Execplan Create logo

Execplan Create

Community
grp06
execplan-create

Create an ExecPlan from a locked refactor decision, PRD, RFC, or detailed problem statement, following the repo's PLANS.md. Use when the user asks for an exec plan, execution plan, or ExecPlan, or wants a decided refactor turned into a step-by-step plan.

Overview

Publishergrp06
Repositoryuseful-codex-skills
Skill nameexecplan-create
Stars
78
Forks
6
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 grp06 on GitHub. Read the source before you install it.

Installation

Install the Execplan Create 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/grp06/useful-codex-skills/tree/main/execplan-create
  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/grp06/useful-codex-skills.git /tmp/useful-codex-skills
mkdir -p .claude/skills
cp -r /tmp/useful-codex-skills/execplan-create .claude/skills/execplan-create
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Execplan Create 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 Execplan Create 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 Execplan Create 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.

ExecPlan Authoring

Write plans the way a strong software designer would: not as a task list for rearranging code, but as a path to a simpler system with clearer boundaries.

Preferred Inputs

Preferred source input is a decided work item with a completed decision.md.

Supported inputs, in priority order:

  1. explicit work-item path
  2. explicit decision.md path
  3. .agent/active when it points at a work item with stage="decision" and state="completed"
  4. the most recently updated work item under .agent/work/ with stage="decision" and state="completed"
  5. a user-supplied PRD, RFC, voice note, or detailed problem statement

If using a decided work item, do not silently reopen candidate search unless the decision artifact is clearly incomplete.

Work Item Model

For the new workflow, plans live inside work-item directories:

.agent/work/<id-slug>/execplan.md

Each work item should have a small meta.json file with:

  • stage
  • state
  • timestamps
  • relative artifact paths

Update .agent/active as a convenience symlink when operating on a work item, but do not treat it as authoritative over meta.json.

Legacy compatibility:

  • If no work-item directory is available and the user explicitly wants the older singleton flow, you may still write .agent/execplan-pending.md.
  • Downstream skills will prefer the work-item format and only fall back to legacy singleton files when needed.

Source of Truth

  • Read {baseDir}/.agent/PLANS.md in full before drafting.
  • If {baseDir}/.agent/PLANS.md is missing, copy this skill's PLANS.md to {baseDir}/.agent/PLANS.md, then read that copy as the source of truth.
  • Follow PLANS.md exactly. If any instruction conflicts with this skill, PLANS.md wins.

Ousterhout Lens

Use John Ousterhout's design philosophy as the default planning lens:

  • prefer deep modules over shallow wrappers
  • prefer interfaces that hide sequencing and policy
  • prefer fewer concepts and fewer special cases
  • prefer simpler mental models over elegant-looking decomposition
  • prefer concentrating complexity behind a stable boundary over spreading it around

Treat these as the main forms of complexity:

  • change amplification
  • cognitive load
  • unknown unknowns

When authoring a plan, answer these questions explicitly:

  • what complexity exists today, and who pays for it
  • what boundary or interface becomes simpler after this work
  • what knowledge moves out of callers and into the implementation
  • what special cases, duplicate concepts, or orchestration steps disappear
  • what future change becomes easier after this work

Workflow

Step 1: Resolve the input source

If operating on a decided work item:

  • read meta.json
  • read decision.md

If operating from a raw user brief instead:

  • create or reuse a work-item directory under .agent/work/
  • initialize or update meta.json
  • use the user brief as the planning source

Step 2: Inspect the repo and planning boundaries

Inspect the relevant files and flows. Ask:

  • what callers currently need to know
  • where sequencing leaks
  • where concepts duplicate
  • where special cases accumulate

Step 3: Draft execplan.md

Write the ExecPlan to:

  • work-item format: .agent/work/<id-slug>/execplan.md
  • legacy fallback only when necessary: .agent/execplan-pending.md

The plan should:

  • preserve the hard constraints from decision.md
  • name the exact files and boundaries involved
  • explain the current pain
  • describe the intended complexity dividend
  • remain self-contained and novice-friendly

Step 4: Finalize metadata

If using a work item, update meta.json:

  • stage="plan"
  • state="completed"
  • artifacts.execplan="execplan.md"
  • updated_at=<now>

Anti-Patterns

  • reopening candidate search during planning without strong evidence
  • writing a mechanically correct plan that preserves the same complexity under new names
  • proposing thin wrappers or pass-through modules unless they clearly hide detail
  • leaving key design choices to the implementer when the repo evidence is already strong

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 Execplan Create AI skill do?

Create an ExecPlan from a locked refactor decision, PRD, RFC, or detailed problem statement, following the repo's PLANS.md. Use when the user asks for an exec plan, execution plan, or ExecPlan, or wants a decided refactor turned into a step-by-step plan.

Why use Execplan Create on TypingMind?

Because you install it once and use it with any model. Execplan Create 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 Execplan Create in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/grp06/useful-codex-skills/tree/main/execplan-create. 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 Execplan Create?

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 Execplan Create?

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

Is the Execplan Create AI skill free?

Yes. It is published on GitHub by grp06 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇