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Omh Agent Instructions

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rlaope
omh-agent-instructions

[omh] Agent instruction file for a repo -- AGENTS.md, CLAUDE.md, a Cursor rule: write or update what an agent cannot derive from the code, inside a marked region, with every command verified or marked unverified and no counts that drift. Use when the user says: agent-instructions, agents.md, claude.md, gemini.md, copilot-instructions.md, .cursorrules, cursor rules, cursor rule.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-agent-instructions
Stars
3.6K
Forks
269
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Omh Agent Instructions 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-agent-instructions
  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-agent-instructions .claude/skills/omh-agent-instructions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Agent Instructions 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 Agent Instructions 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 Agent Instructions 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.

Agent Instructions

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

Why This Exists

agent-instructions exists because the file every handoff target reads first had no owner: rules-distill extracts rule candidates, codebase-onboarding builds a human reading path, and context aligns terminology, and each reads that file without writing it.

First Steps

  • List every instruction file and which agent reads it before proposing a section.
  • Run or ask for the observed run of each command before marking it verified.

Do Not Use When

  • The ask is distilling repeated lessons into reviewed rule candidates; use omh-rules-distill.
  • The ask is a reading path through the codebase for a new engineer; use omh-codebase-onboarding.
  • The ask is project terminology alignment -- reviewing the terms this project uses and correcting inconsistent vocabulary; use ulw-context.
  • The ask is user-facing product documentation; use omh-docs.

Examples

Good example:

  • Prompt: update our CLAUDE.md
  • Expected behavior: Inventory the instruction files, run or collect each build and test command, mark each verified or unverified, and replace only the marked region with the commands, the generated-file map, the gates, and the costed pitfalls, refusing any count or line number.
  • Why: An instruction file that states an unrun command or a stale count sends every later agent the wrong way.

Bad example:

  • Prompt: add that the suite has 4,100 tests and the router is at line 212 of chat.py
  • Expected behavior: Refuse both values, and write the command that counts the tests and the symbol that locates the router instead.
  • Why: Both numbers were already wrong by the next merge.

Completion Checklist

  • Every instruction file and its reader are listed.
  • Every command is marked verified with an observed run, or unverified.
  • Only the marked region changed, and hand-written text is byte-for-byte.
  • No count, line number, or value the code already states was written.
  • Every generated file names its source, its regenerate command, and its gate.

Recovery Notes

  • If a command cannot be run here, write it marked unverified with what would verify it.
  • If the file has no markers, insert them once around the new section and leave everything else untouched.

When to Use

Use when the repository's agent instruction file is being written or kept current: AGENTS.md, CLAUDE.md, GEMINI.md, a Cursor rule, or a Copilot instructions file. The output is the build and test commands each marked verified or unverified, the generated-file map with its regenerate command and gate, the byte-exact gates, and the pitfalls that cost time, written inside a marker-delimited region so hand-written sections survive.

Strong routing signals: `agent-instructions`, `agents.md`, `claude.md`, `gemini.md`, `copilot-instructions.md`, `.cursorrules`, `cursor rules`, `cursor rule`, `agent instruction file`, `agent instructions file`, `instructions file for agents`, `set up agents.md`, `update our claude.md`, `write an agents.md`

Catalog Metadata

Category: planning Phase: agent-instructions Quality tier: verified-command-and-region-gated Reasoning demand: standard

Quality bar:

  • Inventory every instruction file first and respect closest-file-wins nesting.
  • Load references/instruction-file-method.md for the section order, the marker convention, the verified and unverified command form, and the drift rules instead of recalling them.
  • Record each pitfall with what it cost, so a reader can tell a scar from a preference.
  • Pair every generated file with its source, its regenerate command, and the gate that checks it.
  • Keep prepared, verified, and written as separate states for every command and section.

Required inputs:

  • which instruction files exist, where they sit, and which agents read them
  • the build, test, lint, and regenerate commands the repository uses
  • which files are generated, from what source, and which gate checks them
  • the pitfalls that have cost time, each with what it cost
  • observed output for every command written into the file

Expected outputs:

  • instruction_file_inventory/v1
  • command_verification_record/v1
  • instruction_region_update/v1
  • drift_refusal_note/v1 when a requested line would record a count or a line number

Artifact expectations:

  • instruction_file_inventory/v1 lists every instruction file, its path, the agents that read it, and which one is closest to each directory, since the closest file wins
  • command_verification_record/v1 marks every command verified, with the observed exit status and when, or unverified, and nothing is written as verified without an observed run
  • instruction_region_update/v1 replaces only the text between <!-- omh:agent-instructions:begin --> and <!-- omh:agent-instructions:end -->, and inserts the markers once when absent, so every hand-written section outside them is left byte-for-byte
  • drift_refusal_note/v1 names each requested count, line number, or other value the code already states, and writes the command or the file that derives it instead

Safety rules:

  • Never write outside the marker-delimited region: the text before <!-- omh:agent-instructions:begin --> and after <!-- omh:agent-instructions:end --> is hand-written and stays byte-for-byte.
  • Never write a command as verified without an observed run; mark it unverified instead.
  • Refuse to record counts, line numbers, test totals, or file sizes; they drift, so point at the command or file that derives them.
  • Write only what an agent cannot derive from the code; restating the code is drift waiting to happen.
  • Never copy secrets, tokens, or private hostnames into an instruction file.

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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Omh Agent Instructions AI skill do?

[omh] Agent instruction file for a repo -- AGENTS.md, CLAUDE.md, a Cursor rule: write or update what an agent cannot derive from the code, inside a marked region, with every command verified or marked unverified and no counts that drift. Use when the user says: agent-instructions, agents.md, claude.md, gemini.md, copilot-instructions.md, .cursorrules, cursor rules, cursor rule.

Why use Omh Agent Instructions on TypingMind?

Because you install it once and use it with any model. Omh Agent Instructions 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 Agent Instructions in TypingMind?

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

Which AI models can use Omh Agent Instructions?

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 Agent Instructions?

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

Is the Omh Agent Instructions 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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