request-refactor-plan

A guided process for planning a refactor, meaning a controlled change to improve existing code without changing its intended behaviour. It interviews the user, checks the repository and tests, breaks the work into small commits, and files the plan as a GitHub issue.

In plain words
What is it for?
Use it to investigate a refactoring request, compare implementation options, define scope, assess test coverage, and create a detailed GitHub issue.
Why use it?
It turns a broad or risky cleanup into reviewed, incremental steps. It also checks whether the code has enough tests to support the planned changes.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/stevesolun/ctx/request-refactor-plan
Any agent
npx skills add stevesolun/ctx --skill request-refactor-plan
Clone the repo
git clone --depth 1 https://github.com/stevesolun/ctx

Made for: Claude Code, Codex.

Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 555 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 88% copy Near-identical to another mod 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 $0.00053 $0.00555
Opus 5 $0.00026 $0.00278
Sonnet 5 $0.00011 $0.00111
Haiku 4.5 $0.00005 $0.00056

Measured 3d ago against content hash d59de4ba6cc1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

request-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.

Origin

This is a copy

88% identical to request-refactor-plan — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

imported-skills/mattpocock/request-refactor-plan/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

This skill will be invoked when the user wants to create a refactor request. You should go through the steps below. You may skip steps if you don't consider them necessary.

  1. Ask the user for a long, detailed description of the problem they want to solve and any potential ideas for solutions.

  2. Explore the repo to verify their assertions and understand the current state of the codebase.

  3. Ask whether they have considered other options, and present other options to them.

  4. Interview the user about the implementation. Be extremely detailed and thorough.

  5. Hammer out the exact scope of the implementation. Work out what you plan to change and what you plan not to change.

  6. Look in the codebase to check for test coverage of this area of the codebase. If there is insufficient test coverage, ask the user what their plans for testing are.

  7. Break the implementation into a plan of tiny commits. Remember Martin Fowler's advice to "make each refactoring step as small as possible, so that you can always see the program working."

  8. Create a GitHub issue with the refactor plan. Use the following template for the issue description:

Problem Statement

The problem that the developer is facing, from the developer's perspective.

Solution

The solution to the problem, from the developer's perspective.

Commits

A LONG, detailed implementation plan. Write the plan in plain English, breaking down the implementation into the tiniest commits possible. Each commit should leave the codebase in a working state.

Decision Document

A list of implementation decisions that were made. This can include:

  • The modules that will be built/modified
  • The interfaces of those modules that will be modified
  • Technical clarifications from the developer
  • Architectural decisions
  • Schema changes
  • API contracts
  • Specific interactions

Do NOT include specific file paths or code snippets. They may end up being outdated very quickly.

Testing Decisions

Read the full file on GitHub · 69 lines

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 First seen · 69 lines · 53 tokens per session scan A d59de4ba6cc1

Subscribe to this mod's changes

request-refactor-plan is a skill published in the GitHub repository stevesolun/ctx (581 stars, last pushed 9d ago), licensed MIT. It adds 53 tokens to every session and 555 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to request-refactor-plan, differing in 2 lines, and is treated as a copy.

Related

Other skills, from other repositories

project-graveyard

Scans the developer's machine for dead side projects, autopsies each one from its git history (died at the payments wall, killed by a newer project, finished but never shipped), surfaces their personal death patterns, and picks the corpse most worth resurrecting — then helps ship it. Use when the user mentions…

Shubhamsaboo/awesome-llm-apps · 127 tokens

web-app-penetration-testing

Pentest a web app or website end to end — black-box testing of a live URL, staging environment, or local dev server that finds and exploits real vulnerabilities (auth bypass, broken access control, IDOR, injection, XSS, SSRF, business logic) and proves each one with a working proof-of-concept instead of a signature…

usestrix/strix · 129 tokens

haiku

When writing a haiku for this bot, follow these conventions.

agno-agi/agno · 0 tokens

deploy-docker-compose

Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack…

omnigent-ai/omnigent · 84 tokens

azure-mgmt-botservice-dotnet

Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".

microsoft/skills · 78 tokens

babysit

Same-session monitoring loop for PRs, CI runs, tickets, and deployments using the monitorstart / monitorupdate / autonudgestop MCP tools. The loop re-injects your check instructions into THIS session on an idle interval — same context, same tools — and works from dashboard chat, Slack threads, and Discord DMs. Use…

kirodotdev/KiroCrew · 137 tokens