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 witt3rd/oh-my-hermes --skill omh-ralph-drivergit clone --depth 1 https://github.com/witt3rd/oh-my-hermesWrote 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/witt3rd/oh-my-hermes/omh-ralph-driver)<a href="https://agentmods.dev/skills/witt3rd/oh-my-hermes/omh-ralph-driver"><img src="https://agentmods.dev/badge/skills/witt3rd/oh-my-hermes/omh-ralph-driver/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/witt3rd/oh-my-hermes/omh-ralph-driver"><img src="https://agentmods.dev/badge/skills/witt3rd/oh-my-hermes/omh-ralph-driver.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00022 | $0.06708 |
| Opus 5 | $0.00011 | $0.03354 |
| Sonnet 5 | $0.00004 | $0.01342 |
| Haiku 4.5 | $0.00002 | $0.00671 |
Grade C, and why
omh-ralph-driver scanned grade C with 1 finding 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 12d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- "Use `git rm -r` (not `rm -rf`) to preserve git history when How it starts
The opening of the file, as written. The whole thing — 645 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OMH Ralph Driver — orchestrator's playbook for verified execution
Load this skill alongside omh-ralph when you are the orchestrator
dispatching the loop. omh-ralph is loaded by the role-tagged
workers (executor / verifier / architect) — it covers the iron-law
discipline inside each task's delegate_task call. This skill covers
what you do as the dispatcher: plan-shape, iteration cadence,
parallel batching, evidence gathering, verifier dispatch, strike
handling, commit hygiene, and the final architect gate.
The two skills have different readers and different jobs. Don't merge them — worker context is precious; the dispatcher's playbook should not ride into every subagent.
This skill is the ralph-side counterpart to omh-ralplan-driver
(which is the dispatcher playbook for ralplan, the design loop). The
relationship is consistent: each method has a worker-side skill (used
inside delegate_task) and a driver-side skill (used by the orchestrator
between dispatches).
When to use ralph vs just write the code
Use ralph when:
- You have a plan with 5+ independently-acceptable tasks (from
omh-ralplanor hand-authored). - Quality-via-verification matters more than wall-clock — each task's output must be evidence-graded before the next builds on it.
- You want clean checkpoints across many work units (no context bloat).
- Some tasks are independent and can run in parallel batches.
Don't use ralph when:
- The work is single-step or trivially obvious to write directly.
- No plan exists yet — run
omh-ralplan(or for an obvious goal,omh-deep-interviewfirst) before invoking ralph. - The user wants to skip verification (unusual; usually means the work is small enough to do directly).
The arc of a ralph run
iter 1: pick eligible tasks → dispatch executors (parallel where safe)
→ gather evidence → dispatch verifiers (parallel) → mark passes/fails
→ update state → release lock → exit
iter 2: re-invoke. Read state. Pick next batch. Same cycle.
...
iter N: all tasks pass → Step 7 final architect review → mark complete.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 645 lines · 22 tokens per session scan C d1b59ae0992c
omh-ralph-driver is a skill published in the GitHub repository witt3rd/oh-my-hermes (321 stars, last pushed 1mo ago), licensed MIT. It adds 22 tokens to every session and 6,708 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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