ccfos/huatuo - Open Source PR Review Scorecard

eBPF-based Linux kernel observability 🚀🚀

C-Rank Grade: A (Welcoming) - 63/100

External PR Merge Rate: 33%

Response Time: -

First Timer Success: 38%

Frequently Asked Questions

Is ccfos/huatuo welcoming to first-time open-source contributors?

ccfos/huatuo has a recorded first-timer success rate of 37.8%. 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 ccfos/huatuo 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 62.7 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 62.7 places ccfos/huatuo in the A tier.

What is the external contributor pull request merge rate for ccfos/huatuo?

The external contributor pull request merge rate for ccfos/huatuo is 33.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in ccfos/huatuo?

ccfos/huatuo currently has 7 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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eBPF-based Linux kernel observability 🚀🚀

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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 Go repository in ccfos/huatuo with ongoing community development and issue triage.

Top PR Submission Do's

  • •Ensure code complies with Go 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
33.0%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
37.8%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
31 core
Highly collaborative maintainer core
Diagnostic Health HUD
33.0%
Merge Gauge
37.8%
1st-Timer
Community Vibe25/100

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GetMerged C-Rank badge for ccfos/huatuo
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Active Good First Issues (5)

View on GitHub

背景 huatuo 目前有 20+ 个 kprobe 挂钩。kprobe 基于 int3 断点陷入 + 单步模拟,单次开销约 0.5–2µs;fentry/fexit 基于 BPF trampoline(内核 5.5+),单次开销约为其 1/5–1/10。在高频挂钩点上,这一差距会转化为可观的 CPU 开销: tcp_v4_rcv —— 逐包触发 account_process_tick —— 每 tick 触发 page_add_new_anon_rmap —— 逐页触发 等等。。。 需求描述 在内核 ≥5.5 且启用 BTF 时,将 kprobe/kretprobe 挂钩自动切换为 fentry/fexit,实现约 5–10 倍的单次挂钩开销下降: 运行时特性探测:internal/bpf/ 增加探测逻辑 —— /sys/kernel/btf/vmlinux 可用(参考 cmd/dropwatch/dropwatch_reason.go:30)且 features.HaveProgramType(ebpf.Tracing) 通过,结果缓存(bpf_features.go:28 的 ProgramProbe 骨架已存在,尚无调用方) C 侧双入口:公共逻辑抽为 static __always_inline helper,每个挂钩同时提供 SEC("kprobe/xxx") 与 SEC("fentry/xxx")

📅 Opened Aug 27, 2026💬 1 comment
Quality: 50/100Contribute

背景 eBPF 观测工具本身会带来一定的性能开销,但当前缺乏系统化的方法对 huatuo 引入的性能影响进行量化评估。用户在选择使用 huatuo 时需要了解其对业务程序的具体影响。 需求描述 设计并实施一套系统化的性能影响评估方案: 基准测试方案设计 CPU 开销:采集使 CPU 使用率增加的百分比 内存开销:huatuo 进程自身内存占用 网络延迟影响:观测对被观测程序网络延迟的增量影响 IO 延迟影响:观测对被观测程序磁盘 IO 的增量影响 多场景测试 空载 vs 高负载场景 单模块 vs 多模块同时采集 容器环境 vs 宿主机环境 自动化与 CI 集成 编写自动化评估脚本 集成到 CI 流水线,每次发布前自动运行 验收标准 基准测试方案设计文档完成 多场景测试数据可重复生成 自动化脚本可正常运行 CI 集成配置完成 意向参与贡献 我有意向参与具体功能的开

📅 Opened Jul 7, 2026💬 1 comment
Quality: 25/100Contribute

背景 OOM(Out Of Memory)Kill 是生产环境中常见但诊断困难的问题,当前 huatuo 对 OOM 事件的支持有限,缺乏足够的上下文信息来快速定位根因。 需求描述 增强 OOM Kill 的诊断能力: 进程语言识别:自动识别被 Kill 进程的开发语言(Java、Go、Python、Node.js 等),便于选择对应的分析工具 退出前 Profiling 快照:在 OOM Kill 发生前触发一次 Profiling 快照,捕获进程最后的性能状态 上下文信息捕获:记录被 Kill 进程的完整 cmdline、环境变量、资源使用情况等信息 OOM 事件与 cgroup 关联:将 OOM 事件与对应的 cgroup(容器)关联,支持容器环境的排查 技术要求 Profiling 快照应在 OOM Kill 发生前尽快完成 采集的数据应自动关联存储 验收标准 OOM 事件可自动检测并记录 被 Kill 进程的语言被正确识别 Profiling 快照可用 上下文信息完整 与 cgroup 关联正确 意向参与贡献

📅 Opened Jul 7, 2026💬 1 comment
Quality: 40/100Contribute

背景 huatuo 已初步支持 Python 内存 Profiling(memray 解码器),但 decoder.go 中存在多处 TODO,功能完整性有待完善。 需求描述 完善 Python 内存 Profiling 能力: 完善 memray 解码器:处理 decoder.go 中的多处 TODO 项 行级分配定位:支持精确到代码行的内存分配定位 codeObject 元信息:解析和展示 codeObject 的完整元信息(文件名、函数名、行号等) 二分搜索优化:对时间戳查找等场景采用二分搜索优化性能 易用性优化:完善错误处理、日志输出、数据格式兼容性 技术要求 保持与现有 memray 格式的兼容性 性能优化不引入回归问题 验收标准 decoder.go 中的 TODO 全部解决 行级分配定位可用 codeObject 元信息完整展示 性能优化生效 意向参与贡献 我有意向参与具体功能的开发实现并将代码贡献回到上游社区

📅 Opened Jul 7, 2026💬 6 comments
Quality: 25/100Contribute

背景 huatuo-apiserver 作为统一的可视化入口,当前功能较为基础,需要增强以满足企业级使用需求。 需求描述 增强 huatuo-apiserver 前端的综合能力: 用户与权限管理(RBAC) 用户注册、登录、角色管理 基于角色的访问控制(RBAC) API 密钥管理 采集任务管理 任务的创建、启停、删除 任务状态监控 采集参数动态配置 多模块集成 Metrics 模块集成 Event Tracing 模块集成 Profiling 模块集成 统一导航和仪表盘 验收标准 RBAC 权限管理可用 采集任务管理 CRUD 完整 三大模块在前端统一集成展示 意向参与贡献 我有意向参与具体功能的开发实现并将代码贡献回到上游社区

📅 Opened Jul 7, 2026💬 1 comment
Quality: 25/100Contribute
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Contributor Compatibility & Review Speed Analysis for ccfos/huatuo

When evaluating whether to contribute to ccfos/huatuo, 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 ccfos/huatuo acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 33.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to ccfos/huatuo

01

Is ccfos/huatuo welcoming to first-time open-source contributors?

ccfos/huatuo has a recorded first-timer success rate of 37.8%. 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 ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 62.7 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 62.7 places ccfos/huatuo in the Welcoming tier.

04

What is the external contributor pull request merge rate for ccfos/huatuo?

The external pull request merge rate is 33.0%. 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 ccfos/huatuo?

Yes, ccfos/huatuo currently has 7 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 ccfos/huatuo 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.