Use OpenAI Codex CLI as a read-only oracle — planning, review, and analysis only. Codex provides its perspective; you synthesize and present results to the user.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionoracle-codexExecute the skills CLI command in your project's root directory to begin installation:
Fetches oracle-codex from paulrberg/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate oracle-codex. Access via /oracle-codex in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Use OpenAI Codex CLI as a read-only oracle — planning, review, and analysis only. Codex provides its perspective; you synthesize and present results to the user.
Sandbox is always read-only. Codex must never implement changes.
Parse $ARGUMENTS for:
--reasoning <level> — override reasoning effort (low, medium, high, xhigh). Optional; default is auto-selected based on complexity.Run the check script before any Codex invocation:
scripts/check-codex.sh
If it exits non-zero, display the error and stop. Use the wrapper for all codex exec calls:
scripts/run-codex-exec.sh
| Setting | Default | Override |
|---|---|---|
| Model | gpt-5.3-codex |
Allowlist only (see references/codex-flags.md) |
| Reasoning | Auto | --reasoning <level> or user prose |
| Sandbox | read-only |
Not overridable |
| Complexity | Effort | Timeout | Criteria |
|---|---|---|---|
| Simple | low |
300000ms | <3 files, quick question |
| Moderate | medium |
300000ms | 3–10 files, focused analysis |
| Complex | high |
600000ms | Multi-module, architectural thinking |
| Maximum | xhigh |
600000ms | Full codebase, critical decisions |
For xhigh tasks that may exceed 10 minutes, use run_in_background: true on the Bash tool and set CODEX_OUTPUT so you can read the output later.
See references/codex-flags.md for full flag documentation.
$ARGUMENTS for query and --reasoningscripts/check-codex.sh — abort on failureBuild a focused prompt from the user's query and any relevant context (diffs, file contents, prior conversation). Keep it direct — state what you want Codex to analyze and what kind of output you need. Do not implement; request analysis and recommendations only.
Invoke via the wrapper with HEREDOC. Set the Bash tool timeout per the reasoning effort table above.
EFFORT="<effort>" \
CODEX_OUTPUT="/tmp/codex-${RANDOM}${RANDOM}.txt" \
scripts/run-codex-exec.sh <<'EOF'
[constructed prompt]
EOF
For xhigh, consider run_in_background: true on the Bash tool call, then read CODEX_OUTPUT when done.
Read the output file and present with attribution:
## Codex Analysis
[Codex output — summarize if >200 lines]
---
Model: gpt-5.3-codex | Reasoning: [effort level]
Synthesize key insights and actionable items for the user.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Useful defaults in oracle-codex — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for oracle-codex matched our evaluation — installs cleanly and behaves as described in the markdown.
oracle-codex has been reliable in day-to-day use. Documentation quality is above average for community skills.
oracle-codex has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend oracle-codex for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for oracle-codex matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: oracle-codex is the kind of skill you can hand to a new teammate without a long onboarding doc.
oracle-codex fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added oracle-codex from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
oracle-codex reduced setup friction for our internal harness; good balance of opinion and flexibility.
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