github-issue-creator▌
google-gemini/gemini-cli · updated Apr 8, 2026
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This skill guides the creation of high-quality GitHub issues that adhere to the
- ›repository's standards and use the appropriate templates.
GitHub Issue Creator
This skill guides the creation of high-quality GitHub issues that adhere to the repository's standards and use the appropriate templates.
Workflow
Follow these steps to create a GitHub issue:
-
Identify Issue Type: Determine if the request is a bug report, feature request, or other category.
-
Locate Template: Search for issue templates in
.github/ISSUE_TEMPLATE/.bug_report.ymlfeature_request.ymlwebsite_issue.yml- If no relevant YAML template is found, look for
.mdtemplates in the same directory.
-
Read Template: Read the content of the identified template file to understand the required fields.
-
Draft Content: Draft the issue title and body/fields.
- If using a YAML template (form), prepare values for each
iddefined in the template. - If using a Markdown template, follow its structure exactly.
- Default Label: Always include the
🔒 maintainer onlylabel unless the user explicitly requests otherwise.
- If using a YAML template (form), prepare values for each
-
Create Issue: Use the
ghCLI to create the issue.- CRITICAL: To avoid shell escaping and formatting issues with multi-line Markdown or complex text, ALWAYS write the description/body to a temporary file first.
For Markdown Templates or Simple Body:
# 1. Write the drafted content to a temporary file # 2. Create the issue using the --body-file flag gh issue create --title "Succinct title" --body-file <temp_file_path> --label "🔒 maintainer only" # 3. Remove the temporary file rm <temp_file_path>For YAML Templates (Forms): While
gh issue createsupports--body-file, YAML forms usually expect key-value pairs via flags if you want to bypass the interactive prompt. However, the most reliable non-interactive way to ensure formatting is preserved for long text fields is to use the--bodyor--body-fileif the form has been converted to a standard body, OR to use the--fieldflags for YAML forms.Note: For the
gemini-clirepository which uses YAML forms, you can often submit the content as a single body if a specific field-based submission is not required by the automation. -
Verify: Confirm the issue was created successfully and provide the link to the user.
Principles
- Clarity: Titles should be descriptive and follow project conventions.
- Defensive Formatting: Always use temporary files with
--body-fileto prevent newline and special character issues. - Maintainer Priority: Default to internal/maintainer labels to keep the backlog organized.
- Completeness: Provide all requested information (e.g., version info, reproduction steps).
How to use github-issue-creator 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 github-issue-creator
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches github-issue-creator from GitHub repository google-gemini/gemini-cli 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 github-issue-creator. Access the skill through slash commands (e.g., /github-issue-creator) 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.
List & Monetize Your Skill
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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
4.5★★★★★68 reviews- ★★★★★Chaitanya Patil· Dec 28, 2024
Solid pick for teams standardizing on skills: github-issue-creator is focused, and the summary matches what you get after install.
- ★★★★★Tariq Mensah· Dec 28, 2024
github-issue-creator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Isabella Bhatia· Dec 16, 2024
I recommend github-issue-creator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Dec 8, 2024
github-issue-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Amina Nasser· Dec 8, 2024
github-issue-creator has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Amina Chen· Nov 27, 2024
github-issue-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Piyush G· Nov 19, 2024
We added github-issue-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Neel Nasser· Nov 19, 2024
I recommend github-issue-creator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ishan Nasser· Nov 15, 2024
Useful defaults in github-issue-creator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ishan Farah· Nov 7, 2024
Keeps context tight: github-issue-creator is the kind of skill you can hand to a new teammate without a long onboarding doc.
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