Customer Story Setup logo

Customer Story Setup

Organization
langfuse
customer-story-setup

Converts draft customer-story Markdown into Langfuse website MDX (Fumadocs), collects missing metadata and assets, wires meta.json and authors. Use when adding or converting a customer case study, user story, or /users page, or when the user mentions customer story setup, cresta/canva-style posts, or CustomerStoryCTA/BlogHeader for customers.

Overview

Publisherlangfuse
Repositorylangfuse-docs
Skill namecustomer-story-setup
Stars
247
Forks
327
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Customer Story Setup 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/langfuse/langfuse-docs/tree/main/.agents/skills/customer-story-setup
  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/langfuse/langfuse-docs.git /tmp/langfuse-docs
mkdir -p .claude/skills
cp -r /tmp/langfuse-docs/.agents/skills/customer-story-setup .claude/skills/customer-story-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Customer Story Setup 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 Customer Story Setup 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 Customer Story Setup 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.

Single source of truth: maintain this skill under .agents/skills/customer-story-setup/ only. Claude and Cursor load projected copies under .claude/skills/customer-story-setup and .cursor/skills/customer-story-setup.

Customer story setup (MD -> MDX)

Turns a plain Markdown draft into content/customers/<slug>.mdx in the same pattern as content/customers/canva.mdx and cresta.mdx.

Before writing any file: collect missing input

Do not guess. If any item below is missing from the user's draft or message, ask explicitly and wait for answers (or confirm defaults).

Content & publishing

TopicAsk
Company nameLegal/marketing name for copy and quotes
Company websitePublic URL for the [Company](https://...) link in About <Company>
SlugFilename: <slug>.mdx (lowercase, hyphens), e.g. cresta -> cresta.mdx
Page titleH1 string for BlogHeader + YAML title (often "How <Company> ... with Langfuse")
Short descriptionYAML description + BlogHeader description (SEO/social; 1-2 sentences)
Publish dateYAML date + BlogHeader date (e.g. March 26, 2026)
OG imageOptional ogImage: path; if unset, leave empty like other stories

Authors (BlogHeader authors={["..."]})

TopicAsk
Byline author(s)Who should appear under the title (keys from data/authors.json)
External / guest speakerIf not in authors.json: collect name, title, optional socials, and headshot path under public/images/people/ or public/images/customers/<slug>/, then add an entry to data/authors.json (see existing entries). Every authors key must resolve in authors.json.

Branding & Users index card

TopicAsk
LogosPaths for customerLogo and customerLogoDark (light + dark mode), usually under public/images/customers/<slug>/
Pull quotecustomerQuote (short, for grid card)
Quote attributionquoteAuthor, quoteRole, quoteCompany
Speaker headshot (optional)quoteAuthorImage for card/SEO if you use the same as Canva
Show on /usersshowInCustomerIndex: true | false

Images (screenshots & diagrams)

Produce a numbered checklist for the user (and keep it in the PR description if useful):

  1. Folder: public/images/customers/<slug>/
  2. For each asset: filename, purpose, where it appears (section + suggested alt text)
  3. Remind: customer posts use <Frame fullWidth> around markdown images, e.g. ![Alt](mdc:/images/customers/<slug>/file.png) per site conventions
  4. Size each image by aspect ratio (run sips -g pixelWidth -g pixelHeight <file> to get dimensions):
    • Portrait / square (ratio <= 1:1) -> <div className="flex justify-center"><Frame fullWidth className="w-1/2">...</Frame></div>
    • Landscape (~1.5:1) -> <div className="flex justify-center"><Frame fullWidth className="w-2/3">...</Frame></div>
    • Panoramic (> 2:1) -> <Frame fullWidth className="w-full">...</Frame> (no centering wrapper needed)

If the draft says "screenshot here" without files, list placeholders in MDX with consistent paths so the user can drop files in later.

Docs links (optional but recommended)

Ask whether to add sparse internal links. Default policy: only link major product concepts (match what we used on Cresta):

Do not pepper every noun with links. Use paths from llms-docs.txt / available-internal-links rule so links resolve.


MDX structure to produce

  1. YAML frontmatter at top: title, date, description, ogImage, tag: customer-story, author (display string if needed), customerLogo, customerLogoDark, optional quote fields, showInCustomerIndex.
  2. Imports: BlogHeader, CustomerQuote (if quote), ImpactChart (if impact section), CustomerStoryCTA; use Frame for images (global in MDX).
  3. BlogHeader: title, description, customerLogo, authors, date; optional image for hero.
  4. Body headings: One conceptual H1 only (from BlogHeader). Body uses ## and ###; do not skip levels.
  5. Quote block: <CustomerQuote quote="..." name="..." role="..." company="..." />
    • align role / company with frontmatter so the byline reads "Name, Role at Company"
    • avoid duplicating company name in role
  6. Images: size by aspect ratio (see checklist item 4 under Images above)
    • portrait/square -> w-1/2 centered
    • landscape -> w-2/3 centered
    • panoramic -> w-full
  7. Closing: <ImpactChart items={[{ area, impact }, ...]} /> (optional) then <CustomerStoryCTA />.

Reference implementations: content/customers/canva.mdx, content/customers/cresta.mdx.


Repo wiring (after MDX exists)

  1. content/customers/meta.json

    • Add "<slug>" to the pages array (with "index" first).
    • Order matters for layout: the Users grid and homepage carousel are sorted by sortCustomerStoriesByMetaOrder in lib/sortCustomerStoriesByMeta.ts, which reads this list. Place the slug where the card should appear (e.g. last in the list = bottom-right in a 2-column grid).
  2. Authors

    • If new author: add to data/authors.json (key must match BlogHeader authors).
  3. Assets

    • Logos and story images under public/images/customers/<slug>/.
  4. Users / adopters list

    • After the story exists, add or update the company in the adopters table with add-customer-to-user-list so the Reference cell is [User Story](/users/<slug>).

Checklist before finishing

  • All required fields collected from user (or documented as TBD)
  • authors keys exist in data/authors.json
  • meta.json includes slug in desired order
  • Image checklist given to user with folder path
  • Company website link in About section
  • Docs links only where agreed; no broken internal URLs
  • Replace all em dashes with regular hyphens (-) - the linter will do this anyway; better to do it upfront
  • Follow AGENTS.md / documentation-pages.mdc: one H1 via BlogHeader, American English, accessible alt text

Quick YAML skeleton (adapt fields)

yaml
---
title: "..."
date: ...
description: ...
ogImage:
tag: customer-story
author: ...
customerLogo: "/images/customers/<slug>/...-light.png"
customerLogoDark: "/images/customers/<slug>/...-dark.png"
customerQuote: "..."
quoteAuthor: "..."
quoteRole: "..."
quoteCompany: "..."
showInCustomerIndex: true
---

Frequently asked questions

What does the Customer Story Setup AI skill do?

Converts draft customer-story Markdown into Langfuse website MDX (Fumadocs), collects missing metadata and assets, wires meta.json and authors. Use when adding or converting a customer case study, user story, or /users page, or when the user mentions customer story setup, cresta/canva-style posts, or CustomerStoryCTA/BlogHeader for customers.

Why use Customer Story Setup on TypingMind?

Because you install it once and use it with any model. Customer Story Setup 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 Customer Story Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/langfuse/langfuse-docs/tree/main/.agents/skills/customer-story-setup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Customer Story Setup?

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 Customer Story Setup?

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

Is the Customer Story Setup AI skill free?

Yes. It is published on GitHub by langfuse 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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