GitHub issue creation skill. Analyzes the entire codebase impact based on user request, then creates a structured issue with AI-verified/human-judgment-needed/caution sections. /issue "issue description" Trigger: "/issue", "이슈 만들어", "issue 만들자", "깃헙 이슈"
Scanned 9/9/2026
npx -y skills add team-attention/hoyeon --skill issue --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: issue
description: |
GitHub issue creation skill. Analyzes the entire codebase impact based on user request,
then creates a structured issue with AI-verified/human-judgment-needed/caution sections.
/issue "issue description"
Trigger: "/issue", "이슈 만들어", "issue 만들자", "깃헙 이슈"
allowed_tools:
- Read
- Grep
- Glob
- Bash
- Agent
- AskUserQuestion
validate_prompt: |
Must complete with one of:
1. GitHub issue created (URL returned)
2. User cancelled after preview
Must NOT: create issue without user confirmation, skip impact analysis.
---
# /issue — Structured GitHub Issue Creator
Investigate the codebase based on the user's request and create a GitHub issue with clearly defined confidence boundaries.
## Input
The text the user typed after `/issue` is the original request. Preserve it verbatim.
Examples:
- `/issue Duplicate Shorts URL fetches in YouTube subscription feed`
- `/issue Add notification settings tab to Settings page`
- `/issue Scheduler occasionally runs twice`
If the input is too vague (e.g., "there's a bug"), ask ONE clarifying question. Otherwise, start investigating immediately.
## Phase 1: Impact Analysis
Perform a **full impact analysis** based on the user's request. Use Agent to investigate in parallel.
### What to Investigate
Launch agents in parallel where possible:
1. **Related code exploration** — Identify files, functions, and modules directly related to the request
2. **Dependency analysis** — Where is this code referenced, and which modules are affected
3. **Existing test coverage** — Whether related tests exist and what they cover
4. **Related issues/history** — Relevant change history from git log, known issues
### Classifying Findings
Classify all findings into three confidence levels:
#### ✅ AI Verified
**Objective facts confirmed through code exploration.** No need for human re-verification.
- Function/file locations, call relationships
- Whether tests exist
- Current behavior (as read directly from code)
- Relevant config values, environment variables
#### 🤔 Decision Required
**Decision points that AI cannot make on your behalf.**
- Trade-off choices (performance vs. accuracy, UX vs. security, etc.)
- Business logic decisions
- Scope decisions (how much to fix)
- Priority judgment
#### ⚠️ Human Verify
**Risks and caveats AI may have missed.**
- Potential side effects
- Risks from production environment differences
- External service dependencies
- Whether data migration is needed
- Areas AI could not verify (external systems, real user data, etc.)
## Phase 2: Preview & Confirm
After investigation, show the user a preview of the issue body.
### Issue Body Template
```markdown
## Request
> {original text the user typed after /issue, verbatim}
## Impact Analysis
### Related Code
- `file:line` — description
- ...
### Scope of Impact
- List of affected modules/features
---
## ✅ AI Verified
> Facts confirmed through code exploration. No further verification needed.
- [ ] Confirmed fact 1
- [ ] Confirmed fact 2
## 🤔 Decision Required
> Decision points requiring human judgment.
- [ ] Decision point 1 — Option A vs B, considerations
- [ ] Decision point 2
## ⚠️ Human Verify
> Risks AI may have missed. Needs human review before and/or after implementation.
- [ ] Verification point 1 — why this needs checking
- [ ] Verification point 2
```
After showing the preview, confirm with AskUserQuestion:
```
AskUserQuestion(
question: "Should I create a GitHub issue with this content?",
header: "Issue Preview",
options: [
{ label: "Create", description: "Create the issue as-is" },
{ label: "Edit then create", description: "I want to make changes first" },
{ label: "Cancel", description: "Do not create the issue" }
]
)
```
- **Create** → Proceed to Phase 3
- **Edit then create** → Incorporate user feedback, then show preview again
- **Cancel** → "Issue creation cancelled." → Stop
## Phase 3: Create Issue
Create the issue with `gh issue create`.
```bash
gh issue create --title "Issue title" --body "$(cat <<'EOF'
Issue body
EOF
)"
```
### Title Rules
- Under 70 characters
- Use a prefix: `feat:`, `fix:`, `refactor:`, `chore:`, etc. (based on content)
- English or Korean OK
### Label Auto-mapping
Based on the issue content, add matching labels via the `--label` flag using the table below.
Multiple labels allowed. If no match, create without labels.
| Issue type | Label |
|-----------|------|
| Bug, error, broken behavior | `bug` |
| New feature, addition, improvement | `enhancement` |
| Documentation related | `documentation` |
| Question, investigation, needs clarification | `question` |
After creation, return the issue URL to the user.
## Hard Rules
1. **Investigate first** — Never create an issue without investigation
2. **Confirm first** — Never create an issue without user confirmation
3. **Preserve original** — The user's original request must be included verbatim in the "Request" section
4. **Facts only** — AI Verified contains only things directly confirmed from code. No speculation.
5. **Be honest** — Anything unverified goes into Human Verify. Never pretend to know.
6. **Keep it concise** — Do not let the issue body grow unnecessarily long
## Checklist Before Stopping
- [ ] Codebase impact analysis completed
- [ ] Findings classified into three confidence levels
- [ ] User's original request included verbatim
- [ ] User reviewed the preview
- [ ] `gh issue create` executed and URL returned (or user cancelled)
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