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Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill qe-agentic-jujutsuコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Ruflo is a multi-agent orchestration platform for AI coding agents (Claude Code, Cursor, Codex, Copilot, Gemini, Amp, +12 more). Use this skill when the user wants to (1) install/init ruflo in a project, (2) run multi-agent swarms with hierarchical coordination, (3) use ruflo's 314+ MCP tools for memory, routing, hooks, sub-agents, or workflows, (4) check ruflo status/version/doctor health, or (5) discover which of ruflo's 30+ plugins fits their task.
Build dependency-aware execution plans for complex Agentic QE, Ruflo, integration, migration, or multi-stream engineering programs. Use when Codex must turn research or requirements into phased work, select a small AQE fleet, map critical paths and parallel streams, define acceptance gates, or sequence risky changes. Use aqe-plan-quality instead when the primary output is only a test or quality plan.
Conduct evidence-first technical research for Agentic QE, Ruflo, related ruvnet projects, or external tools. Use when Codex must investigate a repository, compare current upstream changes, trace dependencies and history, distinguish verified facts from inference, or synthesize findings into actionable engineering recommendations. Do not use for a simple known-answer lookup or an implementation-only task.
SOC 職業分類に基づく
SKILL.md を表示中
| inclusion | auto |
| name | qe-agentic-jujutsu |
| description | Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination |
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Tags: qe, quality-engineering
This skill requires the AQE MCP server. Ensure it is configured in .kiro/settings/mcp.json.
Installation
Basic Usage
Core Capabilities
Track operations, learn patterns, and get intelligent suggestions:
Automatically identify successful operation sequences:
Track improvement over time:
Fast integrity verification with quantum-resistant cryptography:
Automatic tracking of all operations:
Use AQE tools via the @agentic-qe MCP server:
@agentic-qe/fleet_init — Initialize the QE fleet@agentic-qe/test_generate_enhanced — Generate tests@agentic-qe/coverage_analyze_sublinear — Analyze coverage@agentic-qe/quality_assess — Assess quality gates@agentic-qe/memory_store — Store learned patterns@agentic-qe/memory_query — Query past patterns