omh-refactor-plan

omh-refactor-plan is a skill for Claude Code, Codex from rlaope/oh-my-hermes. It costs 93 tokens per session (1,538 once invoked), scanned A, original, MIT.

A phased plan for refactoring software when the change crosses module or system boundaries. It maps affected files and consumers, then defines verification and rollback for each phase.

In plain words
What is it for?
Use it to split modules, change architectural boundaries, and prepare a staged implementation plan after the direction is agreed.
Why use it?
It makes large refactors easier to review, stop, and undo when hidden dependencies or side effects appear.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to split modules, change architectural boundaries, and prepare a staged implementation plan after the direction is agreed.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rlaope/oh-my-hermes/omh-refactor-plan
About the project

oh-my-hermes is an operating layer for Hermes Agent that organizes requests into workflows for planning, research, creation, coding handoffs, operations, and project memory. Hermes users run these workflows through the desktop app, CLI, or messenger app, while the catalogue add-ons extend its native capabilities.

rlaope/oh-my-hermes · 1,648 stars · on GitHub · rlaope.github.io

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add rlaope/oh-my-hermes --skill omh-refactor-plan
Clone the repo
git clone --depth 1 https://github.com/rlaope/oh-my-hermes

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for omh-refactor-plan

README.md
[![agentmods](https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-refactor-plan/github.svg)](https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-refactor-plan)
Your own site
<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-refactor-plan"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-refactor-plan/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for omh-refactor-plan

Your own site · 80×15
<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-refactor-plan"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-refactor-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,538 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.01538
Opus 5 $0.00046 $0.00769
Sonnet 5 $0.00019 $0.00308
Haiku 4.5 $0.00009 $0.00154

Measured 3d ago against content hash 78f810bf2c44, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

omh-refactor-plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/omh-refactor-plan/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Refactor Plan

This is a Hermes-native refactor-plan workflow skill.

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 ralplan.
  • The work is deletion-first cleanup with no boundary changes; use ai-slop-cleaner.
  • The plan is done and the claim is that work is complete; use verification-gate for the evidence close.

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.
  • 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.

Read the full file on GitHub · 126 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago Changed 78f810bf2c44
  2. 8d ago First seen · 126 lines · 93 tokens per session scan A 0db2ec58d460

Subscribe to this mod's changes

omh-refactor-plan is a skill published in the GitHub repository rlaope/oh-my-hermes (1,648 stars, last pushed yesterday), licensed MIT. It adds 93 tokens to every session and 1,538 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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