channel-io

This sop executes automated clustering and tagging of customer support chat data through a Python pipeline, producing clustered data, cluster tags, and a comprehensive analysis report for Stage 2 (Pattern Extraction). The agent orchestrates the Python clustering script, monitors execution, validates outputs, and generates an analysis report to guide subsequent extraction work. **Language:** Auto-detects Korean (한국어) or Japanese (日本語) from user input.

Generate an ALF implementation package from all pipeline outputs. Produces rules draft, RAG knowledge items, dialog type cross-analysis heatmap, automation feasibility analysis, ROI calculation, task flowcharts (05_sales_report/tasks/), API requirements doc, and final ALF implementation guide. **Language:** Auto-detects Korean (한국어) or Japanese (日本語) from user input.

Split rules_draft.md into individual rule files and expand rag_items.md into standalone RAG knowledge documents for direct ALF registration.

Generate a client-facing deployment scenario and QA set from pipeline outputs (Stages 1-6). Maps consultation categories to resolution methods (RAG/Task) and deployment steps, with test queries per category. Outputs HTML + Markdown, optionally publishes to Notion.

Complete end-to-end pipeline for transforming Excel customer support data into production-ready Agent SOP documents, flowcharts, ALF implementation package, individual ALF registration files, and client-facing deployment scenario through 7 stages.

Channel.io 봇의 RAG 응답 품질을 Playwright로 자동 테스트합니다.

Task JSON 품질 평가. 검증 및 품질 점수를 제공합니다.

Generate production-ready SOP documents from Stage 2 extraction results, with a verification loop that tests each SOP against real conversations. **Language:** Auto-detects Korean (한국어) or Japanese (日本語) from user input.

Use when creating or modifying Core API proto contracts in ch-proto-public, including service request/result messages, model/common public schemas, validation, comments, generated output expectations, and proto pattern discovery.

Creates an n8n node from a Linear issue link by extracting the issue key and the final URL path segment as the API title, then building the node from the ChannelTalk swagger spec. Use when the user provides a Linear issue URL for creating a new n8n node.