本文へ移動
cccskills
無料GitHub で公開

churn-autopsy

Post-mortem analysis when a client churns. Takes client history, engagement data, support tickets, usage logs, and exit feedback to produce a comprehensive churn autopsy with root cause classification, timeline of decline, and preventive measures.

OneWave-AI/claude-skills
インストール方法を見る

含まれるファイル（6）

  • SKILL.md2.0 KB
  • references/analysis-framework.md7.8 KB
  • references/inputs.md1.8 KB
  • references/output-template.md3.7 KB
  • references/root-cause-taxonomy.md3.4 KB
  • references/standards.md3.3 KB

SKILL.md（原文）

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Churn Autopsy

Dissect a client departure with forensic rigor and produce churn-autopsy.md: a historical record and retention playbook that turns a loss into organizational learning.

Contents

  • references/inputs.md -- required and optional data to gather before analysis
  • references/analysis-framework.md -- the six-phase forensic method
  • references/root-cause-taxonomy.md -- root cause categories and subcategories
  • references/output-template.md -- full churn-autopsy.md report structure
  • references/standards.md -- objectivity, rigor, sensitivity, incomplete-data, and operating rules

Workflow

  1. Collect. Gather all available inputs per references/inputs.md. Read provided files directly; query connected CRM and analytics MCP tools for account, usage, and support data. Note any gaps.
  2. Organize. Build the full chronological timeline from first touch to cancellation before attempting analysis.
  3. Analyze. Apply the six phases in references/analysis-framework.md systematically, without skipping: baseline, timeline of decline, root cause classification, missed warning signs, counterfactual analysis, lessons learned.
  4. Classify. Assign one primary root cause and any contributing causes using references/root-cause-taxonomy.md.
  5. Draft. Write the report in the structure defined in references/output-template.md.
  6. Challenge. Review every conclusion against references/standards.md; attempt to disprove each finding before keeping it.
  7. Finalize. Produce churn-autopsy.md with all sections complete in the current working directory or a user-specified location.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

ログインしてレビューを書く

同じリポジトリのスキル

概要と使いどころ

accessibility-auditor

無料

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3402026年10月2日 更新

agent-army

無料

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.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3402026年10月2日 更新

agent-eval-harness

無料

Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3402026年10月2日 更新

agent-swarm-deployer

無料

Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3402026年10月2日 更新

agent-team-builder

無料

Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3402026年10月2日 更新

agent-to-agent

無料

Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3402026年10月2日 更新

OneWave-AI のスキルをすべて見る

このスキルの問題を報告する