Batch dispatch — read queued tasks from ~/.claude/batch/inbox.md, fix each task's spec contract, fan them out to background subagents per case, and leave the user free until review time. Also surfaces unreported client sessions (~/.claude/batch/unreported.md). Use when the user says "batch", "morning batch", "朝バッチ", "タスク投入", "/batch", "/morning-batch", or at the start of a work day with queued tasks.
Standardized "investigate → written report" pipeline for SRE client work. Fixes the deliverable contract up front (format + done-criteria), delegates repo/infra scanning to subagents, verifies every claim, and outputs an issue-ready Markdown report. Use when the user says "調査して", "調べてレポート", "investigation report", "報告書にまとめて", or hands over an investigation-shaped task.
Turn a finished case (case-reflect / sreaas report output) into a generalized, confidentiality-scrubbed company tech-blog draft. Use when the user says "会社ブログ", "テックブログ", "案件を記事化", "company blog", or wants to asset-ify case outcomes for public publishing. Realizes the company-blog stage of learn_cycle.md.
Generate a personalized learning guide (text + hands-on script) for a technology/topic, tuned to the user's level and case context — like an AI-personalized intro book. Use when the user says "学習ガイド", "入門ガイド", "ハンズオンを作って", "learn guide", "この技術を学びたい", or wants a guided, output-oriented way to learn something. Powers the learning half of learn_cycle.md.
From a Claude Code /insights report, generate a Japanese-translated HTML report AND reflect its actionable recommendations into the config (~/.claude/), confirming EACH item one-by-one (apply or skip). Skipped items are left untouched. Use when the user says "insights apply", "insightを設定に反映", "insightを日本語HTML", "apply insights to config".
Systematically investigate and fix a GitHub Issue with root cause analysis. Use when user says "fix issue", "fix
Comprehensive security audit based on OWASP 2025 Top 10 with automated checks. Scans for vulnerabilities, insecure patterns, hardcoded secrets, and dependency risks.
Cross-cutting incident investigation using AWS CLI, Datadog (pup), and local repository analysis. Use when user says "incident analysis", "investigate outage", "root cause analysis", "postmortem", or "analyze incident". Systematically collects infrastructure metrics, application logs, and codebase evidence to produce a comprehensive incident report with timeline, root cause, and remediation recommendations.