Write Issue

OrganizationPopular

tldraw

write-issue

Reference standards for writing and maintaining GitHub issues in the tldraw repository. Use as supporting guidance when another skill or workflow needs issue title, body, type, label, or triage standards.

Overview

Publisher	tldraw
Repository	`tldraw`
Skill name	`write-issue`
Stars	50.4K
Forks	3.5K
Bundled files	Instructions only
Links	Skill source Repository Homepage

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by tldraw on GitHub. Read the source before you install it.

Installation

Install the Write Issue 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.
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/tldraw/tldraw.git /tmp/tldraw
mkdir -p .claude/skills
cp -r /tmp/tldraw/skills/write-issue .claude/skills/write-issue

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

Use it in TypingMind

Enable Write Issue 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 Write Issue 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 Write Issue 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.

Writing and maintaining GitHub issues

Standards for issues in tldraw/tldraw.

Title standards

Sentence case - Capitalize only the first word and proper nouns
No type prefixes - Use GitHub issue types, not Bug:, Feature:, [Bug], etc.
Imperative mood for enhancements - "Add padding option" not "Adding padding option"
Descriptive for bugs - Describe the symptom: "Arrow bindings break with rotated shapes"
Specific - Readable without opening the issue body

Good titles

Arrow bindings break with rotated shapes
Add padding option to zoomToFit method
Pinch zoom resets selection on Safari

Bad titles

Bug: arrow bug (prefix, vague)
[Feature] Add new feature (prefix, vague)
Not working (vague)

Title cleanup transformations

Remove prefixes: Bug: X → X
Fix capitalization: Add Padding Option → Add padding option
Use imperative: Adding feature X → Add feature X
Be specific: Problem → [Describe the actual problem]
Translate non-English titles to English

Issue types

Set via the GitHub GraphQL API after creating the issue (the --type flag is not reliably supported):

Type	Use for
`Bug`	Something isn't working as expected
`Feature`	New capability or improvement
`Example`	Request for a new SDK example
`Task`	Internal task or chore

Labels

Use sparingly (1-2 per issue) for metadata, not categorization.

Common labels

Label	Use for
`good first issue`	Well-scoped issues for newcomers
`More Info Needed`	Requires additional information
`sdk`	Affects the tldraw SDK
`dotcom`	Related to tldraw.com
`a11y`	Accessibility
`performance`	Performance improvement
`api`	API change

Automation labels (do not apply manually)

keep, stale, update-snapshots, publish-packages, major, minor, skip-release, deploy triggers

Issue body standards

Bug reports

Clear description of what's wrong
Steps to reproduce
Expected vs actual behavior
Environment details (browser, OS, version) when relevant
Screenshots/recordings when applicable

Feature requests

Problem statement - What problem does this solve?
Proposed solution - How should it work?
Alternatives considered
Use cases

Example requests

What API/pattern to demonstrate
Why it's useful
Suggested approach
Which example category it belongs to

Agent-drafted issues (problem readback and open questions)

Issues created by the /issue skill capture the user's intent over a short interrogation, so they carry an unheaded readback paragraph beneath the verbatim description, followed by open questions and a confidence status line at the bottom:

Problem readback - A brief, unheaded paragraph that states the agent's interpretation of the problem, expected behavior, and scope. It should be easy for the user to correct. Keep it product-facing: no code blocks, no long implementation analysis, no file paths, no function names, no line numbers, and no fix recipes unless the user explicitly asks for them.
Open questions - A numbered list of the specific gaps in intent or context still worth asking the user about. Answers are written beneath each question as the user replies, and the readback is revised each round. A question prefixed with Critical: is genuinely blocking — the issue cannot be worked on until it is answered. Most issues have none. Non-critical questions the user chooses not to answer are marked _Deferred by user; not blocking implementation._.
Confidence line - A plain-text line at the bottom, not a section heading, such as Confidence: 84%, ready to get started. or Confidence: 42%, still need more information. It reflects whether the issue has enough of the user's intent and context to work on, not confidence in the eventual fix.

Leave the readback, open questions, and confidence line in the issue once interrogation is complete. The answered questions are a record of the discussion that produced the issue, so keep them rather than deleting them — mark questions resolved in place and keep the final readback as the issue's concise problem statement.

Triage workflow

New issues

Verify sufficient information to act on
Set appropriate issue type
Clean up title if needed
Add More Info Needed label and comment if details missing
Add good first issue if appropriate

Stale issues

Review if still relevant
Close if no longer applicable
Add keep label if should remain open
Request updates if waiting on information

Important

Never include AI attribution unless the issue directly relates to AI tooling
Never use title case for descriptions - use sentence case

Frequently asked questions

What does the Write Issue AI skill do?

Why use Write Issue on TypingMind?

Because you install it once and use it with any model. Write Issue 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 Write Issue in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tldraw/tldraw/tree/main/skills/write-issue. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Write Issue?

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 Write Issue?

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

Is the Write Issue AI skill free?

It is published on GitHub by tldraw. Check the repository for licensing terms. 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

Receiving Code Review

obra

CommunityPopular

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative…

Requesting Code Review

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CommunityPopular

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

Systematic Debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Test Driven Development

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CommunityPopular

Use when implementing any feature or bugfix, before writing implementation code

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Writing and maintaining GitHub issues

Title standards

Good titles

Bad titles

Title cleanup transformations

Issue types

Labels

Common labels

Automation labels (do not apply manually)

Issue body standards

Bug reports

Feature requests

Example requests

Agent-drafted issues (problem readback and open questions)

Triage workflow

New issues

Stale issues

Important

Frequently asked questions

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