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 mrzhangguoguo/oh-my-workbuddy --skill ralphgit clone --depth 1 https://github.com/mrzhangguoguo/oh-my-workbuddyWrote 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/mrzhangguoguo/oh-my-workbuddy/ralph)<a href="https://agentmods.dev/skills/mrzhangguoguo/oh-my-workbuddy/ralph"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/ralph/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/mrzhangguoguo/oh-my-workbuddy/ralph"><img src="https://agentmods.dev/badge/skills/mrzhangguoguo/oh-my-workbuddy/ralph.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 | $0.00069 | $0.02027 |
| Opus 5 | $0.00034 | $0.01014 |
| Sonnet 5 | $0.00014 | $0.00405 |
| Haiku 4.5 | $0.00007 | $0.00203 |
Grade A, and why
ralph scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ported from oh-my-codex
ralph. OMX runtime conventions ($macroinvocation,omxCLI,.omx/state directory) are replaced with WorkBuddy idioms (Skill tool, Agent tool, task list,.workbuddy/memory).
Ralph
Ralph is a persistence loop that keeps working on a task until it is fully complete and architect-verified. It wraps parallel execution with session persistence, automatic retry on failure, and mandatory verification before completion.
Use When
- Task requires guaranteed completion with verification (not just "do your best").
- User says "ralph", "don't stop", "must complete", "finish this", "keep going until done".
- Work may span multiple iterations and needs persistence across retries.
- Task benefits from parallel execution with architect sign-off at the end.
Do Not Use When
- User wants a full autonomous pipeline from idea to code — use the pipeline/autopilot path.
- User wants to explore or plan first — use
plan. - User wants a quick one-shot fix — delegate directly to an executor Agent.
- User wants manual control over completion — execute directly.
Why This Exists
Complex tasks fail silently: partial implementations declared "done", tests skipped, edge cases forgotten. Ralph prevents this by looping until work is genuinely complete, requiring fresh verification evidence before completion, and using an explicit architect Agent verification to confirm quality.
Execution Policy
- Fire independent Agent calls simultaneously — never wait sequentially for independent work.
- Use
run_in_background: truefor long operations (installs, builds, test suites). - Preserve legacy Ralph tier intent through model selection if available: LOW → light model, STANDARD → default, THOROUGH → strongest available model. (WorkBuddy model routing is environment-dependent; only apply when a lighter/heavier model is selectable.)
- Deliver the full implementation: no scope reduction, no partial completion, no deleting tests to make them pass.
- Apply the shared workflow guidance pattern: outcome-first framing, concise visible updates, local overrides, validation proportional to risk, explicit stop rules, automatic continuation for safe reversible steps. Ask only for material, destructive, credentialed, external-production, or preference-dependent branches.
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.
- 11d ago First seen · 115 lines · 69 tokens per session scan A ce626a7190b2
ralph is a skill published in the GitHub repository mrzhangguoguo/oh-my-workbuddy (2 stars, last pushed 2mo ago), licensed MIT. It adds 69 tokens to every session and 2,027 once invoked, about $0.0003 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 2026-08-31.
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