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Omh Production Audit

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rlaope
omh-production-audit

[omh] Imminent production launch or release: evaluate release, deploy, security, observability, rollback, docs, and support readiness without claiming production access. Use when the user says: production-audit, production audit, production readiness, prod audit, prod readiness, ready for production, ready to ship, ship readiness.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-production-audit
Stars
3.6K
Forks
269
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rlaope on GitHub. Read the source before you install it.

Installation

Install the Omh Production Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-production-audit
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rlaope/oh-my-hermes.git /tmp/oh-my-hermes
mkdir -p .claude/skills
cp -r /tmp/oh-my-hermes/agent-skills/omh-production-audit .claude/skills/omh-production-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Production Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Omh Production Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Omh Production Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Production Audit

This is an OMH production-audit workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

Why This Exists

production-audit gives OMH a preflight release surface so operators can see production risks before launch while OMH stays out of deploy and infrastructure execution.

Do Not Use When

  • The user wants to implement a feature or fix; prepare a coding handoff first.
  • The user wants incident/SLO analysis after production behavior; use omh-reliability-review.
  • The user wants a narrow code diff review; use omh-code-review.

Examples

Good example:

  • Prompt: production-audit 이 릴리즈가 운영에 나가도 되는지 테스트, CI, 롤백, 모니터링 기준으로 봐줘.
  • Expected behavior: Prepare readiness_matrix/v1, release_gate_verdict/v1, rollback_and_monitoring_plan/v1, and missing-evidence list.
  • Why: The request is release-readiness review, not implementation or deploy execution.

Bad example:

  • Prompt: production-audit 지금 바로 prod 배포하고 정상이라고 말해줘.
  • Expected behavior: Block deploy/health claims without observed operator evidence and route deploy to an explicit authorized workflow.
  • Why: Production audit can assess readiness, but it cannot secretly deploy or observe live health.

Completion Checklist

  • Findings or no-issue results are grounded in concrete file, artifact, command, or source evidence.
  • Open questions, residual risk, and missing verification are named.
  • Fixes or follow-up work are separate handoffs unless the user explicitly asked to implement them.

Recovery Notes

  • If the reviewed target is missing, inspect the requested artifact or ask one target question.
  • If independent verification is unavailable, report the gap and avoid an approval-style claim.

When to Use

Use before launch, deploy, release, or public delivery when Hermes should check operational readiness and expose missing production evidence.

Strong routing signals: `production-audit`, `production audit`, `production readiness`, `prod audit`, `prod readiness`, `ready for production`, `ready to ship`, `ship readiness`, `release readiness`, `launch readiness`, `preflight audit`, `operational readiness`, `rollback readiness`, `프로덕션 준비`, `출시 준비`, `운영 준비`, `릴리즈 준비`, `롤백 준비`

Catalog Metadata

Category: review Phase: production-readiness Quality tier: production-readiness-gated Reasoning demand: standard

Quality bar:

  • Name scope, environment, release channel, owners, and acceptable risk threshold.
  • Check build/test/CI, security/privacy, performance, observability, rollback, docs/support, and release communication.
  • Return GO, HOLD, or BLOCK only with evidence IDs and missing evidence.
  • Convert remediation into explicit follow-up workflows instead of silently patching.

Required inputs:

  • product, service, release, or artifact scope
  • target environment and release channel
  • known test, CI, deploy, observability, security, and support evidence
  • rollback owner and acceptable risk threshold

Expected outputs:

  • production_audit_plan/v1
  • readiness_matrix/v1
  • release_gate_verdict/v1
  • rollback_and_monitoring_plan/v1
  • risk_register/v1
  • not-evidence boundary

Artifact expectations:

  • readiness_matrix/v1 covering build, tests, CI, security/privacy, performance, observability, rollback, docs/support, and release communication
  • release_gate_verdict/v1 with GO, HOLD, or BLOCK plus missing evidence
  • rollback_and_monitoring_plan/v1 with health signals, owner, threshold, and recovery path

Artifact contracts:

This label denotes the machine-enforcement level, not a skill quality score and not an observed evidence state.

  • contract_id: readiness_matrix/v1; enforcement_level: executable_validated; consumer_id: parse_readiness_matrix

Safety rules:

  • Do not claim production deploy, security scan, live traffic, monitoring health, rollback readiness, or support readiness without observed evidence.
  • Do not perform deploy, infra, credential, production, or external-platform actions from the audit lane.
  • Keep readiness verdict separate from implementation, CI, incident closure, or merge evidence.

Runtime Evidence

Use the current host's own tools and subagent/task mechanism when available; otherwise run the same lanes sequentially or name the unavailable capability. A prepared plan, handoff, checklist, or skill installation is not execution, review, CI, merge-readiness, or merge evidence. Record actual tool results, or not_observed / not_available, in the record; never invent dispatch or host accounting. Treat supplied context as advisory, not proof of hidden memory reads or writes. State scope, constraints, verification, and the stop condition before work. Reply in the user's own words and the host's own voice: the host's persona owns reply language, tone, speech level, and sentence endings, progress updates included (where it sets no language, use the one the user wrote in), and OMH shapes structure and content only; OMH's record terms (surface, lane, wrapper, handoff, evidence boundary, not_observed) stay in records and tool calls, never in the sentence the user reads unless they ask about one; and when a real unresolved user decision or a useful briefing discussion remains, offer one specific, content-linked question. Completed work needs no question; omit unrelated non-action footers and generic offers to continue. Supporting paths are relative to this skill directory; sibling skill paths are relative to its parent. Resolve them from the host-provided skill base directory ({baseDir} on hosts that provide it), never a hardcoded install location. A named workflow not installed here is unavailable, not permission to emulate its host-specific capabilities. Verify through the real surface before done.

Frequently asked questions

What does the Omh Production Audit AI skill do?

[omh] Imminent production launch or release: evaluate release, deploy, security, observability, rollback, docs, and support readiness without claiming production access. Use when the user says: production-audit, production audit, production readiness, prod audit, prod readiness, ready for production, ready to ship, ship readiness.

Why use Omh Production Audit on TypingMind?

Because you install it once and use it with any model. Omh Production Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Omh Production Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-production-audit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Omh Production Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Omh Production Audit?

As many as you like. As long as a model supports skills, you can use Omh Production Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Omh Production Audit AI skill free?

Yes. It is published on GitHub by rlaope under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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