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-native-debugginggit 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-native-debugging)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-native-debugging"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-native-debugging/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-native-debugging"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-native-debugging.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 | $0.00068 | $0.01988 |
| Opus 5.5 | $0.00027 | $0.00795 |
| Sonnet 5.5 | $0.00014 | $0.00398 |
| Haiku 4.5 | $0.00007 | $0.00199 |
Grade A, and why
omh-native-debugging 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Native Debugging
This is an OMH native-debugging workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
Why This Exists
native-debugging closes OMH's zero-coverage low-level domain by preparing a hypothesis-driven, DAP-first debugging plan for native binaries, while OMH itself continues to execute nothing.
Do Not Use When
- The failure is a build or CI failure rather than a runtime fault in a binary; use
omh-build-failure-triage. - The subject is an agent or workflow misbehaving rather than a native binary; use
omh-agent-debug. - The wrong result, flaky test, or lost update is in application code such as a Python or TypeScript service and needs its root cause reproduced; use
omh-app-debugging. - The change is Rust source work whose risk is
unsafeor UB discipline; useomh-rust. - The request is to judge whether a fix is verified rather than to find the fault; use
omh-verification-gate.
Examples
Good example:
- Prompt: This binary segfaults on the third request; help me debug it.
- Expected behavior: Prepare native_fault_statement/v1, three competing hypotheses with distinguishing observations, and a debugger_session_plan/v1 naming the DAP adapter, breakpoints, and values to read.
- Why: The request is a runtime fault in a native binary where the plan, not the guess, is what OMH can prepare.
Bad example:
- Prompt: Add some printfs and tell me it is fixed once the crash stops.
- Expected behavior: Name the DAP-driven observation plan, and keep reproduction, root cause, and fix as separate not_observed states.
- Why: A disappearing symptom is not a root cause, and printf-via-rebuild is the fallback rather than the method.
Completion Checklist
- The fault is stated as an observed symptom with a reproduction command, separate from any assumed cause.
- At least three hypotheses span distinct axes and each carries its refuting observation.
- The debugger session plan names the DAP adapter, breakpoints, watchpoints, threads, frames, and values to read.
- The handoff says the executor drives the debugger and OMH executes nothing.
- Reproduction, debugger output, root cause, and fix are reported as separate observed or not_observed states.
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 de811334a500
- 6d ago Changed 586037dabdb8
- 8d ago Changed 2f3427a3f540
- 14d ago Changed · +1 lines 8aa8443cfa22
- 27d ago Changed · +3 lines 9653ffeaf097
- 1mo ago Changed · +1 lines 97820a1a3394
- 1mo ago Changed · +2 tokens per session 010086d08f7b
- 1mo ago Changed · +6 lines 3c4e71bc5956
- 1mo ago Changed · -11 lines 7b14d5ac7290
- 1mo ago First seen · 140 lines · 66 tokens per session scan A 109ebcb5eab8
omh-native-debugging is a skill published in the GitHub repository rlaope/oh-my-hermes (4,366 stars, last pushed today), licensed MIT. It adds 68 tokens to every session and 1,988 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 2026-09-03.
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