Files with the highest combination of change frequency and waste ratio. These are candidates for refactoring or closer review.
Cumulative contribution over time. Watch developers race as positions shift month by month.
Commit activity distribution by hour and day of week across all contributors in this repository.
Performance has many faces. Navigara breaks down the effort to visualize what parts of codebase has been changed and where energy flowed. Our Architect AI can break the performance even further into particular components and patterns.
Breakdown of file changes over time. Play the timeline to see how change types evolved across periods.
Monthly overview of bugs introduced and fixed, based on symbol-level commit analysis. Fixes show whether the original author fixed their own bug (self-fix) or someone else did (cross-fix).
Bug attribution uses symbol-level matching from commit history. For each fix commit, we look at the changed symbols (functions, classes, methods) and trace backwards to find who last modified that symbol in a non-fix commit. This person is the probable bug introducer. The algorithm only works when commits have symbol-level data from the Navigara analysis engine โ the coverage rate shows what percentage of fix commits had this data available.
The current metrics model has a semantic inversion: when developer A creates a feature with a bug, they receive grow (positive). When developer B fixes that bug, they receive waste (negative). The bug creator is rewarded while the fixer is penalized. Bug attribution addresses this by explicitly tracking who introduced bugs and who fixed them, providing a more accurate picture of code quality contributions.
Currently computed client-side from commit data. Ideal server-side endpoint:
POST /v1/repositories/{repositoryId}/bug-attributions
Content-Type: application/json
Request:
{
"startTime": "2025-01-01T00:00:00Z",
"endTime": "2025-12-31T23:59:59Z"
}
Response:
{
"totalBugsAttributed": 42,
"selfFixRate": 35,
"coverageRate": 78,
"attributions": [
{
"filePath": "src/lib/auth.ts",
"symbol": "validateToken",
"introducer": { "name": "Alice", "email": "alice@co.com", "commitSha": "abc123" },
"fixer": { "name": "Bob", "email": "bob@co.com", "commitSha": "def456" },
"fixedAt": "2025-06-15T10:30:00Z",
"isSelfFix": false
}
]
}Reclassifies engineering effort based on bug attribution. Commits that introduced bugs are retrospectively counted as poor investments.
Investment Quality reclassifies engineering effort based on bug attribution data. Commits identified as buggy origins (those that introduced bugs later fixed by someone) have their grow and maintenance time moved into the Wasted Time category. Their waste (fix commits) remains counted as productive. All other commits retain their standard classification: grow is productive, maintenance is maintenance, and waste (fixes) is productive.
The standard model classifies commits as Growth, Maintenance, or Fixes. Investment Quality adds a quality lens: a commit that introduced a bug is retrospectively counted as a poor investment โ the engineering time spent on it was wasted because it ultimately required additional fix work. Fix commits (Fixes in the standard model) are reframed as productive, because fixing bugs is valuable work.
Currently computed client-side from commit and bug attribution data. Ideal server-side endpoint:
POST /v1/organizations/{orgId}/investment-quality
Content-Type: application/json
Request:
{
"startTime": "2025-01-01T00:00:00Z",
"endTime": "2025-12-31T23:59:59Z",
"bucketSize": "BUCKET_SIZE_MONTH",
"groupBy": ["repository_id" | "deliverer_email"]
}
Response:
{
"productivePct": 74,
"maintenancePct": 18,
"wastedPct": 8,
"buckets": [
{
"bucketStart": "2025-01-01T00:00:00Z",
"productive": 4.2,
"maintenance": 1.8,
"wasted": 0.6
}
]
}Latest analyzed commits in this repository.
| Hash | Message | Author | Effort |
|---|
Average context complexity and engagement score of file changes over time. Higher complexity means more intricate changes; higher impact means broader effect on the codebase.
| 7be1372 | post release cleanup | Sunil Pai | โ |
| c6ebfe7 | Version Packages (#1238) | github-actions[bot] | โ |
| 809f4dd | Fix stop() for tool continuation streams; fix orphaned continuation hibernation (#1234) | whoiskatrin | maint |
| 2713c45 | Fix duplicate assistant messages during overlapping submits (#1232) | whoiskatrin | maint |
| 4f79280 | fix(ai-chat): strip messageId from continuation start chunks (#1229) (#1235) | whoiskatrin | maint |
| b20b047 | post release fix npm i and format | Sunil Pai | โ |
| d8cb148 | Version Packages (#1221) | github-actions[bot] | โ |
| 28925b6 | Add message concurrency controls to AIChatAgent (#1192) | whoiskatrin | maint |
| 599390c | Fix cache key to ignore query params (#1225) | Sunil Pai | maint |
| 53f27b1 | feat(ai-chat): add onChatResponse hook + client streaming indicators (#1228) | Sunil Pai | maint |
post release cleanup
Version Packages (#1238)
Fix stop() for tool continuation streams; fix orphaned continuation hibernation (#1234)
Fix duplicate assistant messages during overlapping submits (#1232)
fix(ai-chat): strip messageId from continuation start chunks (#1229) (#1235)
post release fix npm i and format
Version Packages (#1221)
Add message concurrency controls to AIChatAgent (#1192)
Fix cache key to ignore query params (#1225)
feat(ai-chat): add onChatResponse hook + client streaming indicators (#1228)
Repository
agents
Build and deploy AI Agents on Cloudflare
Average Developer Performance (ETV)
Year-by-year Trend:+1986%Contributors ranked by total performance (ETV) from analyzed commits.
| # | |||||
|---|---|---|---|---|---|
| 1 | Sunil Pai623 commits | 75.2 | 38.3 | 23.5 | 13.4 |
| 2 | Matt49 commits | 23.3 | 10.7 | 8 | 4.6 |
| 3 | whoiskatrin72 commits | 22.4 | 6.2 | 4.5 | 11.7 |
| 4 | deathbyknowledge1 commits | 5.4 | 2.1 | 1.4 | 1.9 |
| 5 | Naresh12 commits | 4.2 | 0.1 | 1.2 | 2.9 |
| 6 | 6 69480022+muhammad-bin-ali9 commits | 2.2 | 0 | 0 | 2.2 |
| 7 | Jeremy Morrell (Cloudflare)8 commits | 1.7 | 1.2 | 0.1 | 0.4 |
| 8 | 2 249159057+ask-bonk[bot]6 commits | 1.6 | 0 | 0 | 1.6 |
| 9 | C csparks19191 commits | 1.5 | 0.8 | 0.3 | 0.3 |
| 10 | H hey3 commits | 1 | 0 | 0.5 | 0.5 |
| 11 | Rui Figueira7 commits | 0.9 | 0.6 | 0.3 | 0.1 |
| 12 | A alexmj0442 commits | 0.7 | 0 | 0 | 0.6 |
| 13 | N naji2471 commits | 0.5 | 0.1 | 0 | 0.5 |
| 14 | G glen4 commits | 0.5 | 0.5 | 0 | 0.1 |
| 15 | Matt Silverlock5 commits | 0.5 | 0 | 0.3 | 0.1 |
| 16 | D dillon1 commits | 0.5 | 0.2 | 0 | 0.2 |
| 17 | 1 13007539+mrgsub1 commits | 0.3 | 0 | 0.3 | 0 |
| 18 | 1 1339492+jvg1231 commits | 0.3 | 0 | 0.2 | 0 |
| 19 | C csims2 commits | 0.3 | 0 | 0 | 0.2 |
| 20 | B beixiaosheng1 commits | 0.2 | 0 | 0 | 0.2 |
| 21 | Z zeb1 commits | 0.2 | 0.2 | 0 | 0 |
| 22 | B brbeut2 commits | 0.2 | 0.2 | 0 | 0 |
| 23 | T tarush.nagpal71 commits | 0.2 | 0 | 0 | 0.2 |
| 24 | C craig1 commits | 0.2 | 0.2 | 0 | 0 |
| 25 | J jaredhanson1 commits | 0.2 | 0.2 | 0 | 0 |
| 26 | F ferdousbd1 commits | 0.2 | 0 | 0 | 0.2 |
| 27 | A amorriscode2 commits | 0.2 | 0.2 | 0 | 0 |
| 28 | G gaforres1 commits | 0.2 | 0 | 0 | 0.2 |
| 29 | 7 70562937+jerrynh7701 commits | 0.2 | 0.2 | 0 | 0 |
| 30 | L laurynas.keturakis1 commits | 0.1 | 0 | 0.1 | 0 |
| 31 | 6 62088388+maximo-guk2 commits | 0.1 | 0 | 0 | 0.1 |
| 32 | 1 197298026+huecodes1 commits | 0.1 | 0 | 0 | 0.1 |
| 33 | A aihsannergiz1 commits | 0.1 | 0.1 | 0 | 0 |
| 34 | 1 1297478+flouse1 commits | 0.1 | 0 | 0 | 0.1 |
| 35 | B brian1 commits | 0.1 | 0 | 0 | 0.1 |
| 36 | D danieljmerwe2 commits | 0.1 | 0 | 0 | 0 |
| 37 | T timdp1 commits | 0.1 | 0.1 | 0 | 0 |
| 38 | G gingerhendrix1 commits | 0.1 | 0 | 0.1 | 0 |
| 39 | M me1 commits | 0.1 | 0 | 0 | 0.1 |