Tooljet Engineering Benchmarks
Tooljet delivery benchmarks are based on 188 merged pull requests in the last 30 days (1,481 all-time), with 1.6 hours median cycle time, 2.0 hours median review time, and 27 active contributors. AI-related signals appear on 0.0% of recent work. PR volume is up 4% compared to the prior period.
Repo vs ToolJet Average
Delivery Trend and AI Signals
PR Backlog (Humans)
Excludes AI agents and automation accounts.
PR Backlog (AI Agents)
AI coding agents only.
Cycle Time by AI-Related Signals
PR Breakdown
Top AI Tools
PR Type Breakdown
Recent Pull Requests
View PR Explorer| Title | Author | AI |
|---|---|---|
| DataBricks migration for Main (gitsync) | rudeUltra | — |
| fix: improve Mobile canvas overflow handling in AppCanvas c… | nakulnagargade | — |
| Databricks Revamp Oauth + Design | rudeUltra | — |
| 🚀 chore: update submodules | adishM98 | — |
| Revert "chore: update package-lock.json with new dependenci… | johnsoncherian | — |
Methodology
Metrics are computed from merged pull request data synced daily from GitHub. AI-related metrics are directional signals inferred from pull request activity patterns and heuristics. Summary metrics use a 30-day rolling window; trends use a 90-day window. Last updated 16 hours, 26 minutes ago.
Updated daily from public GitHub pull requests.
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