issue-fields-migration▌
github/awesome-copilot · updated Apr 8, 2026
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Issue fields 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.
Issue Fields Migration
Issue fields 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/highinto 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)
ghCLI 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/projects-api.md, and references/labels-api.md for full API details.
Workflow
Step 0: Migration Source
Ask the user what they are migrating:
-
"Are you migrating labels or project fields?"
- Labels: proceed to the Label Migration Flow below.
- Project fields: proceed to the Project Field Migration Flow below.
-
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")
-
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 map to single_select issue fields (each label name maps to one option value).
Phase L1: Input & Label Discovery
- Ask the user for: org name and repo(s) to migrate.
- Fetch labels from each repo:
gh label list -R {owner}/{repo} --limit 1000 --json name,color,description
- Fetch org issue fields:
gh api /orgs/{org}/issue-fields \
-H "X-GitHub-Api-Version: 2026-03-10" \
--jq '.[] | {id, name, content_type, options: [.options[]?.name]}'
-
Filtering (for repos with many labels): if the repo has 50+ labels, group by common prefix (e.g.,
priority-*,team-*,type-*) or color. Let the user filter with "show labels matching priority" or "show blue labels" before mapping. Never dump 100+ labels at once. -
Ask the user which labels map to which issue field and option. Support these patterns:
- Single label to single field: e.g., label "bug" → Type field, "Bug" option
- Multiple labels to one field (bulk): e.g., labels p0, p1, p2, p3 → Priority field with matching options
- Multiple labels to multiple fields: e.g., p1 → Priority + frontend → Team. Handle as separate mapping groups.
-
Auto-suggest mappings: for each label, attempt to match issue field options using these patterns (in order):
- Exact match (case-insensitive): label
Bug→ optionBug - Prefix-number (
{prefix}-{n}→{P}{n}): labelpriority-1→ optionP1 - Strip separators (hyphens, underscores, spaces): label
good_first_issue→ optionGood First Issue - Substring containment: label
type: bug→ optionBug
Present all suggestions at once for the user to confirm, correct, or skip.
- Exact match (case-insensitive): label
Example output:
Labels in github/my-repo (showing relevant ones):
p0, p1, p2, p3, bug, enhancement, frontend, backend
Org issue fields (single_select):
Priority: Critical, P0, P1, P2, P3
Type: Bug, Feature, Task
Team: Frontend, Backend, Design
Suggested mappings:
Label "p0" → Priority "P0"
Label "p1" → Priority "P1"
Label "p2" → Priority "P2"
Label "p3" → Priority "P3"
Label "bug" → Type "Bug"
Label "frontend" → Team "Frontend"
Label "backend" → Team "Backend"
Label "enhancement" → (no auto-match; skip or map manually)
Confirm, adjust, or add more mappings?
Phase L2: Conflict Detection
After finalizing the label-to-option mappings, check for conflicts. A conflict occurs when an issue has multiple labels that map to the same issue field (since single_select fields can hold only one value).
- Group label mappings by target issue field.
- For each field with multiple label sources, note the potential for conflicts.
- Ask the user for a conflict resolution strategy:
- First match: use the first matching label found (by order of label mapping list)
- Skip: skip issues with conflicting labels and report them
- Manual: present each conflict for the user to decide
Example:
Potential conflict: labels "p0" and "p1" both map to the Priority field.
If an issue has both labels, which value should win?
Options:
1. First match (use "p0" since it appears first in the mapping)
2. Skip conflicting issues
3. I'll decide case by case
Phase L3: Pre-flight Checks & Data Scan
- For each repo, verify write access and cache the
repository_id:
gh api /repos/{owner}/{repo} --jq '{full_name, id, permissions: .permissions}'
- For each label in the mapping, fetch matching issues:
gh issue list -R {owner}/{repo} --label "{label_name}" --state all \
--json number,title,labels,type --limit 1000
Warning: --limit 1000 silently truncates results. If you expect a label may have more than 1000 issues, paginate manually or verify the total count first (e.g., gh issue list --label "X" --state all --json number | jq length).
PR filtering: gh issue list returns both issues and PRs. Include type in the --json output and filter for type == "Issue" if the user only wants issues migrated.
-
If all selected labels return 0 issues, stop and tell the user. Suggest: try different labels, check spelling, or try a different repository. Do not proceed with an empty migration.
-
For multi-repo migrations, repeat across all specified repos.
-
For each issue found:
- Check if the issue already has a value for the target issue field (skip if set).
- Detect multi-label conflicts (issue has two labels for the same field).
- Apply the conflict resolution strategy chosen in Phase L2.
- Classify: migrate, skip (already set), skip (conflict), or skip (no matching label).
Phase L4: Preview / Dry-Run
Present a summary before any writes.
Example preview:
Label Migration Preview
Source: labels in github/my-repo
Target fields: Priority, Type, Team
| Category | Count |
|-------------------------|-------|
| Issues to migrate | 156 |
| Already set (skip) | 12 |
| Conflicting labels (skip)| 3 |
| Total issues with labels| 171 |
Label breakdown:
"p1" → Priority "P1": 42 issues
"p2" → Priority "P2": 67 issues
"p3" → Priority "P3": 38 issues
"bug" → Type "Bug": 9 issues
Sample changes (first 5):
github/my-repo#101: Priority → "P1"
github/my-repo#203: Priority → "P2", Type → "Bug"
github/my-repo#44: Priority → "P3"
github/my-repo#310: Priority → "P1"
github/my-repo#7: Type → "Bug"
After migration, do you also want to remove the migrated labels from issues? (optional)
Estimated time: ~24s (156 API calls at 0.15s each)
Proceed?
Phase L5: Execution
- For each issue to migrate, write the issue field value (same endpoint as project field migration):
echo '{"issue_field_values": [{"field_id": FIELD_ID, "value": "OPTION_NAME"}]}' | \
gh api /repositories/{repo_id}/issues/{number}/issue-field-values \
-X POST \
-H "X-GitHub-Api-Version: 2026-03-10" \
--input -
Replace FIELD_ID with the integer field ID (e.g., 1) and OPTION_NAME with the option name string.
- If the user opted to remove labels, remove each migrated label after successful field write:
gh api /repos/{owner}/{repo}/issues/{number}/labels/{label_name} -X DELETE
URL-encode label names that contain spaces or special characters.
- Pacing: 100ms delay between calls. Exponential backoff on HTTP 429 (1s, 2s, 4s, up to 30s).
- Progress: report every 25 items (e.g., "Migrated 75/156 issues...").
- Error handling: log failures but continue. Include label removal failures separately.
- Final summary:
Label Migration Complete
| Result | Count |
|-----------------------|-------|
| Fields set | 153 |
| Labels removed | 153 |
| Skipped | 15 |
| Failed (field write) | 2 |
| Failed (label remove) | 1 |
Failed items:
github/my-repo#501: 403 Forbidden (insufficient permissions)
github/my-repo#88: 422 Validation failed (field not available on repo)
github/my-repo#120: label removal failed (404, label already removed)
Project Field Migration Flow
Use this flow when the user wants to copy values from a GitHub Project V2 field to the corresponding org-level issue field.
Follow these six phases in order. Always preview before executing.
Phase P1: Input & Discovery
- Ask the user for: org name and project number (or project URL).
- Fetch project fields:
# Use MCP tool
mcp__github__projects_list(owner: "{org}", project_number: {n}, method: "list_project_fields")
- Fetch org issue fields:
gh api /orgs/{org}/issue-fields \
-H "X-GitHub-Api-Version: 2026-03-10" \
--jq '.[] | {id, name, content_type, options: [.options[]?.name]}'
-
Filter out proxy fields: after issue fields are enabled on a project, some project fields appear as "proxy" entries with empty
options: []for single-select types. These mirror the real issue fields and should be ignored. Only match against project fields that have actual option values. -
Auto-match fields by name (case-insensitive) with compatible types:
| Project Field Type | Issue Field Type | Compatible? |
|---|---|---|
| TEXT | text | Yes, direct copy |
| SINGLE_SELECT | single_select | Yes, option mapping needed |
| NUMBER | number | Yes, direct copy |
| DATE | date | Yes, direct copy |
| ITERATION | (none) | No equivalent; skip with warning |
- Present the proposed field mappings as a table. Let the user confirm, adjust, or skip fields.
Example output:
Found 3 potential field mappings:
| # | Project Field | Type | Issue Field | Status |
|---|-------------------|---------------|--------------------|------------|
| 1 | Priority (renamed) | SINGLE_SELECT | Priority | Auto-match |
| 2 | Due Date | DATE | Due Date | Auto-match |
| 3 | Sprint | ITERATION | (no equivalent) | Skipped |
Proceed with fields 1 and 2? You can also add manual mappings.
Phase P2: Option Mapping (single-select fields only)
For each matched single-select pair:
- Compare option names between the project field and issue field (case-insensitive).
- Auto-match options with identical names.
- For any unmapped project field options, present all unmapped options in a single summary and ask the user to provide mappings for all of them at once. Do not prompt one-by-one; batch them into a single exchange.
- Show the final option mapping table for confirmation.
Example output:
Option mapping for "Release - Target":
Auto-matched (case-insensitive):
"GA" → "GA"
"Private Preview" → "Private Preview"
"Public Preview" → "How to use issue-fields-migration on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add issue-fields-migration
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches issue-fields-migration from GitHub repository github/awesome-copilot and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate issue-fields-migration. Access the skill through slash commands (e.g., /issue-fields-migration) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★61 reviews- ★★★★★Yusuf Iyer· Dec 28, 2024
issue-fields-migration has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Layla Choi· Dec 20, 2024
issue-fields-migration has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Pratham Ware· Dec 16, 2024
Keeps context tight: issue-fields-migration is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Isabella Torres· Dec 12, 2024
Solid pick for teams standardizing on skills: issue-fields-migration is focused, and the summary matches what you get after install.
- ★★★★★Chaitanya Patil· Dec 8, 2024
issue-fields-migration reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Piyush G· Nov 27, 2024
I recommend issue-fields-migration for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Yusuf Srinivasan· Nov 19, 2024
issue-fields-migration fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Diego Okafor· Nov 15, 2024
Keeps context tight: issue-fields-migration is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Nikhil Verma· Nov 15, 2024
issue-fields-migration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Yuki Torres· Nov 11, 2024
issue-fields-migration fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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