega-codex-cli/scripts/ask-codex.mjs "Generate unit tests" --json
node .claude/skills/omega-codex-cli/scripts/ask-codex.mjs "Write and test a sort algorithm" --sandbox
node .claude/skills/omega-codex-cli/scripts/verify-setup.mjs
# Exit 0 = available (CLI found + OPENAI_API_KEY set)
# Exit 1 = not available
| Script | Purpose |
|---|---|
ask-codex.mjs | Core headless wrapper — prompt as positional arg |
parse-args.mjs | Argument parser (--model, --json, --sandbox, --timeout-ms) |
verify-setup.mjs | Availability check (CLI + OPENAI_API_KEY) |
format-output.mjs | JSONL event stream normalization |
| Model ID | Description | When to Use |
|---|---|---|
codex-mini-latest | Default. Fine-tuned o4-mini. Low-latency code Q&A. $1.50/$6 per 1M. | Fast code questions, CI pipelines, high-volume calls |
gpt-5.4 | Full GPT-5.4 (released ~2026-03-05). 1M context, computer-use, top coding perf. | Complex multi-file tasks, computer-use agentic flows |
gpt-5.4-pro | Pro variant of GPT-5.4. Higher capacity, higher cost. | State-of-the-art coding benchmarks, research tasks |
Default model: codex-mini-latest — fine-tuned o4-mini optimized for low-latency code Q&A with a 75% caching discount. Do not override unless you need GPT-5.4's extended context or computer-use capability.
To use GPT-5.4:
node .claude/skills/omega-codex-cli/scripts/ask-codex.mjs "PROMPT" --model gpt-5.4
Pricing (codex-mini-latest): $1.50/1M input tokens · $6/1M output tokens · 75% caching discount
| Flag | Description |
|---|---|
--model MODEL | Override model (default: codex-mini-latest). Use gpt-5.4 or gpt-5.4-pro for GPT-5.4. |
--json | JSONL event stream output |
--sandbox | Workspace-write sandbox mode |
--timeout-ms N | Timeout in milliseconds (exit code 124 on expiry) |
| Code | Meaning |
|---|---|
| 0 | Success |
| 1 | Error (CLI failure, auth issue, API error) |
| 124 | Timeout (--timeout-ms exceeded) |
OPENAI_API_KEY env var requiredBefore starting:
Read .claude/context/memory/learnings.md
After completing:
.claude/context/memory/learnings.md.claude/context/memory/issues.md.claude/context/memory/decisions.mdASSUME INTERRUPTION: If it's not in memory, it didn't happen.
Note: Use pnpm search:code to discover references to this skill codebase-wide.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
日本語の概要は準備中です。原文の説明を表示しています。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
日本語の概要は準備中です。原文の説明を表示しています。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
日本語の概要は準備中です。原文の説明を表示しています。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
日本語の概要は準備中です。原文の説明を表示しています。