MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Issue-Fields-Migration

Issue-Fields-Migration是一款writing方向的AI技能,核心价值是Bulk-migrate metadata to GitHub issue fields from two sources: repo labels (e,可用于解决开发者在writing领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。

Bulk-migrate metadata to GitHub issue fields from two sources: repo labels (e.g. priority labels to a Priority field) and Project V2 fields. Use when users say "migrate my labels to issue fields", "mi

Last verified on: 2026-05-30
mkdir -p ./skills/issue-fields-migration && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/issue-fields-migration/SKILL.md -o ./skills/issue-fields-migration/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Issue Fields Migration


[Issue fields](https://github.blog/changelog/2026-03-12-issue-fields-structured-issue-metadata-is-in-public-preview/) are org-level typed metadata (single select, text, number, date) that replace label-based workarounds with structured, searchable, cross-repo fields. Every organization gets `Priority`, `Effort`, `Start date`, and `Target date` preconfigured, with support for up to 25 custom fields.


This skill bulk-migrates existing metadata into issue fields from two sources:


- **Repo labels**: Convert labels like `p0`, `p1`, `priority/high` into structured issue field values (e.g. the Priority field). Supports migrating multiple labels at once and optionally removing them after migration.

- **Project V2 fields**: Copy field values (single select, text, number, date, iteration) from a GitHub Project into the equivalent org-level issue fields.


When to Use


- User added org-level issue fields that overlap with existing project fields

- User wants to copy values from project fields to issue fields before deleting the old project fields

- User asks about "migrating", "transferring", or "copying" project field data to issue fields

- User wants to convert repo labels (e.g., p0, p1, p2, p3) into issue field values (e.g., Priority field)

- User asks about replacing labels with issue fields or cleaning up labels after adopting issue fields


Prerequisites


- The target org must have issue fields enabled

- The issue fields must already exist at the org level

- For project field migration: issue fields must be added to the project

- For label migration: labels must exist on the target repo(s)

- The user must have write access to the repos (and project, if migrating project fields)

- `gh` CLI must be authenticated with appropriate scopes


Available Tools


MCP Tools (read operations)


| Tool | Purpose |

|------|---------|

| `mcp__github__projects_list` | List project fields (`list_project_fields`), list project items with values (`list_project_items`) |

| `mcp__github__projects_get` | Get details of a specific project field or item |


CLI / REST API


| Operation | Command |

|-----------|---------|

| List org issue fields | `gh api /orgs/{org}/issue-fields -H "X-GitHub-Api-Version: 2026-03-10"` |

| Read issue field values | `gh api /repos/{owner}/{repo}/issues/{number}/issue-field-values -H "X-GitHub-Api-Version: 2026-03-10"` |

| Write issue field values | `gh api /repositories/{repo_id}/issues/{number}/issue-field-values -X POST -H "X-GitHub-Api-Version: 2026-03-10" --input -` |

| Get repository ID | `gh api /repos/{owner}/{repo} --jq .id` |

| List repo labels | `gh label list -R {owner}/{repo} --limit 1000 --json name,color,description` |

| List issues by label | `gh issue list -R {owner}/{repo} --label "{name}" --state all --json number,title,labels --limit 1000` |

| Remove label from issue | `gh api /repos/{owner}/{repo}/issues/{number}/labels/{label_name} -X DELETE` |


See [references/issue-fields-api.md](references/issue-fields-api.md), [references/projects-api.md](references/projects-api.md), and [references/labels-api.md](references/labels-api.md) for full API details.


Workflow


Step 0: Migration Source


Ask the user what they are migrating:


1. **"Are you migrating labels or project fields?"**

- **Labels**: proceed to the [Label Migration Flow](#label-migration-flow) below.

- **Project fields**: proceed to the [Project Field Migration Flow](#project-field-migration-flow) below.


2. If the user says **labels**:

- Ask: "Which org and repo(s) contain the labels?"

- Ask: "Which labels do you want to migrate?" (they can name them or say "show me the labels first")


3. If the user says **project fields**:

- Ask: "Can you share the link to your project or tell me the org name and project number?"

- Ask: "Which field do you want to migrate?"


---


Label Migration Flow


Use this flow when the user wants to convert repo labels into issue field values. Labels can only

🎯 Best For

  • Claude users
  • GitHub Copilot users
  • Content creators
  • Writers
  • Editors

💡 Use Cases

  • Content creation
  • Style guide enforcement

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Issue-Fields-Migration to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

Can Issue-Fields-Migration maintain my brand voice?

Yes — provide style guides or example content in your prompt for consistent brand-aligned output.

How do I install Issue-Fields-Migration?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/issue-fields-migration/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Publishing unedited drafts

AI writing needs human editing for facts, flow, and authentic voice.

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