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Capacity And Demand Planning

CommunityPopular
cbrock84
capacity-and-demand-planning

Matches operational capacity to expected demand — forecasting load, sizing teams and systems, managing queues, and deciding when to add capacity. Use this to plan staffing for expected volume, diagnose a queue that keeps growing, size support or fulfillment capacity, or decide whether a bottleneck needs more capacity or better flow.

Overview

Publishercbrock84
Repositoryheadcount
Skill namecapacity-and-demand-planning
Stars
2K
Forks
316
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by cbrock84 on GitHub. Read the source before you install it.

Installation

Install the Capacity And Demand Planning AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cbrock84/headcount/tree/main/plugins/operations/skills/capacity-and-demand-planning
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cbrock84/headcount.git /tmp/headcount
mkdir -p .claude/skills
cp -r /tmp/headcount/plugins/operations/skills/capacity-and-demand-planning .claude/skills/capacity-and-demand-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Capacity And Demand Planning in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Capacity And Demand Planning on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Capacity And Demand Planning is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Capacity and demand planning

This is operational throughput — how much work the organization can absorb. Allocating people across projects is portfolio work, handled in pmo:portfolio-governance.

Forecast demand honestly

Separate the three components, because they need different treatment:

  • Baseline — the steady rate, best estimated from your own history rather than from a plan.
  • Trend — the direction, measured over enough periods to distinguish it from noise.
  • Spikes — launches, seasonality, campaigns, incidents. Known spikes are a planning input; unknown ones are what headroom is for.

Forecast in the unit the work actually arrives in — tickets, orders, shipments, minutes of handling — not in revenue. Revenue divided by an average is a forecast of an average, and averages are where capacity planning goes to die.

Capacity is not headcount

Usable capacity is people multiplied by available hours multiplied by the fraction spent on the work in question. The last term is the one everyone omits and it is rarely above 70%: meetings, training, holiday, and the interruptions that come with the job are real.

Plan against realistic effective capacity. Planning at 100% guarantees the plan fails on its first ordinary week.

Queues tell you before the dashboard does

Utilization above roughly 80% makes wait times rise sharply and non-linearly — a system at 95% is not slightly slower than one at 85%, it is qualitatively worse. This is why "we have spare capacity on paper" coexists with a queue that never clears.

Watch the trend in queue age, not the queue length. A stable-length queue whose oldest item keeps getting older is a queue that is quietly failing its slowest customers.

Add capacity or fix flow

Before adding capacity, establish which it is:

  • Genuine capacity shortfall — arrival rate exceeds service rate at reasonable utilization. Add capacity.
  • Flow problem — rework, handoffs, waiting on another team, batching. Adding capacity here adds cost and often makes throughput worse by increasing coordination. Send this to operations:process-design.

The tell: if work spends most of its life waiting rather than being worked, it is a flow problem.

Sources

references/sources.md in this skill lists the outside authorities that settle the questions here — what each one is authoritative for, and what you may do with it. Check them before answering on anything they cover, and cite what you used. Most are free to read and not free to reproduce; the use note on each is binding.

Never

  • Plan against nominal headcount rather than effective capacity.
  • Run a critical queue at sustained high utilization and treat the wait times as a mystery.
  • Add capacity to a process you have not measured.
  • Forecast in aggregate currency when work arrives in discrete units.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Capacity And Demand Planning AI skill do?

Matches operational capacity to expected demand — forecasting load, sizing teams and systems, managing queues, and deciding when to add capacity. Use this to plan staffing for expected volume, diagnose a queue that keeps growing, size support or fulfillment capacity, or decide whether a bottleneck needs more capacity or better flow.

Why use Capacity And Demand Planning on TypingMind?

Because you install it once and use it with any model. Capacity And Demand Planning is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Capacity And Demand Planning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cbrock84/headcount/tree/main/plugins/operations/skills/capacity-and-demand-planning. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Capacity And Demand Planning?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Capacity And Demand Planning?

As many as you like. As long as a model supports skills, you can use Capacity And Demand Planning with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Capacity And Demand Planning AI skill free?

Yes. It is published on GitHub by cbrock84 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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