运营产能规划师

SKILL商业运营
商业运营 未标注权限 许可证不明确
安装这个技能

客服/支持/运营团队的产能规划工具:Erlang-C 排队论测算、P90 需求峰值定容、损耗修正 FTE(shrinkage)、利用率风险预警(持续>80%即超载)、含爬坡与流失的季度招聘序列。适用场景:客服排班与编制、支持团队扩容决策、年度人力预算测算。当用户说"客服要多少人 / 排班怎么排 / 团队利用率 / 编制规划 / 产能测算 / 招聘节奏 / 人力预算"时使用。自带 3 个可复算 Python 脚本(标准库、零外联)。注意:本 Skill 面向运营团队产能,不含工程研发效能规划。

一句话选型结论

按资料字段整理

运营产能规划师是商业运营类的 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。

分类商业运营 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
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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_de9e22a1/ops-capacity-planner
  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

商业运营
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_de9e22a1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2026-11-06上游最后核验时间 · 数据更新 2026-11-06
正文体量12.2 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
写运营方案

按目标产出活动方案与执行清单。

分析数据与指标

从报表里找问题、给结论。

整理客户与销售材料

把客户信息与话术整理成可直接用的材料。

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

  • 需要在商业运营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
运营产能规划师当前 未标注权限 未标注 未标注 未标注 有
MX 股票筛选器 联网访问 ClawHub 市场 79.9 万 OpenClaw 有
交易 未标注权限 ClawHub 市场 58.1 万 OpenClaw 有
营销技巧 只读 ClawHub 市场 54.0 万 OpenClaw 有
百灵鸟好 联网访问 GitHub 仓库 52.6 万 Codex、Claude、Cursor 有
股票信息浏览器 接触敏感数据 ClawHub 市场 40.5 万 OpenClaw 有

SKILL.md 全文

12.2 KB
模型实际读到的说明书原文,来自技能仓库

capacity-planner

> 移植说明:本 Skill 收录于 alirezarezvani/claude-skills(MIT 协议),移植到 SkillHub/WorkBuddy 供中文用户使用。scripts/ 下 3 个脚本均通过安全审查(纯标准库、零外联、零写盘);输入输出可要求用中文呈现。

Sizing tool for ops teams that handle queued work — Support, CX,
Customer Success, BizOps, IT ops, Finance ops. Built on Erlang-C
queueing theory, Little's Law, and the operational-leadership canon
(Fournier, Larson, Cleveland, Reinertsen). Deterministic, stdlib-only,
no LLM calls.

Purpose

You are an ops leader sized 15 → 35 with no idea how the 35-person org
will actually behave at peak load. Or you are at 88% utilization and
SLA is starting to slip. Or you have a hiring budget approved and need
to sequence it across four quarters without burning out the existing
team. This skill answers those questions with arithmetic, not vibes.

It produces three artifacts:

  1. Capacity sizing at 70/80/90% utilization against P50/P90/P99
    demand, with P(SLA breach) at each point and a SAFE/WATCH/AT_RISK/CRITICAL
    risk band.
  2. Utilization health at the per-member traffic-light level plus a
    team verdict (HEALTHY/SQUEEZED/OVERLOADED/UNBALANCED).
  3. 12-month quarterly hiring plan accounting for ramp curves,
    attrition, QoQ demand growth, and span-of-control manager triggers.

When to use

  • Annual ops capacity planning (October-November for the following
    fiscal year).
  • Quarterly re-sizing if demand changed >15% or attrition spiked.
  • Pre-budget defense — the math that justifies the headcount ask
    to your CFO.
  • Diagnostic when an ops team is missing SLA and you need to know
    whether it's a sizing problem, a process problem, or a bottleneck
    problem.
  • M&A / new-segment launch modeling — sizing a new team or
    combined org.

Workflow

  1. Intake demand. Pull P50/P90/P99 daily ticket/case volume from
    your work system (Zendesk, Intercom, JSM, ServiceNow, Salesforce).
    If you only have averages, stop and pull the distribution. Single-
    point demand estimates are the most expensive anti-pattern in ops.
  2. Model throughput. Run capacity_modeler.py with your demand,
    AHT, SLA target, current FTE, and shrinkage. Use --profile for
    your function (support / cx / bizops / finance-ops / it-ops). Read
    the 80%-utilization row — that's your sizing point.
  3. Flag utilization risk. Run utilization_analyzer.py against
    your current team's actual utilization data. Anyone >85% sustained
    is a throughput-collapse risk per Reinertsen. Spread >30 percentage
    points across team means UNBALANCED — fix that before hiring.
  4. Sequence hiring. Run hiring_sequencer.py with current FTE,
    target EOY, ramp time, attrition, and growth. It will front-load
    hires (Q1 35%, Q4 15%), apply ramp curves, and trigger a manager
    hire when span of control crosses 7 ICs/manager.
  5. Walk the Forcing-question library (see below). One question at
    a time. Do not skip ahead. Answers must be written down before
    you commit the plan.

Scripts

  • scripts/capacity_modeler.py — Erlang-C sizing with shrinkage
    adjustment and P50/P90/P99 breach probabilities. --profile
    for industry defaults.
  • scripts/utilization_analyzer.py — per-member traffic-light +
    team-level health verdict with variance detection.
  • scripts/hiring_sequencer.py — 12-month quarterly plan with ramp,
    attrition, growth, max-hires-per-quarter constraint, and
    manager-trigger logic.

All three accept --input <path> (JSON), --output {markdown,json},
--sample (built-in example), and --help. Stdlib only.

Quick example

# Emits an Erlang-C capacity model (required headcount + P50/P90/P99 breach probabilities) for the built-in example
cd business-operations/skills/capacity-planner && python3 scripts/capacity_modeler.py --sample

References

  • references/queueing_theory_canon.md — Erlang, Little, Hopp &
    Spearman, Reinertsen, Kingman, Cleveland, ITIL, Armony et al. (8
    sources). The math.
  • references/ops_workforce_planning_canon.md — Fournier, Larson,
    Google SRE Workbook, Frei, Lawler, Bersin, Gartner, Grove (8
    sources). The people factors.
  • references/capacity_anti_patterns.md — 11 named anti-patterns
    with cited sources, tool guards, and the meta-discipline that
    Lencioni + Goldratt + Christensen impose. (8+ named sources.)

Assets

  • assets/capacity_brief_template.md — 20-minute fill-out template
    with JSON skeletons for all three tools and an output checklist.

Assumptions

This skill assumes:

  • Work is queued (tickets, cases, work items) — not project-style.
    If your team's work isn't queued, this is the wrong skill.
  • Demand has a stationary-enough distribution within a quarter.
    Step-changes (new product launch, M&A, regulatory shift) require
    re-running mid-quarter.
  • You have at least 90 days of historical demand data to compute
    P50/P90/P99. If not, generate the distribution from your sales /
    user-base forecast first.
  • Service is single-class within a queue. If you have hard
    priority tiers (P1/P2/P3 with class-specific SLAs), model each as
    a separate queue and sum.
  • Channels are modeled coherently. Multi-channel teams use the
    appropriate --profile with built-in shrinkage premium.

Anti-patterns

See references/capacity_anti_patterns.md for the full taxonomy with
sources. Top eight:

  1. Plan-to-100%-utilization (Reinertsen Principle 12)
  2. Treat-ramp-as-instant (Larson)
  3. Ignore-attrition-in-12-month-plan (Bersin)
  4. Hire-ICs-forever-with-no-manager-trigger (Fournier)
  5. Size-to-P50-demand-only (Cleveland)
  6. No-shrinkage-adjustment (Cleveland, SRE Workbook)
  7. Single-channel-model-for-multi-channel-work (Gartner, Kingman)
  8. No-surge-plan-for-P99-events (Hopp & Spearman, Reinertsen)

Distinct from

  • c-level-advisor/vpe-advisor measures engineering throughput
    via DORA 4 metrics, story points, deployment frequency, and cycle
    time bottlenecks. It is for engineering teams shipping code. This
    skill is for ops teams handling tickets/cases. Different unit of
    work, different math (Erlang-C vs. DORA), different bottleneck
    (queueing-blind staffing vs. WIP + lead time).
  • c-level-advisor/chro-advisor does strategic workforce
    planning (1-5 year capability portfolios, talent supply, leadership
    succession). This skill does operational 0-12 month capacity
    sizing against demand. Per Lawler: conflating them gets you hired
    into the wrong jobs.
  • project-management/* tracks delivery throughput on projects
    (Jira velocity, sprint capacity). This skill sizes around steady-
    state queued work.
  • Sibling process-mapper finds the bottleneck. This skill
    sizes the team around a known bottleneck. Order of operations:
    process-mapper first → capacity-planner second. Hiring around the
    wrong constraint wastes the hires.
  • business-growth/cs-coverage (if it exists) sizes Customer
    Success coverage by ARR/CSM ratio and segment. This skill sizes by
    queued work volume (tickets, cases, escalations). For a CS team
    that handles both relationship work AND a ticket queue, run both.

Forcing-question library (Matt Pocock grill discipline)

Discipline: walk these one at a time. Do not skip ahead. Answers must
be written down. If you can't answer one, that is your next investigation.

Q1 — "What is your bottleneck, and have you confirmed it empirically?"

Recommended answer: a named, measured stage in the workflow with
queue-time data showing where work waits. Not a vibe. Not "escalations
take too long". An actual measured queue.

Why it's the first question: Goldratt (The Goal, 1984) — every
system has exactly one binding constraint at a time. Sizing around the
wrong constraint wastes hires entirely. If you do not know your
bottleneck, run process-mapper BEFORE this skill.

Canon: Eli Goldratt, The Goal (1984); Reinertsen, Principles of
Product Development Flow
(2009).

Q2 — "What service trade-off are you accepting?"

Recommended answer: a written, explicit choice — fast vs. empathetic,
broad vs. deep, low-cost vs. high-quality. Frances Frei is unambiguous:
you cannot win all four. The team that tries wins zero.

Why it matters: AHT, SLA, and shrinkage inputs are the operational
expression of this trade-off. If they don't agree (e.g., you set AHT for
"empathy" but SLA for "speed"), the plan is internally inconsistent.

Canon: Frances Frei & Anne Morriss, Uncommon Service (HBR Press,
2012).

Q3 — "What's your demand P90, and what's the gap to your P99?"

Recommended answer: two specific numbers from the last 90 days of
data, with the calendar context of each (e.g., "P90 was 480 tickets/day
on normal Tuesdays; P99 was 720 on the day after the November release").
A team sized to P50 misses SLA half the time. A team sized to P99
overstaffs by 30-50%. P90 is the right operating sizing point per
Cleveland.

Canon: Brad Cleveland, Call Center Management on Fast Forward (4th
ed., 2019); A.K. Erlang, The Theory of Probabilities and Telephone
Conversations
(1909).

Q4 — "At your planned utilization, what is P(SLA breach) at P90 and at P99?"

Recommended answer: two probabilities, computed (not guessed) from
Erlang-C with your specific N, AHT, and SLA target. If P(breach at P90)
> 10% you are understaffed at the sizing point. If P(breach at P99) >
50% you have no surge plan and the next peak event will be visible to
the CEO.

Canon: Erlang (1909); Hopp & Spearman, Factory Physics (3rd ed.,
2008), VUT equation.

Q5 — "Have you budgeted replacement hires for the attrition you'll see this year?"

Recommended answer: yes, with a specific number. At 30% annual
attrition (Bersin BPO midpoint), a 20-FTE team loses ~6 people this year.
If your "add 5 net" plan is actually a "hire 11" plan, the recruiting
volume changes drastically. Anti-pattern #3.

Canon: Bersin/Deloitte talent benchmarks (2015-2023); Edward Lawler,
Strategic Workforce Planning (USC CEO, 2008).

Q6 — "When does span of control trigger a manager hire, and who is the candidate?"

Recommended answer: a specific quarter (from hiring_sequencer.py)
and at least one identified candidate (internal lead or external hire).
Past 7 ICs/manager, 1:1s degrade, feedback cycles slip, attrition
climbs. Past 10 you have a coverage crisis. Hire the manager BEFORE
crossing 10, not after.

Canon: Camille Fournier, The Manager's Path (O'Reilly, 2017),
ch. 5; Andy Grove, High Output Management (1983).

Q7 — "What is your surge plan for the P99 day?"

Recommended answer: an explicit, documented plan — overflow tier,
BPO contracted capacity, on-call rotation, executive escalation tree,
OR a written degradation contract that says "on P99 days we extend SLA
to X minutes and notify customers proactively". If the answer is "we'll
figure it out", the P99 day is a fire visible to the board.

Canon: Hopp & Spearman, Factory Physics (2008); Reinertsen (2009)
on capacity-margin discipline.


Walk these seven in order. One at a time. Write the answers down. The
plan you submit is only as defensible as your answers to these seven
questions.

常见问题

5 问
答案由本站依据条目字段整理
运营产能规划师怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_de9e22a1/ops-capacity-planner。安装方式为未标注。装完刷新技能列表或重开客户端。

运营产能规划师支持哪些客户端?

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。

运营产能规划师权限高吗,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。

运营产能规划师收费吗?

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。

运营产能规划师用什么许可证?

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 2026-11-06。