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Omh Reliability Review

CommunityPopular
rlaope
omh-reliability-review

[omh] Postmortem for an outage or SLO miss: postmortems, SLOs, error budgets, incident follow-ups, and service reliability evidence. Use when the user says: reliability-review, reliability review, incident review, incident postmortem, postmortem, post-mortem, slo review, slo.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-reliability-review
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 Reliability Review 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-reliability-review
  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-reliability-review .claude/skills/omh-reliability-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Reliability Review 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 Reliability Review 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 Reliability Review 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.

Reliability Review

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

Why This Exists

reliability-review exists to make SRE-style review strict: service reliability claims must point to metrics or references, and remediation remains separate from the review narrative.

Do Not Use When

  • The user only needs a generic status report or leadership deck.
  • No service, incident, SLO, metric, or reliability source boundary is available.
  • The request is implementation of remediation rather than review of reliability evidence.
  • The incident is still open and the user needs severity declared, a commander assigned, a running timeline, and recovery verified; use omh-live-incident-response and review it once it is closed.

Examples

Good example:

  • Prompt: reliability-review 장애 포스트모템과 SLO 에러버짓 상태를 검토해줘.
  • Expected behavior: Prepare a reliability artifact that separates metrics/references, assumptions, missing evidence, and remediation follow-ups.
  • Why: The request is reliability evidence review with closure-sensitive claims.

Bad example:

  • Prompt: reliability-review make a monthly PPT report for leadership.
  • Expected behavior: Use report-package unless the report specifically asks for reliability evidence review.
  • Why: Report packaging and reliability validation are independent operations surfaces.

Completion Checklist

  • Confirm the workflow target, evidence boundary, and stop condition are named.
  • Report which outputs are prepared, observed, blocked, or missing.
  • Name the smallest next verification or handoff instead of claiming completion from narration.

Recovery Notes

  • If required context is missing, ask one blocking question or route back to the narrower workflow.
  • If runtime or wrapper evidence is unavailable, keep the status as not_observed and expose the next observable action.

When to Use

Use when Hermes should review incident notes, SLOs, error budgets, or service reliability evidence while keeping remediation and closure claims observed.

Strong routing signals: `reliability-review`, `reliability review`, `incident review`, `incident postmortem`, `postmortem`, `post-mortem`, `slo review`, `slo`, `sla`, `error budget`, `service reliability`, `reliability followup`, `remediation tracking`, `sre review`, `장애 리뷰`, `장애 회고`, `포스트모템`, `사후 분석`, `에러버짓`, `에러 버짓`, `서비스 신뢰성`, `신뢰성 검증`, `재발 방지`

Catalog Metadata

Category: reliability Phase: incident-and-slo-review Quality tier: reliability-gated Reasoning demand: standard

Quality bar:

  • Name service, incident/time window, SLO/error-budget target, source references, and missing observations.
  • Separate supplied metrics, incident notes, assumptions, and remediation follow-ups.
  • Keep closure and remediation status unobserved until evidence is supplied.

Required inputs:

  • service or incident scope
  • time window
  • metric/source references
  • known remediation items or gaps

Expected outputs:

  • reliability review
  • evidence and missing-evidence list
  • remediation follow-up boundary

Artifact expectations:

  • omh_operation_artifact/v1 reliability-review artifact when a wrapper or CLI records it

Artifact contracts:

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

  • contract_id: omh_operation_artifact/v1; enforcement_level: shared_operation_validated; consumer_id: validate_operation_artifact

Safety rules:

  • Do not claim SLO pass, healthy error budget, incident closure, or remediation completion without source, metric, or reference evidence.
  • Do not treat a reliability narrative as verification, review, CI, merge, or deploy evidence.
  • Route code remediation through a separate accepted plan or executor handoff.

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 Reliability Review AI skill do?

[omh] Postmortem for an outage or SLO miss: postmortems, SLOs, error budgets, incident follow-ups, and service reliability evidence. Use when the user says: reliability-review, reliability review, incident review, incident postmortem, postmortem, post-mortem, slo review, slo.

Why use Omh Reliability Review on TypingMind?

Because you install it once and use it with any model. Omh Reliability Review 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 Reliability Review in TypingMind?

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

Which AI models can use Omh Reliability Review?

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 Reliability Review?

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

Is the Omh Reliability Review 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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