SQLMesh/sqlmesh - Open Source PR Review Scorecard

Scalable and efficient data transformation framework - backwards compatible with dbt.

C-Rank Grade: A (Welcoming) - 61/100

External PR Merge Rate: 43%

Response Time: 4h

First Timer Success: 64%

Frequently Asked Questions

Is SQLMesh/sqlmesh welcoming to first-time open-source contributors?

SQLMesh/sqlmesh has a recorded first-timer success rate of 63.6%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in SQLMesh/sqlmesh respond to incoming external pull requests in approximately 4.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 61.4 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 61.4 places SQLMesh/sqlmesh in the A tier.

What is the external contributor pull request merge rate for SQLMesh/sqlmesh?

The external contributor pull request merge rate for SQLMesh/sqlmesh is 43.3%, based on public PR activity from non-core contributors.

Are there Good First Issues available in SQLMesh/sqlmesh?

SQLMesh/sqlmesh currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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SQLMesh

SQLMesh/sqlmesh

3,308
Active (30d)A•Welcoming(61/100)Python

Scalable and efficient data transformation framework - backwards compatible with dbt.

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AI Maintainer Review Guidelines

Review Persona

Active Open-Source Maintainer

Warmth Score
7.8/10
Patience Score
8.2/10
Nitpick Rate
20%

Active maintainer team in SQLMesh/sqlmesh welcoming community pull requests and bug fixes.

Top PR Submission Do's

  • •Ensure code complies with repository style conventions
  • •Keep PRs focused and well-documented

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without context
  • •Do not break existing automated test suites
Response Velocity
4 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
43.3%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
63.6%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
40 core
Highly collaborative maintainer core
Diagnostic Health HUD
43.3%
Merge Gauge
63.6%
1st-Timer
Community Vibe63/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for SQLMesh/sqlmesh
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/SQLMesh/sqlmesh)](https://getmerged.abhishekco.de/SQLMesh/sqlmesh?utm_source=github&utm_medium=badge)

Active Good First Issues (1)

View on GitHub

Link: https://github.com/SQLMesh/sqlmesh/actions/runs/32525879293/job/96916106956 Two Issues that are failing the Fabric Tests. These are code based. AI Notes 1 Failing tests tests/core/engine_adapter/integration/test_integration_fabric.py::test_create_drop_catalog tests/core/engine_adapter/integration/test_integration.py::test_janitor[fabric-catalog] What’s Wrong Creating a Fabric warehouse that already exists should do nothing. Fabric used to return HTTP 400 for that; now it returns 409. Our code only handles 400, so it crashes. Possible Fix In sqlmesh/core/engine_adapter/fabric.py (create_warehouse): treat “already exists” (ItemDisplayNameAlreadyInUse) on 409 the same way as 400. 2 Failing tests tests/core/engine_adapter/integration/test_integration.py::test_catalog_operations[fabric] tests/core/engine_adapter/integration/test_integration.py::test_get_data_objects[[query]fabric] tests/core/engine_adapter/integration/test_integration.py::test_get_data_objects[[df-pandas]fabric]

📅 Opened Aug 21, 2026💬 2 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for SQLMesh/sqlmesh

When evaluating whether to contribute to SQLMesh/sqlmesh, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of SQLMesh/sqlmesh acknowledge new external contributions in approximately 4 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 43.3% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to SQLMesh/sqlmesh

01

Is SQLMesh/sqlmesh welcoming to first-time open-source contributors?

SQLMesh/sqlmesh has a recorded first-timer success rate of 63.6%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~4 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 61.4 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 61.4 places SQLMesh/sqlmesh in the Welcoming tier.

04

What is the external contributor pull request merge rate for SQLMesh/sqlmesh?

The external pull request merge rate is 43.3%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in SQLMesh/sqlmesh?

Yes, SQLMesh/sqlmesh currently has 1 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for SQLMesh/sqlmesh are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.