oh-my-codex is a workflow layer for OpenAI Codex CLI that adds prompts, agent teams, skills, hooks, HUDs, and other runtime assistance while leaving Codex as the execution engine. It is for people who use Codex CLI and want structured workflows and additional help as tasks become larger. The catalogue entries are its skills, hooks, and MCP integrations for those Codex workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Yeachan-Heo/oh-my-codex --skill autoresearchgit clone --depth 1 https://github.com/Yeachan-Heo/oh-my-codexWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yeachan-heo/oh-my-codex/autoresearch)<a href="https://agentmods.dev/skills/yeachan-heo/oh-my-codex/autoresearch"><img src="https://agentmods.dev/badge/skills/yeachan-heo/oh-my-codex/autoresearch/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yeachan-heo/oh-my-codex/autoresearch"><img src="https://agentmods.dev/badge/skills/yeachan-heo/oh-my-codex/autoresearch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00014 | $0.00689 |
| Opus 5 | $0.00007 | $0.00345 |
| Sonnet 5 | $0.00003 | $0.00138 |
| Haiku 4.5 | $0.00001 | $0.00069 |
Grade A, and why
autoresearch scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- autoresearch — 98% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autoresearch
Autoresearch is the skill-first replacement for the deprecated omx autoresearch command.
It keeps the useful measured-research loop, but it now runs as a native-hook stateful workflow instead of a direct CLI or tmux launch surface.
Boundary with planning research
Use $autoresearch when the research output itself is a bounded deliverable that must pass an explicit validator. Do not recommend it for ordinary pre-planning docs lookup or general best-practice checks; use $best-practice-research for that. If $autoresearch is intentionally run before architecture planning, its approved artifact should feed evidence into $ralplan; it should not become a final architecture/component unless the user explicitly asks for ongoing research automation.
Use when
- You want a Ralph-ish persistent research loop
- The task should keep nudging until explicit validation evidence exists
- You want init-time choice between script validation and prompt+architect validation
Do not use when
- You want the old
omx autoresearchcommand surface (hard-deprecated) - You want detached tmux or split-pane launch parity
- You have not decided the validation regime yet
Core contract
- Init chooses validation mode. Pick exactly one:
mission-validator-scriptprompt-architect-artifact
- Persist mode state in
.omx/state/.../autoresearch-state.jsonincluding:validation_modecompletion_artifact_pathmission_validator_commandorvalidator_prompt- optional
output_artifact_path
- Completion is artifact-gated. The loop does not stop because the model says “done”, because a stop hook fired once, or because several turns were no-ops.
- Direct CLI launch is gone. Use
$deep-interview --autoresearchfor intake and$autoresearchfor execution.
Completion artifact contract
mission-validator-script
The completion artifact must exist and record a passing validator result, for example:
{
"status": "passed",
"passed": true,
"summary": "metric improved beyond baseline"
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 73 lines · 14 tokens per session scan A 5620155f3122
autoresearch is a skill published in the GitHub repository Yeachan-Heo/oh-my-codex (33,102 stars, last pushed yesterday), licensed MIT. It adds 14 tokens to every session and 689 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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