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Omh Decide

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rlaope
omh-decide

[omh] Decide between options: tradeoffs, a recommendation, and a decision note you can act on. Use when the user says: strategy-brief, strategy brief, strategy memo, product strategy, strategic options, decision note, leadership strategy, next strategy.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-decide
Stars
2.7K
Forks
194
Bundled files
2
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.

  • 2 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 Decide 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.
  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-decide .claude/skills/omh-decide
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Decide 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 Decide 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 Decide 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.

Strategy Brief

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

Why This Exists

strategy-brief exists to keep strategy work explicit, evidence-backed, and inside the Hermes/executor boundary instead of relying on ad hoc chat narration.

Do Not Use When

  • The strategic question is whether an early idea's customer problem and segment are real, and no validated discovery receipt exists yet; use product-discovery-validation.
  • The question is how to run a hiring process — scorecards, interview loops, candidate comparison — rather than whether to hire at all; use people-ops.

Examples

Good example:

  • Prompt: strategy-brief: decide whether our onboarding should prioritize solo founders or enterprise buyers.
  • Expected behavior: Frame options, tradeoffs, assumptions, rejected paths, and the decision evidence needed.
  • Why: The request is strategy-shaped and should not jump directly into implementation.

Bad example:

  • Prompt: strategy-brief: treat casual chat or unaccepted work as if this workflow already produced verified results.
  • Expected behavior: Ask a clarification question or route to a narrower workflow instead of forcing strategy-brief.
  • Why: The request lacks the required inputs or would overclaim work that Hermes did not observe.

Completion Checklist

  • The decision, options, tradeoffs, assumptions, and rejected alternatives are named.
  • Observed signals are separated from strategic inference.
  • Accepted decisions and implementation follow-ups are not conflated.

Recovery Notes

  • If evidence is mostly assumption, label it and recommend a research or feedback-triage pass.
  • If the decision owner is missing, keep the output as options rather than accepted strategy.

Use When

Use when Hermes should turn goals and evidence into options, tradeoffs, recommendations, and a decision-ready brief.

Strong routing signals: `strategy-brief`, `strategy brief`, `strategy memo`, `product strategy`, `strategic options`, `decision note`, `leadership strategy`, `next strategy`, `capacity planning`, `hire or outsource`, `outsource or hire`, `cut scope`, `headcount plan`, `demand versus capacity`, `다음 전략`, `전략 정리`, `전략 메모`, `전략 옵션`, `의사결정`, `리더십 회의`

Catalog Metadata

Category: strategy Phase: brief Quality tier: decision-gated Reasoning demand: standard

Quality bar:

  • Name the decision, constraints, options, tradeoffs, and rejected alternatives.
  • Tie recommendations to observed evidence or mark them as assumptions.
  • Keep coding handoff disabled until strategy is accepted and code work is explicit.
  • When the decision is a resourcing one — hire, outsource, or cut scope — quantify demand and capacity against each other in one unit before comparing options, and price each option with the lag before it lands; a gap that exists this quarter is not closed by a hire that ramps next quarter. The worked example is omh-decide/references/capacity-planning.md.
  • Ask whether the decision deserves a durable record - hard to reverse, surprising without its context, and carrying a real trade-off; all three or no record, a decision note in chat is enough.
  • When a record is warranted, draft it per omh-decide/references/decision-records.md - the docs/adr/ convention with Context, Drivers, Considered Options, Decision, Consequences with mitigations, and Related - and stop for the user's approval before any file is written.
  • Never edit an accepted record: status moves Proposed to Accepted to Deprecated or Superseded, supersession is a new record pointing back at the old one, and a Rejected record is kept - it is what decision-recall reads later.

Required inputs:

  • goal
  • known evidence
  • constraints
  • decision owner

Expected outputs:

  • options
  • tradeoffs
  • recommended direction
  • decision note

Artifact expectations:

  • strategy brief or decision note when a wrapper captures it

Safety rules:

  • Do not treat a draft recommendation as an accepted decision.
  • Keep unresolved assumptions visible.
  • Separate strategy from implementation planning unless the user asks for execution.
  • A drafted decision record stays a proposal: nothing is written under docs/adr/ until the user approves the write.

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. Report actual tool results or not_observed / not_available; 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. 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 Decide AI skill do?

[omh] Decide between options: tradeoffs, a recommendation, and a decision note you can act on. Use when the user says: strategy-brief, strategy brief, strategy memo, product strategy, strategic options, decision note, leadership strategy, next strategy.

Why use Omh Decide on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-decide. 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 Decide?

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 Decide?

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

Is the Omh Decide 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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