macrozheng/mall-swarm - Open Source PR Review Scorecard

mall-swarm是一套微服务商城系统,采用了 Spring Cloud Alibaba、Spring Boot 3.5、Sa-Token、MyBatis、Elasticsearch、Docker、Kubernetes等核心技术,同时提供了基于Vue的管理后台方便快速搭建系统。mall-swarm在电商业务的基础集成了注册中心、配置中心、监控中心、网关等系统功能。

C-Rank Grade: D (Risky) - 8/100

External PR Merge Rate: -

Response Time: -

First Timer Success: -

Frequently Asked Questions

Is macrozheng/mall-swarm welcoming to first-time open-source contributors?

macrozheng/mall-swarm has a recorded first-timer success rate of 0.0%. Repositories ranked D 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 macrozheng/mall-swarm respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 8.0 C-Rank™ score (D 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 8.0 places macrozheng/mall-swarm in the D tier.

What is the external contributor pull request merge rate for macrozheng/mall-swarm?

The external contributor pull request merge rate for macrozheng/mall-swarm is 0.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in macrozheng/mall-swarm?

macrozheng/mall-swarm does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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macrozheng/mall-swarmDRisky13.1k
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macrozheng/mall-swarm

13,066
DRisky(8/100)Java

mall-swarm是一套微服务商城系统,采用了 Spring Cloud Alibaba、Spring Boot 3.5、Sa-Token、MyBatis、Elasticsearch、Docker、Kubernetes等核心技术,同时提供了基于Vue的管理后台方便快速搭建系统。mall-swarm在电商业务的基础集成了注册中心、配置中心、监控中心、网关等系统功能。

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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%

Established Java ecosystem in macrozheng/mall-swarm. Maintains structured code review standards for external contributors.

Top PR Submission Do's

  • Ensure code complies with Java style conventions
  • Keep PRs scoped 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
-
No reviewer activity recorded

Average Response Latency

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

Merge Efficiency
0.0%
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
CRITICAL BUS FACTOR
Single maintainer
No active GitHub maintainers found (may review internally on Gerrit or internal tools)
Diagnostic Health HUD
0.0%
Merge Gauge
0.0%
1st-Timer
Community Vibe0/100

Embed C-Rank Badge

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

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

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for macrozheng/mall-swarm.

View all good first issues directly on GitHub

Looking for more Java beginner tasks?Explore Java 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 macrozheng/mall-swarm

When evaluating whether to contribute to macrozheng/mall-swarm, 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 macrozheng/mall-swarm acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to macrozheng/mall-swarm

01

Is macrozheng/mall-swarm welcoming to first-time open-source contributors?

macrozheng/mall-swarm has a recorded first-timer success rate of 0.0%. Repositories ranked Risky 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 ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 8.0 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 8.0 places macrozheng/mall-swarm in the Risky tier.

04

What is the external contributor pull request merge rate for macrozheng/mall-swarm?

The external pull request merge rate is 0.0%. 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 macrozheng/mall-swarm?

macrozheng/mall-swarm 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 macrozheng/mall-swarm 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.