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-application-threat-modelgit 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-application-threat-model)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-application-threat-model"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-application-threat-model/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-application-threat-model"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-application-threat-model.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 | $0.00080 | $0.02076 |
| Opus 5.5 | $0.00032 | $0.00830 |
| Sonnet 5.5 | $0.00016 | $0.00415 |
| Haiku 4.5 | $0.00008 | $0.00208 |
Grade A, and why
omh-application-threat-model 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Application Threat Model
This is an OMH application-threat-model workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
application-threat-model exists because the nearest neighbour does not merely miss this request. security-safety-review maps the agent's own prompt, tool, credential, and dependency surface, so an application threat-model request came back as an agent tool inventory under a near-identical name — a confident wrong artifact rather than a miss, in the one domain where that costs most.
Do Not Use When
- The subject is the agent's own prompts, tools, files, credentials, dependencies, or destructive actions; use
omh-security-safety-review, which maps that runtime surface. - The user wants defects found in a diff or a file; use
omh-code-review. - The user asks whether a release is ready across rollout, rollback, and observability; use
omh-production-audit. - The user asks which commands prove a merge is safe; use
omh-verification-gate. - The user asks for a contractual or regulatory obligation rather than an attacker; use
omh-legal-compliance-review.
Examples
Good example:
- Prompt: build a threat model for our payment service architecture
- Expected behavior: Prepare application_threat_model/v1: ask for the component map and data flows, register card data and settlement records as assets, mark the merchant API edge and the PSP callback as trust boundaries, derive scenarios per boundary, decide a control for each, and name the test that fails when the control is removed.
- Why: The subject is an application the user operates, and the goal needs assets, boundaries, scenarios, controls, and tests.
Bad example:
- Prompt: application-threat-model check whether this agent can be prompt-injected through its file tool
- Expected behavior: Route to
security-safety-review: prompts, tools, and credentials are the agent's runtime surface, not an application this workflow models. - Why: The two surfaces share vocabulary and nothing else; modeling the agent's runtime here is how the artifacts get confused.
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 e1e249b1407f
- 16d ago Changed · +3 lines 028a2bc9d658
- 21d ago Changed · +2 tokens per session 37ee56f4688e
- 23d ago Changed · +6 lines 5438e0bf5e21
- 1mo ago First seen · 133 lines · 78 tokens per session scan A 705162d7ce28
omh-application-threat-model is a skill published in the GitHub repository rlaope/oh-my-hermes (3,392 stars, last pushed today), licensed MIT. It adds 80 tokens to every session and 2,076 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 2026-09-16.
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