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-ralplangit 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-ralplan)<a href="https://agentmods.dev/skills/witt3rd/oh-my-hermes/omh-ralplan"><img src="https://agentmods.dev/badge/skills/witt3rd/oh-my-hermes/omh-ralplan/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-ralplan"><img src="https://agentmods.dev/badge/skills/witt3rd/oh-my-hermes/omh-ralplan.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 | $0.00021 | $0.01699 |
| Opus 5 | $0.00010 | $0.00849 |
| Sonnet 5 | $0.00004 | $0.00340 |
| Haiku 4.5 | $0.00002 | $0.00170 |
Grade A, and why
omh-ralplan 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OMH Ralplan — Consensus Planning
When to Use
- Before implementing any feature that touches multiple files or components
- When architectural decisions need validation from multiple perspectives
- When you need a plan that's been stress-tested against adversarial critique
- When the user says: "plan this", "consensus plan", "ralplan", "let's think this through"
When NOT to Use
- Trivial single-file changes (just do them)
- Tasks where the approach is obvious and low-risk
- When the user explicitly wants to skip planning
Prerequisites
- A clear goal or specification (if ambiguous, use
omh-deep-interviewfirst) - The
delegate_tasktool must be available
Procedure
Phase 0: Context Gathering
Before planning, gather project context:
- Read relevant files to understand the codebase structure
- Identify existing patterns, conventions, and constraints
- Summarize context into a brief (~500 words) that all agents will receive
Phase 1: Planning Loop (max 3 rounds)
Round 1 — All Sequential (Planner → Architect → Critic):
Step 1 — Planner (single delegate_task)
delegate_task(
goal="[omh-role:planner] Create an implementation plan for: {goal}\n\n{detailed_requirements}",
context="# Project Context\n\n{project_context}"
)
The goal should include the full specification — don't assume the subagent knows anything.
Step 2 — Architect Review (single delegate_task)
delegate_task(
goal="[omh-role:architect] Review this implementation plan for architectural soundness:\n\nPLAN:\n{planner_output}",
context="# Project Context\n\n{project_context}"
)
Step 3 — Critic Challenge (single delegate_task)
delegate_task(
goal="[omh-role:critic] Critically challenge this plan and architect review:\n\nPLAN SUMMARY:\n{plan_summary}\n\nARCHITECT REVIEW:\n{architect_verdict_and_concerns}",
context="# Project Context\n\n{project_context}"
)
Step 4 — Consensus Check Check all three verdicts:
- If ALL three are APPROVE → consensus reached, proceed to output
- If any is REQUEST_CHANGES → collect all feedback, proceed to Round 2
- If any is REJECT → output concerns and ask user whether to continue
What ships with it
2 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.
- 11d ago First seen · 146 lines · 21 tokens per session scan A 23dc404d2bd4
omh-ralplan is a skill published in the GitHub repository witt3rd/oh-my-hermes (322 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 1,699 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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