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-relational-dbgit 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-relational-db)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-relational-db"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-relational-db/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-relational-db"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-relational-db.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 | $0.00100 | $0.01934 |
| Opus 5.5 | $0.00040 | $0.00774 |
| Sonnet 5.5 | $0.00020 | $0.00387 |
| Haiku 4.5 | $0.00010 | $0.00193 |
Grade A, and why
omh-relational-db 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 3d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Relational Db
This is an OMH relational-db workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
relational-db exists because the database work itself had no owner: backend owns schema_migration_plan/v1 for a service change, and an index question, a lock taken during deploy, or an N+1 finding was answered by a data, deploy, or interview lane with no lock model at all.
First Steps
- Ask for the engine, the version, and the table sizes before proposing any statement.
- For a migration, give every step its lock behaviour and its rollback before calling the plan ready.
Do Not Use When
- The request is a service or API change whose storage part is one section of the contract; use
omh-backend, which owns schema_migration_plan/v1. - The request is an end-to-end performance goal across the whole system rather than one database; use
ulw-perf. - The request is analysis of the data itself -- trends, metrics, a report; use
omh-data-analysis. - The request is watching a release roll out with its health signals and rollback criteria; use
omh-deploy-and-monitor.
Examples
Good example:
- Prompt: write an online migration for a 200M row table
- Expected behavior: Ask for the engine and version, then prepare online_migration_plan/v1: expand, batched backfill, switch, and contract, each step with the lock it takes, its
lock_timeout, and its rollback, and a readiness verdict. - Why: At 200M rows the lock each statement takes decides whether the deploy is an outage.
Bad example:
- Prompt: just add the index, it will be fine
- Expected behavior: Size the index, cite the plan it changes, build it with the non-blocking method, and name what is unverified.
- Why: An index built with a blocking statement on a large table locks writes for the whole build.
Completion Checklist
- Engine, version, and table sizes are stated.
- Every proposed index cites an observed plan or is marked unverified.
- Every migration step states its lock mode, its duration bound, and its rollback.
- The readiness verdict is ready only when no step lacks lock behaviour or rollback.
- Nothing was connected to, run, or applied by OMH.
What ships with it
1 file 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.
- 3d ago Changed · +1 lines fac22f8aa8e0
- 16d ago Changed · +3 lines cadf67ded0fc
- 19d ago First seen · 137 lines · 100 tokens per session scan A 7362d2fae8e4
omh-relational-db is a skill published in the GitHub repository rlaope/oh-my-hermes (3,392 stars, last pushed today), licensed MIT. It adds 100 tokens to every session and 1,934 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-28.
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