Chained Pr logo

Chained Pr

OrganizationPopular
Gentleman-Programming
chained-pr

Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.

Overview

PublisherGentleman-Programming
Repositorygentle-ai
Skill namechained-pr
Stars
7K
Forks
760
Bundled files
1
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • 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 Gentleman-Programming on GitHub. Read the source before you install it.

Installation

Install the Chained Pr 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/Gentleman-Programming/gentle-ai.git /tmp/gentle-ai
mkdir -p .claude/skills
cp -r /tmp/gentle-ai/internal/assets/skills/chained-pr .claude/skills/chained-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Chained Pr 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 Chained Pr 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 Chained Pr 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.

Activation Contract

Load this skill when a planned PR may exceed 400 changed lines, SDD forecasts 400-line budget risk: High or Chained PRs recommended: Yes, an ODD feature's forecast or running authored changed-line count from work-unit commits exceeds about 400, or the user asks for chained/stacked PRs, review slices, or reviewer-load control.

Hard Rules

  • Split PRs over 400 changed lines unless a maintainer explicitly accepts size:exception.
  • The budget constrains how work is sliced, never the code itself. Never delete comments, blank lines, docs, or tests, and never compress or restyle code, to fit under the budget.
  • Slicing is bounded: make one honest slicing pass. If no cohesive split brings every slice within budget, stop iterating, keep the best cohesive split, and report the final line count with a size:exception recommendation.
  • Keep each PR reviewable in about ≤60 minutes.
  • Use one deliverable work unit per PR; keep tests/docs with the unit they verify.
  • State start, end, prior dependencies, follow-up work, and out-of-scope items in every chained PR.
  • Every child PR must include a dependency diagram marking the current PR with 📍.
  • In Feature Branch Chain, create a draft/no-merge tracker PR; child PR #1 targets the tracker branch, later children target the immediate parent branch.
  • Treat polluted diffs as base bugs: retarget or rebase until only the current work unit appears.
  • Do not mix chain strategies after the user chooses one.

Decision Gates

ConditionAction
PR ≤400 changed lines and focusedKeep single PR.
PR >400, each slice can land independentlyUse Stacked PRs to main.
PR >400, feature must integrate before mainUse Feature Branch Chain with tracker.
Generated/vendor/migration diff cannot split cleanlyAsk maintainer for size:exception.
No cohesive split fits the budget after one slicing passStop; deliver the best split, report the overage and why it cannot shrink further, and recommend size:exception.
SDD provides delivery_strategyFollow it before apply/PR creation.
ODD provides delivery_strategy and chain_strategyFollow them before the next work-unit commit or PR creation.

Execution Steps

  1. Estimate changed lines and identify independent work units.
  2. Ask for a chain strategy when none is cached and the budget is exceeded.
  3. Create branches/PRs using the chosen strategy only.
  4. Add Chain Context to each PR without replacing the repo PR template.
  5. Verify each PR independently: CI/tests/docs/manual checks, rollback scope, and clean diff.
  6. Keep tracker PR draft/no-merge until all child PRs are reviewed and integrated.

Output Contract

Return the chosen strategy, PR order, current PR boundary, dependency diagram, review budget (additions + deletions), verification plan, and any size:exception rationale.

References

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 Chained Pr AI skill do?

Trigger: PRs over 400 lines, stacked PRs, review slices. Split oversized changes into chained PRs that protect review focus.

Why use Chained Pr on TypingMind?

Because you install it once and use it with any model. Chained Pr 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 Chained Pr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Gentleman-Programming/gentle-ai/tree/main/internal/assets/skills/chained-pr. 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 Chained Pr?

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 Chained Pr?

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

Is the Chained Pr AI skill free?

Yes. It is published on GitHub by Gentleman-Programming under the Apache-2.0 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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