Sync AI development conversations from IDEs or terminals to the cloud. File issues and requests. Benefits developers and operations teams by preserving and sharing knowledge.
git clone https://github.com/specstoryai/getspecstory.githttps://specstory.com
1. **Set up the integration**: Configure your IDE (VS Code, IntelliJ) or terminal to send session data to the cloud. For VS Code, install the 'Cloud Sync' extension. For terminals, use a script like `getsync.sh` that pipes session logs to a cloud endpoint. 2. **Start a debugging session**: Work through the issue in your IDE or terminal as usual. Ensure error messages, code snippets, and context are captured in the session. 3. **Trigger the sync**: Run the command `getsyncstory --issue "Fix memory leak" --team backend --priority high` or use the IDE extension to export the session. The AI will extract the key details and generate a structured issue. 4. **Review and refine**: Open the generated issue in GitHub/Jira. Edit the description to add missing context or clarify steps. Assign the ticket to the relevant team. 5. **Collaborate**: Share the issue link with your team. Use the AI-generated summary to kick off discussions in Slack or Teams, referencing the preserved context. **Tips:** - For terminal sessions, use tools like `script` or `tmux` to capture full session logs before syncing. - Include error messages, stack traces, and relevant logs in the session to ensure the AI captures all critical details. - Use the `--dry-run` flag to preview the generated issue before creating it in your project management tool.
Automatically save every AI interaction during coding sessions for future reference.
Sync local coding history to the cloud for centralized access and organization.
Generate summaries and insights from past AI interactions to improve future coding practices.
Share specific solutions or code snippets with team members directly from the SpecStory interface.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/specstoryai/getspecstoryCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Sync the current development conversation from my [IDE/TERMINAL] to the cloud. Extract the key context, code snippets, and discussion points from the session and create a detailed GitHub issue or Jira ticket titled '[SUMMARY OF ISSUE]'. Include the following details: [BRIEF DESCRIPTION OF PROBLEM], [CODE SNIPPETS OR ERROR MESSAGES], [STEPS TO REPRODUCE], and [SUGGESTED SOLUTIONS]. Tag the relevant team members: [TEAM_NAME].
```markdown
**Title:** Fix Memory Leak in User Authentication Service
**Description:**
During a debugging session in VS Code, we identified a memory leak in the `/api/auth` endpoint that occurs when handling concurrent login requests. The issue was first noticed when the service crashed after 5,000 active users, with the following error in the logs:
```
Error: Heap out of memory
at /app/src/auth/service.js:42:15
at processTicksAndRejections (node:internal:339:5)
```
**Steps to Reproduce:**
1. Deploy the service with the latest `auth-service` image (v2.1.4).
2. Simulate 5,000 concurrent login requests using `autocannon -c 5000 -d 60 http://localhost:3000/api/auth`.
3. Monitor memory usage in Grafana. The service crashes within 2 minutes.
**Code Snippet:**
```javascript
// auth/service.js:42
const authService = async (req, res) => {
const token = jwt.sign({ userId: req.user.id }, process.env.JWT_SECRET, {
expiresIn: '1h',
});
// Memory leak occurs here due to unclosed streams
const stream = fs.createReadStream('/tmp/cache');
stream.pipe(res);
// Missing stream.on('end', () => stream.close());
};
```
**Suggested Solutions:**
1. Close the stream after piping: `stream.on('end', () => stream.close());`
2. Implement a connection pool for file streams.
3. Add memory monitoring to alert on leaks.
**Tags:** #backend #memory-leak #critical
**Assignee:** @dev-team-lead
**Priority:** P1
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