💻 Coding & Development

Work on Linear Issue

📁 Coding & Development 👤 Contributed by @DoguD 🗓️ Updated 2026-04-19

The prompt

--- name: work-on-linear-issue description: You will receive a Linear issue id usually on the the form of LLL-XX... where Ls are letters and Xs are digits. Your job is to resolve it on a new branch and open a PR to the branch main. --- You should follow these steps: 1. Use the Linear MCP to get the context of the issue, the issue number is at $0. 2. Start on the latest version of main, do a pull if necesseray. Then create a new branch in the format of claude/<ISSUE ID>-<SHORT 3-4 WORD DESCRIPTION OF THE ISSUE> checkout to this new branch. All your changes/commits should happen on the new branch. 3. Do your research of the codebase with respect to the info of the issue and come up with an implementation plan. While planning if you have any confusions ask for clarifications. Enter to planning after every verification step. 4. Implement while commiting along the way, following git commit best practices. 5. After you think you are done with the issue, with a clear fresh new perspective, re-look at your changes to identify possible issues, bugs, or edge cases. If there is any address them. 6. After you are confident that you have implemented the changes without problems, bugs, etc. create a PR to the main branch.

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🚀 Open in ChatGPT ✨ Open in Claude 💎 Open in Gemini

How to use this prompt

Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.

Which AI model works best

Claude Opus 4 and Sonnet 4.6 generally outperform ChatGPT and Gemini on coding tasks — better reasoning, better at handling long context (full files, multi-file projects), and more honest about uncertainty. ChatGPT is faster for quick snippets; Gemini is best when code involves screenshots or visual context.

How to customize this prompt

Swap the language mentioned in the prompt (Python, JavaScript, etc.) for whichever stack you're on. For debugging or code review, paste your actual code right after the prompt. For generation tasks, specify the framework (React, Vue, Django, FastAPI) and any constraints (max lines, no external libraries, must be async).

Common use cases

Writing production code with strict style requirements
Reviewing pull requests and catching bugs before merge
Converting between languages (Python → TypeScript, for example)
Generating unit tests for existing functions
Explaining unfamiliar codebases to new team members

Variations

Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).