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-agent-debuggit 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-agent-debug)<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-agent-debug"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-agent-debug/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-agent-debug"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-agent-debug.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 | $0.00071 | $0.01453 |
| Opus 5 | $0.00036 | $0.00727 |
| Sonnet 5 | $0.00014 | $0.00291 |
| Haiku 4.5 | $0.00007 | $0.00145 |
Grade A, and why
omh-agent-debug 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Debug
This is a Hermes-native agent-debug workflow skill.
Why This Exists
agent-debug exists so Hermes users can ask for this workflow in chat and receive a structured, evidence-bounded OMH operating surface instead of ad hoc narration.
Do Not Use When
- The request is already handled by a narrower explicit skill with stronger evidence.
- The user asks OMH to secretly run external platforms, connectors, schedulers, file exports, or runtime agents.
- The only safe answer is to ask for missing authority, credentials, target, or observed evidence first.
Examples
Good example:
- Prompt: agent-debug capture why this agent is looping on the same tool and prepare the smallest safe recovery action.
- Expected behavior: Produce
prepare_agent_debugwith required context, wrapper actions, and not-evidence boundaries. - Why: The prompt names a real workflow surface that Hermes can orchestrate without hiding execution.
Bad example:
- Prompt: agent-debug silently reset the executor, patch the environment, and claim the future loop is fixed.
- Expected behavior: Report the missing observed evidence or authority instead of claiming the external step happened.
- Why: Prepared OMH guidance is not platform, runtime, connector, file, memory, or delivery evidence.
Completion Checklist
- Failure state, intended goal, recent tool sequence, and context pressure are captured.
- Diagnosis distinguishes repeated command/tool loops, context drift, environment mismatch, service errors, and wrong-hypothesis tests.
- Recovery action is contained, reversible, and does not claim implementation, verification, CI, merge, or future-loop fixes.
Recovery Notes
- If the request is install/setup health, route to doctor.
- If the request is a manager status or throughput review, route to agent-ops-review.
- If the request is a durable self-improvement record after diagnosis, route to workflow-learning.
Workflow Lane
- Current lane: Automation and status (
achievements,workspace-audit,production-audit,automation-blueprint,github-event-ops,github-issue-intake,buzz,agent-board,+35 more) - schedules, status, health, and ops review. - If intent belongs to another lane, hand back to
oh-my-hermesor name the adjacent workflow. - Shared product, routing, compatibility, and evidence rules:
omh-routing/references/skill-common-rail.md.
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 27c808fc91bb
- 10d ago First seen · 129 lines · 71 tokens per session scan A 56e1c3836dfc
omh-agent-debug is a skill published in the GitHub repository rlaope/oh-my-hermes (1,605 stars, last pushed today), licensed MIT. It adds 71 tokens to every session and 1,453 once invoked, about $0.0004 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.
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