perf-check

SKILL运维和基础设施
运维和基础设施 未标注权限 许可证不明确
安装这个技能

Machine performance check: read-only sampling diagnosis of the dev machine's speed — memory pressure (MemAvailable gauge, swap thrash rate), CPU (load vs cores, utilization sampling), WSL2 resource tuning (cgroup ceilings, .wslconfig with autoMemoryReclaim advice), disk IO await per device, top CPU/memory processes, and macOS memory pressure (compressor gauge). Judgements follow the USE method; every threshold carries a basis tag (consensus vs heuristic). Read-only, tuning suggestions are commands for the user — never executed. Use when the machine feels slow, builds stall, memory pressure or swap activity is suspected, a process eats CPU/memory, disk latency is suspect, or WSL2 vmmem/VM sizing needs review. NOT for: runnability checks (env-check), application load testing, or AI session health.

一句话选型结论

按资料字段整理

perf-check是运维和基础设施类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类运维和基础设施 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_692c63a9/perf-check
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

运维和基础设施
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_692c63a9仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791621819
正文体量7.1 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
查服务与日志

按现象定位服务状态与日志线索。

写部署与巡检脚本

把重复的部署、巡检写成脚本。

故障排查

按步骤排查网络、依赖与配置。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在运维和基础设施场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
perf-check当前 未标注权限 未标注 未标注 未标注 有
Azure 部署 调用外部服务 GitHub 仓库 664.2 万 Codex、Claude、Cursor 有
Azure diagnostics 问题管理 调用外部服务 GitHub 仓库 657.6 万 Codex、Claude、Cursor 有
Azure aigateway 部署 调用外部服务 GitHub 仓库 655.3 万 Codex、Claude、Cursor 有
Azure AI 搜索 调用外部服务 GitHub 仓库 651.4 万 Codex、Claude、Cursor 有
Azure Cloud migrate 部署 调用外部服务 GitHub 仓库 650.7 万 Codex、Claude、Cursor 有

SKILL.md 全文

7.1 KB
模型实际读到的说明书原文,来自技能仓库

Perf Check

Read-only performance diagnosis of the development machine: "is it fast", where env-check answers "can it run". Judgement skeleton is Brendan Gregg's USE method (Utilization / Saturation / Errors per resource). Every threshold is pinned in the script and tagged with its basis: consensus (authoritative) or heuristic (experience line — WARN only, never conclusive alone). Tuning suggestions are commands for the user; nothing is executed, nothing is tuned.

中文速览(Quick Guide)

  • 做什么:只读性能体检(1.1 六维:内存压力/CPU/WSL2 资源配置/磁盘 IO await/TOP 进程/macOS 压力判读),每条判据带 basis 标注(consensus=权威共识/heuristic=经验线),USE 方法骨架。
  • 何时用:「机器怎么这么卡」「构建越跑越慢」「怀疑内存压力/swap 抖动」「WSL2 的 vmmem 是不是又吃爆了」。
  • 核心步骤:跑 scripts/perf-check.py(改过脚本先 --selftest)→ 读 WARN/FAIL(先看 basis=heuristic 的提示「需交叉验证」)→ 把 suggest: 命令原样给用户确认执行(本技能永不代调)→ 平台细节查 references/。
  • 国内可达性边界:全部本地采样(/proc、/sys、/mnt/c 只读),零依赖零网络;微软官方阈值与命令仅作文字引用。

When to Use

  • Machine feels slow, builds progressively slower, compile jobs stall.
  • Suspected memory pressure / swap thrash; WSL2 vmmem size review or VM sizing.
  • NOT for: runnability issues (env-check: dead proxy, missing tools, disk nearly full), application load testing (k6), AI session health (session-health).

Hard Constraints

  1. Read-only — samples /proc, /sys, loadavg; reads Windows-side .wslconfig via /mnt/c. No writes, no sysctl changes, no process kills, no cache drops (drop_caches is a suggestion string only, never run).
  2. Never tune — output suggest: commands as text. The user runs them. No --fix mode (repair actions are system-state changes).
  3. Pinned thresholds with basis tags — PASS/WARN/FAIL logic lives in the script; each finding carries basis: consensus | heuristic. Heuristic WARNs say "cross-check" rather than convict.
  4. Gauge discipline — MemAvailable not MemFree; pswpin/pswpout not pgpgin/out; high buff/cache is healthy, never a finding (it is what free memory is for).

Workflow

  1. Run:
    python3 scripts/perf-check.py # human report (2s sampling window) python3 scripts/perf-check.py --json # machine-readable (schema perf-check/1) python3 scripts/perf-check.py --sample 5 # longer sampling window (0 < s <= 60)
    Exit codes: 0 = no FAIL, 1 = at least one FAIL, 2 = usage error.
  2. Read findings worst-first. For basis=heuristic WARNs, relay the cross-check hint instead of a verdict. Relay suggest: commands as text and wait for the user.
  3. Platform detail: references/checks-linux-wsl.md (Linux/WSL thresholds & sources), references/checks-macos.md (macOS deltas).
  4. Re-run after changes to compare.

Check Matrix

Dimension Checks Level logic (pinned in script)
Memory — available MemAvailable vs MemTotal <5% = FAIL, <10% = WARN, else PASS (basis: heuristic, gauge per proc_meminfo(5))
Memory — swap thrash pswpin/pswpout rate over sampling window both >200 KB/s = FAIL, any direction >100 KB/s = WARN (includes the 100–200 both-directions zone), quiet = PASS (basis: heuristic)
Memory — cgroup ceiling cgroup v2 memory.max/memory.current INFO report (ceiling often < MemTotal on WSL/containers)
CPU — load load1/cores (cgroup cpu.max quota wins as core count) >1.0 = WARN, >0.7 = INFO (basis: consensus, Brendan Gregg)
CPU — utilization /proc/stat double-sample delta >85% = WARN (basis: heuristic)
WSL2 .wslconfig reading (memory/processors/swap/autoMemoryReclaim), official defaults cited INFO + advice; autoMemoryReclaim known-conflict notes are hints, not verdicts
Disk IO — await /proc/diskstats double-sample per physical device (ops-weighted await, top 3) >50ms = FAIL, >10ms = WARN (basis: heuristic; SSD/HDD baselines differ — cross-check)
Top processes ps snapshot, top 3 by CPU and by memory INFO evidence; WARN only if a process holds >70% of memory (killing is the user's call)
macOS memory vm_stat compressor occupation + Swapins/Swapouts delta (needs sysctl + vm_stat) compressor >20% of physical pages = WARN; free-low is normal, never a finding (basis: heuristic)

Deferred (do not improvise): BSD iostat disk gauges for macOS, --fix anything. A future minor version owns them.

Output Contract

Human report: [LEVEL][basis] title + evidence lines + suggest: command. JSON: {&quot;schema&quot;: &quot;perf-check/1&quot;, &quot;platform&quot;: {...}, &quot;basis_legend&quot;: ..., &quot;findings&quot;: [{id, level, title, evidence[], hint, basis}]}. Levels: PASS / INFO / WARN / FAIL / SKIP. Absent signals degrade to SKIP/INFO with the reason — never fabricated.

Platform Test Matrix (evidence-pinned, rule-12 style)

Platform Status Evidence
WSL2 / Linux (this host) tested 2026-10-02 selftest 33/33 (v1.1.0); live run exit=0 with real findings (.wslconfig memory=24GB/processors=12/swap=8GB; autoMemoryReclaim=gradual advice; disk await 0.8ms; process snapshot)
macOS 15.8.1 (x86_64, ssh host mac) tested 2026-10-02 selftest 33/33; normal run exit=0: macOS memory gauge live (compressor %, swap delta), top-process snapshot live, absent-Linux-gauges SKIP with reasons. v1.0.0 macOS runs exposed three real bugs (order-dependent import time, (None,None) bypassing cpu_util guard, run_cmd arity) — all fixed with regression fixtures
Plain Linux (docker ubuntu:24.04) tested 2026-10-02 selftest 33/33; normal run exit=0; wsl=False (no host-kernel false positive with /run/WSL confirmation); disk await + process snapshot live; --json valid

Re-run on new hardware, then update this table with date + findings summary. Absence of a row entry means untested.

Completion Criteria

  • Checker ran with exit code reported; every WARN/FAIL relayed to the user as commands, not executed.
  • No tuning was performed by the agent; nothing outside the working scratch was written.

常见问题

5 问
答案由本站依据条目字段整理
perf-check怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_692c63a9/perf-check。安装方式为未标注。装完刷新技能列表或重开客户端。

perf-check支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

perf-check权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

perf-check收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

perf-check用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。