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Analyze Performance Revenue Join

OrganizationPopular
gooseworks-ai
analyze-performance-revenue-join

Step of the analyze-performance playbook: joins cleaned store or CRM numbers with ad spend to build the business-truth table, MER, new-customer cost and the overclaim ratio. Run analyze-performance instead; not for direct use.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill nameanalyze-performance-revenue-join
Stars
1.3K
Forks
219
Bundled files
1
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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 gooseworks-ai on GitHub. Read the source before you install it.

Installation

Install the Analyze Performance Revenue Join 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/gooseworks-ai/goose-skills/tree/main/skills/marketing/analyze-performance-revenue-join
  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/gooseworks-ai/goose-skills.git /tmp/goose-skills
mkdir -p .claude/skills
cp -r /tmp/goose-skills/skills/marketing/analyze-performance-revenue-join .claude/skills/analyze-performance-revenue-join
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyze Performance Revenue Join 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 Analyze Performance Revenue Join 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 Analyze Performance Revenue Join 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.

Revenue join (atom)

Load: ../analyze-performance/references/revenue-join.md.

Inputs: clean store/CRM numbers; total spend per platform; platform claims; break-even MER and allowable CAC (campaign brief economics box / measurement contract); last week's report (the story the marketer picked).

Do:

  1. Business-truth table: this week, last week, 4-week average, same week last year.
  2. MER, new-customer MER, nCAC, contribution after ads — each vs break-even / allowable / target.
  3. Overclaim ratio, like-for-like as in the reference (claimed purchases ÷ store orders, or claimed revenue ÷ store gross; a floor when a claimant is missing), with its 4-week trend.
  4. Marginal: Δ new-customer revenue ÷ Δ spend vs last week and vs the 4-week average.
  5. If the platform and blended stories point different ways: write both at the same grain, each ending "if true, you'd…", a recommendation, and the cheapest test that would settle it. Carry forward the story the marketer picked last time unless a test changed it.
  6. B2B: pipeline chain and cost per qualified lead / opportunity instead of revenue.

Output: the report's Business truth, overclaim line and Two stories sections.

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 Analyze Performance Revenue Join AI skill do?

Step of the analyze-performance playbook: joins cleaned store or CRM numbers with ad spend to build the business-truth table, MER, new-customer cost and the overclaim ratio. Run analyze-performance instead; not for direct use.

Why use Analyze Performance Revenue Join on TypingMind?

Because you install it once and use it with any model. Analyze Performance Revenue Join 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 Analyze Performance Revenue Join in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/marketing/analyze-performance-revenue-join. 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 Analyze Performance Revenue Join?

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 Analyze Performance Revenue Join?

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

Is the Analyze Performance Revenue Join AI skill free?

Yes. It is published on GitHub by gooseworks-ai 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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