oh-my-hermes is an operating layer for Hermes Agent that organizes requests into workflows for planning, research, creation, coding handoffs, operations, and project memory. Hermes users run these workflows through the desktop app, CLI, or messenger app, while the catalogue add-ons extend its native capabilities.
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 rlaope/oh-my-hermes --skill omh-decision-prototypegit clone --depth 1 https://github.com/rlaope/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/rlaope/oh-my-hermes/omh-decision-prototype)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-decision-prototype"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-decision-prototype/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/rlaope/oh-my-hermes/omh-decision-prototype"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-decision-prototype.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 | $0.00079 | $0.00388 |
| Opus 5 | $0.00039 | $0.00194 |
| Sonnet 5 | $0.00016 | $0.00078 |
| Haiku 4.5 | $0.00008 | $0.00039 |
Grade A, and why
omh-decision-prototype 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 4d 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.
What it actually says
Decision Prototype
Required: one decision, a bounded experiment, an isolated scratch boundary, and a measurement method. Output: a decision record, prepared handoff, observation ledger, and receipt.
HOLD: Missing inputs or failed contract gates. Prepared OMH routing is not execution or approval. Completion: Follow the full-contract checklist.
Shared product, routing, compatibility, and evidence rules: omh-routing/references/skill-common-rail.md.
Agent/operator: omh runtime workflow-artifact decision-prototype prepare --input <json-file-or-> prepares bounded metadata only. Shared operator reference: omh-routing/references/workflow-artifacts.md.
Contract: references/full-contract.md. Procedure: references/procedure.md.
Completion Checklist
- Preserve workflow intent and stop conditions; load the full contract before claiming completion.
- Record observed delegation results; otherwise return
not_availableornot_observed. - Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.
Recovery Notes
- If a required input, authority, or runtime capability is unavailable, HOLD and name the smallest safe next action; do not invent observation or approval.
Workflow Lane
advisory local context
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.
- 4d ago First seen · 38 lines · 79 tokens per session scan A 2d3673964dd4
omh-decision-prototype is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 388 once invoked, about $0.0004 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 2026-09-08.
Other skills, from other repositories
story-long-analyze
A structured process for deeply analysing a long online novel, starting with its opening three chapters and continuing chapter by chapter.
story-review
A review process for finding problems in a novel’s structure, characters, wording, and world rules. It can use several reviewers or one reviewer when others are unavailable.
moxiangtongxiu-perspective
A Chinese-language creative-writing guide built around character-led stories, interwoven plotlines, memorable dialogue, ensemble casts, and emotional contrasts. It is presented as a perspective associated with the author Mo Xiang Tong Xiu.
tiancantudou-perspective
A creative-writing guide based on the storytelling patterns associated with Chinese web novelist Tiancan Tudou. It focuses on stories where an underestimated character grows stronger through challenges and moves into new settings.
tianya-gods-team
A decision-making system in which 20 fictional specialist viewpoints analyze one question in parallel before a coordinating AI combines them. It covers areas such as history, economics, relationships, technology, mysteries, and culture.
lijigang-skill
A Chinese-language approach to writing precise, highly structured prompts, sometimes using Lisp-like notation. It combines concise wording, philosophical questioning, and a process for defining roles, conditions, output formats, and revisions.