Contact person: VSCode Extension for Developer Metrics

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Location: Bengaluru, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"looking for vscode extension to be created with the following data to be collected

Developer Productivity Metrics and KPIs
1. Code Activity Metrics (VS Code)- Lines Typed:
Total lines of code manually written.- Lines Copied:
Lines pasted into the editor (vs typed).- Words Typed:
Useful for documentation and comments.- Files Edited:
Number of files modified per day/session.- Files Created/Deleted:
Indicates new feature or cleanup work.- Typing Speed:
Avg. keystrokes per minute during active sessions.- Undo/Redo Count:
Can indicate code trial-and-error or indecisiveness.- Auto-format Triggers:
If code formatting extensions are used.- Build/Run Actions:
Number of times code is built/run locally.- Search Activity:
Frequency of code/keyword searches.- Snippet Usage:
Custom/user-defined snippet vs native typing.- AI Code Suggestion Acceptances:
Suggestions accepted from Copilot or TabNine.- Refactor Operations:
Usage of automated refactorings like extract method.- Test Runs Triggered:
Indicates TDD behavior or focus on validation.
Developer Productivity Metrics and KPIs
2. AI & Extension Usage Metrics- AI Suggestions Shown vs Accepted:
Total vs accepted Copilot/CodeWhisperer suggestions.- AI Typing Ratio (%):
AI-suggested code as % of total lines.- Extension Usage Frequency:
Active use of extensions like Linting, Prettier, Debuggers.- Extensions Installed/Removed:
Tracks what tooling is in active use.
3. System & Environment Metrics- Idle Time:
Time with no keyboard/mouse activity.- Active Coding Time:
Time spent interacting with VS Code actively.- First Activity Time:
When the developer starts their work.- Last Activity Time:
When the developer ends their work.- System Sleep/Lock Time:
Duration when machine was locked or inactive.- Workspace Switching:
Count of project/directory switches during the day.
4. Terminal Usage Metrics (within IDE)- Terminal Commands Executed:
Total number of CLI commands issued.- Frequent Commands:
Repeated commands (e.g., git, npm, pytest, etc.).- Error Rate from Commands:
How often terminal commands result in errors.
Developer Productivity Metrics and KPIs- Build Failures vs Success:
Ratio of failed to successful builds/tests.
5. Version Control Metrics (Git/GitHub)- Commits per Day:
Raw number of commits.- Lines Added/Removed:
Code churn.- Files Modified per Commit:
Granularity of change.- Commit Frequency (hour-wise):
Distribution of commits through the day.- Commit Message Quality:
Length, structure, and meaning of messages.- PRs Created:
Pull Requests opened by the developer.- PRs Reviewed:
Code reviews provided by the developer.- PR Comments Made:
Total comments and discussions.- PR Merge Time:
Average time for a PR to be merged.- Issue Mentions/Closures:
Issues closed via commits or PRs.- Branching Pattern:
Usage of feature/bugfix branches.- Conflict Frequency:
How often the developer hits merge conflicts.- Linter/CI Failures in PR:
Quality control through lint/test pipelines.
Developer Productivity Metrics and KPIs
6. Outcome-Based Metrics- Feature Delivered Count:
Features marked completed.- Bug Fixes Delivered:
Number of bug-related commits or PRs.- Test Coverage Change:
7. Collaboration Metrics- Code Review Comments Given:
Number of suggestions/improvements made.- Mentions in Comments:

Use AI to speed up and develop this cost effectively." (client-provided description)