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-finance-analysisgit 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-finance-analysis)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-finance-analysis"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-finance-analysis/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-finance-analysis"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-finance-analysis.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 | $0.00072 | $0.01258 |
| Opus 5.5 | $0.00029 | $0.00503 |
| Sonnet 5.5 | $0.00014 | $0.00252 |
| Haiku 4.5 | $0.00007 | $0.00126 |
Grade A, and why
omh-finance-analysis 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 5d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Finance Analysis
This is an OMH finance-analysis workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
finance-analysis prepares a source-bounded decision brief without claiming an authoritative financial action.
Do Not Use When
- The request is for a current quote, exchange rate, crypto price, or other live market lookup; use
omh-live-info. - The user wants generic exploration of a supplied CSV or table without accounting periods, controls, or finance decision framing; use
omh-data-analysis. - The user asks to post journal entries, reconcile accounts, approve payments, submit tax filings, or configure an accounting system; use
omh-appsfor an explicit observed action path. - The user wants pipeline coverage, deal health, or a seller forecast scenario rather than authoritative revenue or close reporting; use
omh-sales-pipeline-review. - The user needs an enterprise or product direction decision after analysis; route that decision to
omh-decide. - The ask is testing whether an internal control operated -- a SOX or ICFR sample, re-performance, or a deficiency's severity; use
omh-internal-audit.
Examples
Good example:
- Prompt: Compare Q2 actuals against budget, explain the biggest expense variances, and flag cash risks for the CFO.
- Expected behavior: Prepare the period boundary, actual-versus-plan narrative, cash-risk register, and decision questions.
- Why: The supplied finance framing needs a bounded decision brief rather than an external accounting action.
Bad example:
- Prompt: What is the USD/KRW exchange rate right now?
- Expected behavior: Route to
live-info-operator, notfinance-analysis. - Why: A live exchange rate needs observed provider data rather than a finance analysis brief.
Completion Checklist
- Confirm the workflow target, evidence boundary, and stop condition are named.
- Report which outputs are prepared, observed, blocked, or missing.
- Name the smallest next verification or handoff instead of claiming completion from narration.
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.
- 5d ago Changed · +1 lines 271ffc90f404
- 14d ago Changed · +1 lines 40474d40a2a7
- 27d ago Changed · +3 lines 7a2cb00ccd91
- 29d ago Changed · +1 lines 56febf9a42a8
- 1mo ago Changed · +1 tokens per session 06f50091bb43
- 1mo ago Changed · +11 tokens per session 7b452ed57832
- 1mo ago Changed · +6 lines 5b51542aabaf
- 1mo ago Changed · -11 lines 03a72fe91f34
- 1mo ago Changed · +1 lines 5862bb46fc5e
- 1mo ago First seen · 128 lines · 60 tokens per session scan A 834127c4aa5b
omh-finance-analysis is a skill published in the GitHub repository rlaope/oh-my-hermes (4,366 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 1,258 once invoked, about $0.0003 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 2026-08-30.
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