EKKOLearnAI/ekko-studio - Open Source PR Review Scorecard

Ekko Studio is a local-first AI workspace for multi-agent chat, coding, and visual workflows, available on desktop and the web.

C-Rank Grade: B (Solid) - 49/100

External PR Merge Rate: 6%

Response Time: 3d

First Timer Success: -

Frequently Asked Questions

Is EKKOLearnAI/ekko-studio welcoming to first-time open-source contributors?

EKKOLearnAI/ekko-studio has a recorded first-timer success rate of 0.0%. 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 EKKOLearnAI/ekko-studio respond to incoming external pull requests in approximately 60.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 49.2 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 49.2 places EKKOLearnAI/ekko-studio in the B tier.

What is the external contributor pull request merge rate for EKKOLearnAI/ekko-studio?

The external contributor pull request merge rate for EKKOLearnAI/ekko-studio is 5.9%, based on public PR activity from non-core contributors.

Are there Good First Issues available in EKKOLearnAI/ekko-studio?

EKKOLearnAI/ekko-studio does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

EKKOLearnAI
EKKOLearnAI/ekko-studioB•Solid11.4k
GitHub
Back to Explorer
EKKOLearnAI

EKKOLearnAI/ekko-studio

11,355
Active (30d)B•Solid(49/100)Low Sample (<20 PRs)TypeScript

Ekko Studio is a local-first AI workspace for multi-agent chat, coding, and visual workflows, available on desktop and the web.

GitHub
Compare••
Jump to:

AI Maintainer Review Guidelines

Review Persona

Strict Architecture Gatekeeper

Warmth Score
7.2/10
Patience Score
8.0/10
Nitpick Rate
25%

Strict review standards in EKKOLearnAI/ekko-studio. Ensure PR scope matches issue requirements closely before requesting review.

What Contributors Actually Say

Discussions in EKKOLearnAI/ekko-studio focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.

Hidden Friction Signals

Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.

Unwritten Rules

  • •1) Keep PR scope strictly aligned with the linked issue.
  • •2) Ensure local linters pass before opening a review.
  • •3) Maintain full test coverage for modified logic.

Top PR Submission Do's

  • •Add or update tests for changed behavior before requesting review
  • •Link the issue and include reproduction context in the PR
  • •Keep PRs small and focused on one change

Top PR Friction Pitfalls (Don'ts)

  • •Do not leave requested test coverage unresolved
  • •Do not open context-free PRs
  • •Do not mix unrelated refactors with feature work
Response Velocity
2 days+
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
5.9%
Selective PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
0.0%
No first-timer merges recorded in window

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
6 core
Highly collaborative maintainer core
Diagnostic Health HUD
5.9%
Merge Gauge
0.0%
1st-Timer
Community Vibe2/100

Embed C-Rank Badge

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

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

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for EKKOLearnAI/ekko-studio.

View all good first issues directly on GitHub

Looking for more TypeScript beginner tasks?Explore TypeScript 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 EKKOLearnAI/ekko-studio

When evaluating whether to contribute to EKKOLearnAI/ekko-studio, 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 EKKOLearnAI/ekko-studio acknowledge new external contributions in approximately 2 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 5.9% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to EKKOLearnAI/ekko-studio

01

Is EKKOLearnAI/ekko-studio welcoming to first-time open-source contributors?

EKKOLearnAI/ekko-studio has a recorded first-timer success rate of 0.0%. 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 ~2 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 49.2 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 49.2 places EKKOLearnAI/ekko-studio in the Solid tier.

04

What is the external contributor pull request merge rate for EKKOLearnAI/ekko-studio?

The external pull request merge rate is 5.9%. 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 EKKOLearnAI/ekko-studio?

EKKOLearnAI/ekko-studio 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 EKKOLearnAI/ekko-studio 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.