Giskard-AI/giskard-oss - Open Source PR Review Scorecard

🐢 Open-Source Evaluation & Testing library for LLM Agents

C-Rank Grade: A (Welcoming) - 57/100

External PR Merge Rate: 61%

Response Time: 1d

First Timer Success: 40%

Frequently Asked Questions

Is Giskard-AI/giskard-oss welcoming to first-time open-source contributors?

Giskard-AI/giskard-oss has a recorded first-timer success rate of 40.0%. 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 Giskard-AI/giskard-oss respond to incoming external pull requests in approximately 28.6 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 57.3 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 57.3 places Giskard-AI/giskard-oss in the A tier.

What is the external contributor pull request merge rate for Giskard-AI/giskard-oss?

The external contributor pull request merge rate for Giskard-AI/giskard-oss is 60.7%, based on public PR activity from non-core contributors.

Are there Good First Issues available in Giskard-AI/giskard-oss?

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

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Giskard-AI/giskard-oss

5,880
InactiveA•Welcoming(57/100)Python

🐢 Open-Source Evaluation & Testing library for LLM Agents

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AI Maintainer Review Guidelines

Review Persona

Strict Quality Architect

Warmth Score
6.6/10
Patience Score
7.2/10
Nitpick Rate
43%

Rigorous architecture standards (66% critical review signals). Ensure PRs strictly follow guidelines before requesting review in Giskard-AI/giskard-oss.

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
1 days+
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
60.7%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
40.0%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
25 core
Highly collaborative maintainer core
Diagnostic Health HUD
60.7%
Merge Gauge
40.0%
1st-Timer
Community Vibe45/100

Embed C-Rank Badge

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GetMerged C-Rank badge for Giskard-AI/giskard-oss
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Active Good First Issues (1)

View on GitHub

Problem The public checks API is async-only. In a normal Python script, users must write asyncio.run(scenario.run()) (and the same applies to Suite and TestCase). This is boilerplate for a common synchronous entry point. Proposed change Add run_sync(...) to the public, user-facing runnable types in giskard-checks: Scenario Suite TestCase Keep the existing async run(...) API unchanged. Use one shared internal helper or mixin so the loop-detection behavior and error message stay consistent. Example: result = scenario.run_sync() results = suite.run_sync(parallel=True, verbose=False) Required behavior In a plain synchronous script or synchronous test, run_sync(*args, **kwargs) returns the same result as asyncio.run(self.run(*args, **kwargs)). It forwards all positional and keyword arguments exactly to run. It must work from a non-main thread that has no running event loop. If called while an asyncio event loop is already running (Jupyter/IPython notebooks, async pytest tests, async web

📅 Opened Aug 20, 2026💬 1 comment
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for Giskard-AI/giskard-oss

When evaluating whether to contribute to Giskard-AI/giskard-oss, 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 Giskard-AI/giskard-oss acknowledge new external contributions in approximately 1 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 60.7% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to Giskard-AI/giskard-oss

01

Is Giskard-AI/giskard-oss welcoming to first-time open-source contributors?

Giskard-AI/giskard-oss has a recorded first-timer success rate of 40.0%. 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 ~1 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 57.3 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 57.3 places Giskard-AI/giskard-oss in the Welcoming tier.

04

What is the external contributor pull request merge rate for Giskard-AI/giskard-oss?

The external pull request merge rate is 60.7%. 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 Giskard-AI/giskard-oss?

Yes, Giskard-AI/giskard-oss 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 Giskard-AI/giskard-oss 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.