capacity-planning-analysis SKILL.md skillA

capacity-planning-analysis from joe-qai/qa-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add joe-qai/qa-skills/capacity-planning-analysis@git:20260915.bc5a8d6

Pins git:20260915.bc5a8d6 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
joe-qai/qa-skills
Path
capacity-planning-analysis/SKILL.md
Versions recorded
2
Latest version
git:20260915.bc5a8d6, committed Sep 15, 2026
First version recorded
Sep 7, 2026
Size
3,625 bytes
Repository stars
25
License
none declared

Use this skill when you need to produce a structured capacity planning report with load models, headroom analysis, scaling triggers, and risk assessment; triggers include 容量规划, 容量分析, 容量规划分析, and capacity planning analysis.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# 容量规划分析

## 何时使用

- 用户提供业务负载、资源利用率或增长假设,需要生成**结构化的容量规划报告**。
- 需要评估现有方案的风险、识别瓶颈、给出扩容建议。

## 输入要求

| 必填 | 字段 | 说明 |
|------|------|------|
| ✅ | 业务场景 | 核心接口/服务、用户量、流量模式 |
| ⬜ | 历史数据 | QPS、并发、响应时间、错误率 |
| ⬜ | 资源信息 | CPU/内存/磁盘/带宽的当前利用率 |
| ⬜ | SLO 目标 | 可用性、响应时间、吞吐量要求 |
| ⬜ | 增长预期 | 用户增长计划、大促/活动信息 |
| ⬜ | 扩缩容策略 | 当前的扩缩容方式和限制 |

## 执行流程

### 1. 输入审计

- 检查业务场景是否清晰(哪些接口、什么流量模式)
- 检查是否有任何量化数据(哪怕是估算)
- 完全无数据时,先列出「假设」和「信息缺口」,再给出受限初版

### 2. 负载建模

基于输入建立负载模型:

| 指标 | 计算方式 | 说明 |
|------|---------|------|
| 峰值 QPS | 日均 × 峰值系数(通常 3-5x) | 无历史数据时用假设 |
| 并发连接数 | QPS × 平均响应时间 | 估算公式 |
| 单请求资源消耗 | CPU/内存/带宽 per request | 基于基准测试 |
| 容量上限 | 单机资源 ÷ 单请求消耗 | 理论最大值 |

### 3. 报告生成

按以下结构生成容量规划报告:

```markdown
# 容量规划报告

## 1. 任务理解
- 目标、对象、成功标准

## 2. 输入审计
- 已确认事实、当前假设、信息缺口、证据质量

## 3. 负载模型
- 峰值与突发、并发和吞吐
- 平均值 vs 峰值

## 4. 容量估算
- 资源瓶颈识别(CPU/内存/磁盘/带宽)
- 安全余量计算(建议 30-50%)
- 当前容量是否满足需求

## 5. 扩容方案
- 扩容触发条件(阈值)
- 扩容方式(水平/垂直/弹性)
- 扩容时效(冷启动时间)

## 6. 风险与优先级
- P0/P1/P2/P3 优先级
- 阻塞条件

## 7. 下一步
- 最小验证动作
- 待确认问题
```

### 4. 报告校验

生成后必须执行以下校验:

- [ ] 区分了「已确认事实」和「当前假设」
- [ ] 有量化的负载模型(QPS、并发、资源消耗)
- [ ] 容量结论关联了 SLO 和验证方式
- [ ] 有安全余量(非刚好够用)
- [ ] 有扩容触发条件和时效
- [ ] 高风险项有优先级和处理建议
- [ ] 无伪精确数字(无数据时给区间)

### 5. 输出交付物
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add joe-qai/qa-skills/capacity-planning-analysis@sha256:0182a825992a378d

The line at the top of this page pins the label git:20260915.bc5a8d6, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_5osgz6vzicpyxemn.svg)](https://markdownregistry.com/a/art_5osgz6vzicpyxemn)

6 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 2 versions of this file, between Sep 7, 2026 and Sep 15, 2026, about one every 8 days.

versioncommittedcommitsizeaudit
git:20260915.bc5a8d6 latest2026-09-15 bc5a8d6 3,625 BA view · diff
git:20260907.af8ce9d2026-09-07 af8ce9d 3,069 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (3625 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

joe-qai/qa-skills · 25 stars · license none declared · pushed 2026-09-29 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_5osgz6vzicpyxemn
GET https://markdownregistry.com/api/v1/resolve?ref=joe-qai/qa-skills/capacity-planning-analysis
GET https://markdownregistry.com/api/v1/blob/0182a825992a378d6f1ce7a91122c3454f8c226606947732e274eb3298ef23f4

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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