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Omh Refactor Plan

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rlaope
omh-refactor-plan

[omh] Decided cross-module refactor to phase: refactor planning - turn a decided boundary-changing refactor into a phased plan - reconnaissance, contracts-first phase order, per-phase verification and rollback, a files table, and an explicit approval gate before any edit. Use when the user says: refactor-plan, refactor plan, plan this refactor, plan the refactor, refactor planning, refactor phases, phased refactor, refactor in phases.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-refactor-plan
Stars
3.6K
Forks
269
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 Refactor Plan 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-refactor-plan
  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-refactor-plan .claude/skills/omh-refactor-plan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Refactor Plan 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 Refactor Plan 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 Refactor Plan 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.

Refactor Plan

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

Why This Exists

refactor-plan exists because boundary-changing refactors bounced between goal planning and behavior-preserving cleanup with neither owning the execution shape: the phase order, the per-phase rollback, and the files table that make a large refactor reviewable and abortable.

Do Not Use When

  • The refactor's direction is still contested or the goal itself needs consensus planning; use ulw-plan.
  • The work is deletion-first cleanup with no boundary changes; use omh-ai-slop-cleaner.
  • The plan is done and the claim is that work is complete; use omh-verification-gate for the evidence close.
  • The version bump carries a security advisory, a CVE, or a leaked secret; use omh-security-event-response, which owns containment and closure.

Examples

Good example:

  • Prompt: We decided to split the billing module out of orders - plan the refactor so each step is shippable.
  • Expected behavior: Map affected files and consumers from the import graph, name hidden coupling and blast radius, order the five phases with per-phase verification and rollback, ship the files table, and stop at the approval gate.
  • Why: The direction is decided and the need is a phased, abortable execution shape - exactly this workflow's territory.

Bad example:

  • Prompt: Should we even split billing out of orders?
  • Expected behavior: Route to ralplan: the direction is not decided, so consensus planning comes before phase planning.
  • Why: A phase plan for a contested direction launders a decision through logistics.

Completion Checklist

  • Reconnaissance names affected files, boundaries, coupling, and blast radius from observed evidence.
  • Every phase carries its verification command and its rollback point, and ends at a shippable commit.
  • The files table covers every touched file with action, phase, and dependencies.
  • For an upgrade, every breaking change row names its call sites or an observed empty search, and every stage names its rollback.
  • The plan stopped at the approval gate; no implementation began without the user's go.

Recovery Notes

  • If the import graph is unavailable, build the codegraph first or reduce the plan's confidence and say which files are unverified.
  • If a phase cannot be made independently green, split it further; two half-phases beat one unabortable one.
  • If reconnaissance finds the direction itself is unsettled, route back to ralplan before ordering phases.

When to Use

Use when a refactor that crosses module boundaries is already decided and needs its execution shaped: which files move in which phase, what verifies each phase, and where each phase rolls back to - before anything is edited.

Strong routing signals: `refactor-plan`, `refactor plan`, `plan this refactor`, `plan the refactor`, `refactor planning`, `refactor phases`, `phased refactor`, `refactor in phases`, `refactor rollback plan`, `blast radius`, `module restructure plan`, `restructure plan`, `dependency upgrade`, `major version upgrade`, `framework upgrade`, `upgrade to the next major`, `breaking change upgrade`, `lockfile`, `리팩터링 계획`, `리팩토링 계획`, `리팩터링 단계`, `단계별 리팩터링`, `리팩터링 계획 세워줘`, `리팩터링 롤백 계획`

Catalog Metadata

Category: planning Phase: refactor-plan Quality tier: plan-gated Reasoning demand: standard

Quality bar:

  • Reconnaissance first: affected files, ownership boundaries, hidden coupling, and blast radius are mapped before any phase is ordered; the full contract is omh-refactor-plan/references/refactor-phases.md.
  • Order phases contracts-first: types and interfaces, then implementations, then callers in reviewable groups, then tests, then cleanup - and name what verifies each phase and where it rolls back to.
  • Ship the files table with the plan: one row per file with action, phase, and blocks/blocked-by; a row without a phase is unplanned work.
  • Size verification to the blast radius, not to optimism: a phase touching public surfaces or persisted shapes carries the full gate, not the fast one.
  • For a dependency or framework upgrade, read four inputs before ordering phases — advisory and end-of-life intake, the licence delta at the target version, the upstream migration guide item by item against this codebase, and lockfile handling in the same commit as the manifest; a breaking change nobody checked is a gap, not a pass. The full contract is omh-refactor-plan/references/dependency-upgrade.md.
  • Stop at the approval gate and hand the user the go/no-go, whole plan or first phase.

Required inputs:

  • the decided target shape (what moves where), or a pointer to the accepted plan that decided it
  • the affected-file evidence: import graph, codegraph handoff, or an observed file inventory
  • the regression gates that exist today (test suite, typecheck, generated-artifact checks)

Expected outputs:

  • reconnaissance: affected files, ownership boundaries, hidden coupling, blast radius — and for an upgrade, the advisory, licence, migration-guide, and lockfile intake
  • phase plan in the fixed order - types/interfaces, implementations, callers, tests, cleanup - each with verification and rollback
  • files table: path, action, phase, blocks/blocked-by
  • for an upgrade, the call-site readiness gate: every breaking change between the two versions against this repository's call sites or an observed empty search, and every stage's rollback
  • the approval gate: the plan stops and waits for the user's go

Artifact expectations:

  • metadata-only runtime record when a wrapper or shell is available

Safety rules:

  • The plan comes from observed repo evidence, never from memory of the tree.
  • An upgrade plan is not ready while any breaking change lacks its call sites or an observed empty search, or any stage lacks its rollback; name the open rows instead of calling the bump safe to merge.
  • Every phase ends at a commit that could ship; a phase that cannot end green is split further.
  • Nothing is deleted before the cleanup phase, and cleanup starts from a tagged rollback point.
  • Do not begin implementing any phase without the user's explicit approval of the plan.

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 Refactor Plan AI skill do?

[omh] Decided cross-module refactor to phase: refactor planning - turn a decided boundary-changing refactor into a phased plan - reconnaissance, contracts-first phase order, per-phase verification and rollback, a files table, and an explicit approval gate before any edit. Use when the user says: refactor-plan, refactor plan, plan this refactor, plan the refactor, refactor planning, refactor phases, phased refactor, refactor in phases.

Why use Omh Refactor Plan on TypingMind?

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

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

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 Refactor Plan?

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

Is the Omh Refactor Plan 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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