dbt-labs/dbt-core - Open Source PR Review Scorecard

dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

C-Rank Grade: B (Solid) - 55/100

External PR Merge Rate: 35%

Response Time: 14h

First Timer Success: 30%

Frequently Asked Questions

Is dbt-labs/dbt-core welcoming to first-time open-source contributors?

dbt-labs/dbt-core has a recorded first-timer success rate of 29.5%. Repositories ranked B 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 dbt-labs/dbt-core respond to incoming external pull requests in approximately 14.4 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 54.6 C-Rank™ score (B 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 54.6 places dbt-labs/dbt-core in the B tier.

What is the external contributor pull request merge rate for dbt-labs/dbt-core?

The external contributor pull request merge rate for dbt-labs/dbt-core is 34.9%, based on public PR activity from non-core contributors.

Are there Good First Issues available in dbt-labs/dbt-core?

dbt-labs/dbt-core does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

dbt-labs
dbt-labs/dbt-coreB•Solid13.8k
GitHub
Back to Explorer
dbt-labs

dbt-labs/dbt-core

13,793
InactiveB•Solid(55/100)Rust

dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

GitHub
Compare••
Jump to:

AI Maintainer Review Guidelines

Review Persona

Constructive Code Reviewer

Warmth Score
7.4/10
Patience Score
7.8/10
Nitpick Rate
33%

Balanced & professional review environment in dbt-labs/dbt-core. Maintains strict focus on technical quality and test standards.

Top PR Submission Do's

  • •Add unit tests with >80% coverage for modified code paths
  • •Run repository linter and code formatters locally before pushing
  • •Link relevant GitHub issue ID in PR description pre-flight checklist

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without referencing an existing issue
  • •Do not mix refactoring and feature logic into a single commit
  • •Do not ping maintainers repeatedly within 24 hours of opening
Response Velocity
14 hours
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
34.9%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
29.5%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
85 core
Highly collaborative maintainer core
Diagnostic Health HUD
34.9%
Merge Gauge
29.5%
1st-Timer
Community Vibe42/100

Embed C-Rank Badge

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

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

Active Good First Issues (1)

View on GitHub

Summary dbt Fusion's run_results.json artifact has several discrepancies compared to dbt Core's output. Since run_results.json is consumed by downstream tools (CI/CD integrations, dbt Cloud, third-party tools), these differences can cause compatibility issues. Tested with: dbt Core 1.11.7 (dbt-snowflake 1.11.3) dbt Fusion 2.0.0-preview.145 Schema version: v6 (both) Adapter: Snowflake Discrepancies 1. Missing fields on result entries Fusion result entries are missing several fields that Core always includes: Field Core behavior Fusion behavior message Always present. Human-readable summary (e.g. "SUCCESS 32", "INSERT 499", "Got 4 results, configured to fail if != 0", or full error message for failures) Missing entirely compiled Always present. true for models/tests, null for seeds Missing entirely compiled_code Always present. Contains compiled SQL for models/tests, null for seeds Missing entirely batch_results Always present (null for non-batched) Missing entirely fail

📅 Opened Mar 12, 2026💬 14 comments
Quality: 30/100Contribute
Looking for more Rust beginner tasks?Explore Rust GFI

Contributor Community Vibe Feedback

Rate what actually matters after opening a pull request here.

Have you contributed to this repo?

Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.

3 ratings required
Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for dbt-labs/dbt-core

When evaluating whether to contribute to dbt-labs/dbt-core, 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 dbt-labs/dbt-core acknowledge new external contributions in approximately 14 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 34.9% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to dbt-labs/dbt-core

01

Is dbt-labs/dbt-core welcoming to first-time open-source contributors?

dbt-labs/dbt-core has a recorded first-timer success rate of 29.5%. Repositories ranked Solid 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 ~14 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 54.6 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 54.6 places dbt-labs/dbt-core in the Solid tier.

04

What is the external contributor pull request merge rate for dbt-labs/dbt-core?

The external pull request merge rate is 34.9%. 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 dbt-labs/dbt-core?

dbt-labs/dbt-core does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for dbt-labs/dbt-core 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.