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-doctorgit 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-doctor)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-doctor"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-doctor/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-doctor"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-doctor.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 | $0.00033 | $0.00954 |
| Opus 5 | $0.00016 | $0.00477 |
| Sonnet 5 | $0.00007 | $0.00191 |
| Haiku 4.5 | $0.00003 | $0.00095 |
Grade A, and why
omh-doctor 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 7d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Doctor
This is a Hermes-native doctor workflow skill.
Why This Exists
doctor exists to turn confusing install/setup states into grouped, local health evidence and the next repair action without treating a check as a fix.
Do Not Use When
- The user is asking for a general product explanation rather than local health diagnostics.
- The requested change is a repository bug fix, not an installed-environment check.
- The wrapper wants to claim Hermes reload, skill execution, or plugin behavior that was not observed.
Examples
Good example:
- Prompt: doctor after omh update says setup is next but Hermes skills still look stale.
- Expected behavior: Inspect managed skills, Hermes registration, runtime state, and next repair action with explicit proof boundaries.
- Why: The issue is local installation health and needs grouped diagnostic evidence.
Bad example:
- Prompt: doctor implement a new uninstall command UX.
- Expected behavior: Route to planning or implementation instead of health diagnostics.
- Why: That is product development work, not a local health check.
Completion Checklist
- Command availability, managed skills, Hermes registration, runtime state, and optional surfaces are grouped separately.
- Blocking issues and warnings are separated, with one next repair action named for each blocking area.
- Plugin install, plugin import/register smoke, and Hermes runtime load are not collapsed into one claim.
- The final status says whether setup/update/doctor repaired anything or only observed health.
Recovery Notes
- If managed skills are stale, recommend omh update or omh setup depending on whether registration also needs repair.
- If skills.external_dirs or Hermes config is missing, route to setup repair rather than editing hidden runtime state.
- If plugin register smoke fails, reinstall the plugin bundle with setup --with-plugin --force before claiming plugin readiness.
- If omh is missing from PATH, use the installer-reported absolute command path and then re-run doctor.
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.
- 7d ago Changed 095b96288adf
- 13d ago First seen · 121 lines · 33 tokens per session scan A 8b724be41faa
omh-doctor is a skill published in the GitHub repository rlaope/oh-my-hermes (1,677 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 954 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
kubernetes-specialist
Use when managing Kubernetes clusters, debugging Pods and workloads, designing Helm charts, reviewing manifests, or improving deployment, scaling, and observability practices.
python-performance
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
fable-recover
Diagnose repeated command failures, stale build caches, branch drift, or contradictory evidence before attempting further code edits. Use when commands fail repeatedly, tests stay red after attempted fixes, build output contradicts source code, or the execution path is confused — even if the user does not explicitly…
cloudflare-troubleshooting
Diagnose Cloudflare DNS, TLS, redirects, and configuration issues using live API settings and request evidence.
debug
Use when diagnosing software errors, test failures, or unexpected runtime behavior.
doubt-driven-development
Review high-risk or uncertain engineering decisions adversarially when independent verification can expose costly assumptions before implementation.