1328 hand-tested AI prompts across image, video, and music — each with full context, variables, and a sample output. Content is authored in Traditional Chinese; the UI here is English.
A ready-to-paste ~/.codex/config.toml template that sets up OpenAI Codex CLI's approval policy, sandbox isolation, reasoning effort, and multiple profiles in one go — balancing automation efficiency with safety boundaries.
A breakdown of the AGENTS.md actually in use in OpenAI's official codex repository — see how a project with millions of lines of code writes team conventions like formatting, testing, commits, module size limits, and API naming into an instruction file that an AI agent can understand and follow, plus a Traditional Chinese adaptation template you can apply directly to your own project.
Uses VoltAgent/awesome-codex-subagents (166+ subagents, 13 categories, MIT license) as a Codex-equivalent curated directory, teaching you to define subagents in .toml format under ~/.codex/agents/ and invoke Codex subagents explicitly.
Turns a vague requirement into a full Codex workflow: first force it to nail down a 'definition of done,' use plan mode to produce a plan for your approval, then implement in small steps, run its own tests, and finally produce a reviewable diff with verification evidence.
Once your code changes are done, have Codex read the staged diff, produce a Conventional Commits message, and write a PR description covering background, what changed, why, how it was verified, and risks — without bundling in unrelated changes, exaggerating, or fabricating tests.
Has Codex do a disciplined code review of your git diff across three tracks (correctness bugs / simplification-and-reuse / security), listing each finding with a confidence level and a pastable fix, and explicitly instructed to say so when nothing's wrong instead of manufacturing complaints.
Forces Codex through a closed loop — write a failing test that reproduces the bug, find the root cause, make the minimal fix, watch that same test go from red to green, then run the full test suite to confirm no regressions — eliminating both 'fixed it without verifying' and 'changed a bunch of unrelated stuff along the way.'
Has Codex write characterization tests for untested legacy code: it first reads and documents what the code 'actually does right now' (bugs included), systematically covers the happy path plus edge cases and error paths, and is strictly forbidden from modifying the code under test.
Has the agent automatically inventory your Cursor project (.cursorrules, .cursor/rules, .cursor/mcp.json), produce a step-by-step migration plan, and generate the corresponding CLAUDE.md or AGENTS.md, slash commands, and MCP config — so you're not stuck 'dumber than Cursor' on day one.
A Definition of Done template you can paste into any coding agent, turning 'what counts as done' into a checklist the agent must self-verify item by item: behavior meets acceptance criteria, tests/lint/typecheck/build all pass (or it states why they didn't run), risky changes come with a rollback plan, and a final 'verification story' is delivered. Puts an end to agents claiming 'done' while everything is actually broken.