Visual Pr

OrganizationPopular

humanlayer

visual-pr

Only use when the user explicitly invokes this skill by name.

Overview

Publisher	humanlayer
Repository	`skills`
Skill name	`visual-pr`
Stars	4.7K
Forks	151
Bundled files	3
License	MIT
Links	Skill source Repository

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.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by humanlayer on GitHub. Read the source before you install it.

Installation

Install the Visual Pr AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/humanlayer/skills/tree/main/plugins/visual-pr/skills/visual-pr
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.

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/humanlayer/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/visual-pr/skills/visual-pr .claude/skills/visual-pr

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Visual 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 Visual 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 Visual 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.

Describe a Pull Request

Create or update the pull request for the current task with a concise description that helps a reviewer understand why the change exists and the shape of the implementation.

Workflow

Read the description template:

Read({SKILLBASE}/references/pr_description_template.md)
Identify or create the pull request:
- Check the current branch for a PR with gh pr view --json url,number,title,state,baseRefName,headRefName 2>/dev/null.
- If no PR exists, inspect git status --short --branch and the commits on the current branch.
- Commit task-related changes when needed, push the branch with an upstream, and create a PR for it. Follow the repository's git safety protocol.
- Ask the user to select a PR only when the current branch has no relevant work and there is no safe current-branch PR to create.
Gather only the context needed to explain the change:
- Read the ticket and any relevant task artifacts.
- Read the complete PR diff and enough surrounding code to understand behavior and ownership.
- Use gh pr view to collect PR metadata and changed files.
- Read {SKILLBASE}/references/show-me.md for the visual-outline conventions used in the PR body.
Write the PR description using the template:
- Keep Why the change to exactly one sentence.
- Keep Special things to note to 1-3 bullets. Prioritize reviewer warnings, migrations, compatibility constraints, deliberate omissions, or surprising decisions. Write - None. when there are no special considerations.
- Make Change outline a compact, /show-me-inspired structural view rather than prose or a file-by-file changelog.
- Include only the views that help explain this PR:
  - SQL table and endpoint contract changes, plus pseudocode for business logic.
  - key data structure / type changes
  - A shallow file tree showing changed responsibilities.
  - React component tree changes, including important hooks, state, and package boundaries.
  - Call-tree, call-stack, control-flow, or data-flow changes.
- Prefer diff blocks when showing changes to an existing shape. Show the complete target shape when most of it is new or diff notation would obscure ownership or order.
- Keep each view focused on what a reviewer needs. Omit categories that did not change.
- optionaL: if you are aware of a ticket id/url, a humanlayer task url, or related plan/document urls, or other relevant links, include them in the header, otherwise omit the header
Save and publish the description:
- Use .humanlayer/tasks/{task-slug}/pr-description.md when the task directory exists; otherwise use .humanlayer/tasks/pr-{number}/description.md.
- Update the PR with gh pr edit {number} --body-file {output-path}.
- Confirm the update succeeded.
Report completion:
- Read {SKILLBASE}/references/describe_pr_final_answer.md.
- Respond using that final answer template with the PR URL, saved description URL, and concise list of changed files.

Always read and follow {SKILLBASE}/references/pr_description_template.md. Do not expand the PR body beyond that template.

Write as one human talking to another: avoid jargon and slang, and use simple, coherent, concise language.

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 Visual Pr AI skill do?

Only use when the user explicitly invokes this skill by name.

Why use Visual Pr on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/humanlayer/skills/tree/main/plugins/visual-pr/skills/visual-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 Visual 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 Visual Pr?

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

Is the Visual Pr AI skill free?

Yes. It is published on GitHub by humanlayer 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Describe a Pull Request

Workflow

Bundled files

Frequently asked questions

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