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Churn Autopsy - Abwanderungsanalyse

Erstellt eine forensische Analyse nach Kundenabwanderung: basierend auf Kundenhistorie, Engagement-Daten, Support-Tickets, Nutzungsprotokollen und Exit-Feedback wird ein umfassender ‚Churn-Autopsiebericht‘ mit Ursachenklassifikation, Zeitstrahl des Niedergangs und Präventionsmaßnahmen erzeugt.

Was ist Churn Autopsy - Abwanderungsanalyse?

Diese Fähigkeit verwandelt einen verlorenen Kunden in eine organisatorische Lernchance. Sie führt einen sechsphasigen forensischen Prozess durch: Datenerhebung (z. B. CRM, Analytics MCP-Tools), Timeline-Erstellung, Ursachenanalyse, Klassifikation, Berichterstellung und kritische Überprüfung. Das Ergebnis ist eine Markdown-Datei (`churn-autopsy.md`), die eine historische Aufzeichnung sowie einen präventiven Playbook-Charakter hat. Unterstützt werden gängige Entwicklerplattformen wie Claude Code, Cursor und Codex. Die Analyse folgt einem strengen Standard – inklusive Objektivität, Sensitivität bei unvollständigen Daten und dem Versuch, jede Schlussfolgerung zu widerlegen. So wird sichergestellt, dass das Team nicht nur die Symptome, sondern die tatsächlichen Ursachen der Abwanderung versteht und konkrete Maßnahmen ableiten kann.

Funktioniert mit✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/OneWave-AI/claude-skills/tree/HEAD/churn-autopsy

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Dokumentation

Churn Autopsy (Abwanderungsanalyse)

Zerlegen Sie eine Kundenabwanderung mit forensischer Präzision und erstellen Sie churn-autopsy.md: eine historische Aufzeichnung und ein Retentions-Playbook, das einen Verlust in organisatorisches Lernen verwandelt.

Inhalt

  • references/inputs.md – erforderliche und optionale Daten, die vor der Analyse gesammelt werden müssen
  • references/analysis-framework.md – die sechsphasige forensische Methode
  • references/root-cause-taxonomy.md – Kategorien und Unterkategorien von Ursachen
  • references/output-template.md – vollständige Struktur des churn-autopsy.md-Berichts
  • references/standards.md – Objektivität, Genauigkeit, Sensitivität, Umgang mit unvollständigen Daten und Betriebsregeln

Arbeitsablauf

  1. Sammeln. Sammeln Sie alle verfügbaren Eingabedaten gemäß references/inputs.md. Lesen Sie bereitgestellte Dateien direkt ein; fragen Sie angeschlossene CRM- und Analytics-MCP-Tools nach Konto-, Nutzungs- und Supportdaten ab. Notieren Sie etwaige Lücken.
  2. Organisieren. Erstellen Sie die vollständige chronologische Zeitleiste vom ersten Kontakt bis zur Kündigung, bevor Sie mit der Analyse beginnen.
  3. Analysieren. Wenden Sie die sechs Phasen in references/analysis-framework.md systematisch an, ohne eine auszulassen: Ausgangslage, Zeitleiste des Niedergangs, Ursachenklassifikation, übersehene Warnsignale, kontrafaktische Analyse, gewonnene Erkenntnisse.
  4. Klassifizieren. Weisen Sie eine primäre Ursache und ggf. beitragende Ursachen mithilfe von references/root-cause-taxonomy.md zu.
  5. Entwerfen. Schreiben Sie den Bericht in der in references/output-template.md definierten Struktur.
  6. Hinterfragen. Überprüfen Sie jede Schlussfolgerung anhand von references/standards.md; versuchen Sie, jede Feststellung zu widerlegen, bevor Sie sie beibehalten.
  7. Abschließen. Erstellen Sie churn-autopsy.md mit allen vollständigen Abschnitten im aktuellen Arbeitsverzeichnis oder an einem benutzerdefinierten Speicherort.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

OneWave-AI/claude-skills

Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.

OneWave-AI/claude-skills

Generate animated videos and motion graphics from natural language descriptions. Creates a standalone Vite + React project with Framer Motion scenes that auto-play in the browser. Use when the user wants to create animations, motion graphics, video intros, animated presentations, or product demos.

OneWave-AI/claude-skills

Use before starting a product, feature, MVP, agent, automation, or integration build to identify the main pre-build risk and choose the smallest validation step. Trigger when the user asks whether to build, scope, validate, prioritize, or sanity-check an idea before implementation.

OneWave-AI/claude-skills

Compose a premium, animated landing page section by section in Next.js + Tailwind + Motion (Framer Motion) — built on a real design system, with editorial copy and motion that feels human-crafted, not template-generated. Use when building or rebuilding a landing page, marketing site, or hero/feature/pricing/CTA sections that need to look production-ready and bespoke from day one.

OneWave-AI/claude-skills

Assemble 2-3 complementary experts to collaboratively analyze anything. Experts work together to explore topics from multiple expert angles.

OneWave-AI/claude-skills

Convert any topic into playable browser games. Types: trivia, matching, word puzzles, adventure games. Uses Phaser.js or Kaboom.js.

OneWave-AI/claude-skills

Turn a marketing brief or product offer into a finished short-form video ad built in HyperFrames — hook, script, shot-by-shot storyboard, scene-by-scene HTML composition, captions, and voiceover. Outputs platform cuts (vertical 9:16, square, 16:9). Use when you need a launch ad, product promo, social video, or paid-creative concept ready to render.

OneWave-AI/claude-skills

Turn a website URL, product docs, or a founder's rambling description into a tight 60-90 second explainer video built in HyperFrames -- problem/solution narrative, animated product walkthrough scenes, captions, and voiceover, ready for the homepage hero, sales emails, and onboarding.

OneWave-AI/claude-skills

Build promo videos for local businesses in HyperFrames -- the new-menu drop, the seasonal offer, the event announcement, the "we're hiring" post, the Google Business Profile clip. Restaurant, salon, gym, trades: 15-30 seconds, brand-clean, captioned, sized for Instagram, Facebook, and the profile.

OneWave-AI/claude-skills

Build a personalized product-demo or sales-walkthrough video in HyperFrames for a specific prospect or account — narrated screen-by-screen, branded to them, ending in a clear next step. Turns a generic demo into a "this was made for me" asset for outbound, follow-up, or deal acceleration. Use when you want to send a tailored video instead of booking another live call.

OneWave-AI/claude-skills

Turn real customer reviews, quotes, and case-study results into polished social-proof videos built in HyperFrames -- single-testimonial spotlights, review-wall montages, and stat-driven proof reels with captions and voiceover, cut for vertical, square, and wide. The highest-converting content most businesses never make.

OneWave-AI/claude-skills

Audit a codebase for LLM calls that are really classifications in disguise, then produce a costed swap plan for a System One model. Use when asked to cut AI inference cost or latency, when scoping a performance engagement for a client, when reviewing an agent loop that feels slow, or when asked "where could we use Jev here". Produces a ranked table of candidates with measured latency and dollar deltas.

OneWave-AI/claude-skills

Build and run a labelled eval set for a System One model (Jev, Von, or any typed-decision config), then sweep criteria wordings and thresholds against it. Use when a Jev/Von classification is wrong or unreliable, when choosing between the hosted API and a local open model, when tuning noul thresholds, or before shipping any typed-decision feature. Produces an accuracy-by-wording matrix and a calibrated threshold.

OneWave-AI/claude-skills

Wire a System One model (Jev, or an open reproduction like Von) into a product feature — routing, guardrails, scoring, classification. Use when replacing an LLM call that returns a label rather than prose, when adding a typed decision to an agent loop, or when deciding between the hosted Jev API and a local open model. Covers question design, the eval-set-first workflow, threshold calibration, confidence gates, and the traps measured on real data.

OneWave-AI/claude-skills

Optimize landing pages for conversions, performance, and SEO. Use when improving landing pages, increasing conversions, or optimizing page performance.

OneWave-AI/claude-skills

TAM/SAM/SOM calculator with deep market research. Produces comprehensive market-sizing.md with top-down and bottom-up estimates, methodology, data sources, assumptions, sensitivity ranges, growth projections, competitive landscape, and Mermaid visualizations. Use when user needs market size estimates, addressable market analysis, go-to-market sizing, investor-ready market analysis, or business plan market validation.

OneWave-AI/claude-skills

Generate unique personalized first lines for hundreds of prospects using company news, LinkedIn activity, and mutual connections. Saves 10+ hours of manual research per campaign. Use when you need personalized outreach at volume.

OneWave-AI/claude-skills

Review investment portfolios for risk, diversification, fees. Asset allocation recommendations, tax-loss harvesting, rebalancing.

OneWave-AI/claude-skills

Create multiple choice, true/false, fill-in-blank, matching quizzes. Auto-generate plausible distractors. Instant grading with explanations.

OneWave-AI/claude-skills

Enhanced skill navigator that maps conversation history, recommends multi-skill chains, identifies patterns from past usage, and learns from session outcomes. Goes beyond basic scout with deep context analysis and workflow orchestration.

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