github-issue-creatorConvert raw notes, error logs, voice dictation, or screenshots into crisp GitHub-flavored markdown issue reports. Use when the user pastes bug info, error messages, or informal descriptions and wants a structured GitHub issue. Supports images/GIFs for visual evidence.
Install via ClawdBot CLI:
clawdbot install thegovind/github-issue-creatorTransform messy input (error logs, voice notes, screenshots) into clean, actionable GitHub issues.
## Summary
[One-line description of the issue]
## Environment
- **Product/Service**:
- **Region/Version**:
- **Browser/OS**: (if relevant)
## Reproduction Steps
1. [Step]
2. [Step]
3. [Step]
## Expected Behavior
[What should happen]
## Actual Behavior
[What actually happens]
## Error Details
[Error message/code if applicable]
## Visual Evidence
[Reference to attached screenshots/GIFs]
## Impact
[Severity: Critical/High/Medium/Low + brief explanation]
## Additional Context
[Any other relevant details]
Create issues as markdown files in /issues/ directory at the repo root. Use naming convention: YYYY-MM-DD-short-description.md
Be crisp: No fluff. Every word should add value.
Extract structure from chaos: Voice dictation and raw notes often contain the facts buried in casual language. Pull them out.
Infer missing context: If user mentions "same project" or "the dashboard", use context from conversation or memory to fill in specifics.
Placeholder sensitive data: Use [PROJECT_NAME], [USER_ID], etc. for anything that might be sensitive.
Match severity to impact:
Image/GIF handling: Reference attachments inline. Format: !Description
Input (voice dictation):
so I was trying to deploy the agent and it just failed silently no error nothing the workflow ran but then poof gone from the list had to refresh and try again three times
Output:
## Summary
Agent deployment fails silently - no error displayed, agent disappears from list
## Environment
- **Product/Service**: Azure AI Foundry
- **Region/Version**: westus2
## Reproduction Steps
1. Navigate to agent deployment
2. Configure and deploy agent
3. Observe workflow completes
4. Check agent list
## Expected Behavior
Agent appears in list with deployment status, errors shown if deployment fails
## Actual Behavior
Agent disappears from list. No error message. Requires page refresh and retry.
## Impact
**High** - Blocks agent deployment workflow, no feedback on failure cause
## Additional Context
Required 3 retry attempts before successful deployment
Input (error paste):
Error: PERMISSION_DENIED when publishing to Teams channel. Code: 403. Was working yesterday.
Output:
## Summary
403 PERMISSION_DENIED error when publishing to Teams channel
## Environment
- **Product/Service**: Copilot Studio → Teams integration
- **Region/Version**: [REGION]
## Reproduction Steps
1. Configure agent for Teams channel
2. Attempt to publish
## Expected Behavior
Agent publishes successfully to Teams channel
## Actual Behavior
Returns `PERMISSION_DENIED` with code 403
## Error Details
Error: PERMISSION_DENIED
Code: 403
## Impact
**High** - Blocks Teams integration, regression from previous working state
## Additional Context
Was working yesterday - possible permission/config change or service regressionGenerated Mar 1, 2026
Developers and QA engineers can paste error logs or describe bugs from testing to generate structured GitHub issues. This streamlines bug tracking in agile sprints, ensuring all necessary details like environment, steps, and impact are captured without manual formatting.
Support teams can convert customer-reported issues from chat logs or emails into GitHub issues for engineering review. This helps prioritize fixes based on severity and provides clear reproduction steps, reducing back-and-forth communication.
Product managers can input user feedback from surveys or voice notes to create GitHub issues for feature requests or improvements. This organizes informal input into actionable items with impact assessments, aiding backlog prioritization.
Operations teams can use screenshots and logs from system outages to document incidents as GitHub issues. This facilitates post-mortem analysis by structuring details like error codes and visual evidence, improving reliability processes.
Offer a free tier for individual developers with basic issue creation, and premium plans for teams with advanced features like AI-powered context inference and integration with project management tools. Revenue comes from monthly subscriptions based on user seats and usage limits.
Sell annual licenses to large organizations needing custom integrations with internal systems like Jira or Slack. Include dedicated support and enhanced security features for handling sensitive data, with pricing based on the number of repositories or active users.
Provide the skill as an API that other software platforms can embed into their workflows, such as helpdesk or CI/CD tools. Charge based on API call volume or through partnership revenue shares, enabling scalable monetization across ecosystems.
💬 Integration Tip
Integrate this skill into chat interfaces or IDEs to allow users to generate issues directly from their workflow, reducing context switching and improving efficiency.
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