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概要と使いどころ
Use this repo skill for Agent Lightning package tasks: authoring trainable agents, tracing rewards and spans, running LightningStore/Trainer loops, using agl CLI services, choosing examples, and troubleshooting optional backends.
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。
Autonomous pentest campaign driver. Runs a scoped engagement end to end with no operator approvals - the deterministic driver (scripts/campaign.py) owns pass state, generates the killchain board from recon, and prints the exact next action (Skill + tool) every turn. Use when starting or resuming a pentest, "run the pt workflow", "work this CIDR/domain", or when handed a client SoW/scope to reach a stated objective or domain admin. Single agent, refuter-verified, wiki-first, tool-first. Deliverable is a client report.
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。
Autonomous bug-bounty campaign driver. Runs a full programme end to end with no operator approvals - the deterministic driver (scripts/campaign.py) owns pass state, generates the killchain board from recon, and prints the exact next action (including which Skill and tool to run) every turn. Use when starting or resuming a bug-bounty engagement, "run the bb workflow", "hunt this program", "9-pass campaign", or when handed a *.scope wildcard to test for TIER1 findings. Single agent, refuter-verified, wiki-first, tool-first.
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。
Autonomous sub-agent hand-off for a fiddly, fully-specified exploit-compile / escalation RUN - the main agent stays on strategy and the board while a cheap sub-agent runs an exact copy-paste checklist behind a false-root/hostname guardrail. Use for "delegate", "offload", "hand this to a sub-agent", "spin a haiku", or the moment a foothold plus a working escalation vector is identified. Main agent dispatches, waits (no parallel duplicate), integrates the result.
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。
Autonomous CTF / boot-to-root campaign driver. Runs a box end to end with no operator approvals - the deterministic driver (scripts/campaign.py) owns pass state, generates the killchain board from recon, and prints the exact next action (Skill + tool) every turn. Use when handed a box/IP to own end to end, "run the ctf workflow", "root this box", "foothold to root". Single agent, wiki-first, tool-first. OSINT is OFF unless you invoke with an osint argument. Delegates box recipes to ctf-box.
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。
Write less code and say less about it. Applies YAGNI and stdlib/native-first so the agent writes the minimum code that needs to exist, and responds tersely — stripping filler, hedging, and pleasantries while keeping code, identifiers, and technical terms exact. Use whenever writing, modifying, refactoring, reviewing, or explaining code, or any response where output volume drives token cost — even if the user never says "minimal" or "concise". Especially in agentic coding, where the volume of generated code and prose runs up the bill.
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。
Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools required.
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。
Stack Honey onto Superpowers-style workflows (subagent-driven-development, dispatching-parallel-agents, executing-plans) and any orchestration that dispatches fresh subagents. Dispatched subagents run in isolated context and do NOT inherit the session's Honey hook, so they emit full-fat code and verbose reports. Use when you are about to dispatch implementer/reviewer/fixer/parallel subagents: it gives the exact Honey directive to paste into each dispatch prompt, with a worker variant and a reviewer variant, so the levers apply inside the subagents too — where the multiplied cost actually is.
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。
Read huge dense read-only text as PNG pages via pxpipe export: ~60-75% fewer input tokens. Lossy on exact strings; never for files you will edit.
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。
Generate or update an Agent Skill that teaches consumers one npm or local package the user maintains, including framework modules and wrappers. Tests each example against the installed version. Use when a maintainer asks for a package Skill, a SKILL.md for their library, or a Skill update after a release.
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。
Prepare the local environment for the Maestro smoke-test suite — verify tooling, select a device, collect the APK if needed, validate the .env file by variable name only, then hand the user the exact lab-store CLI command to run or run it on request.
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。
Evaluate Agent Skill design quality with an opinionated, practice-derived rubric informed by public specifications and examples. Use when reviewing, auditing, comparing, or improving SKILL.md files and skill packages. Produces evidence-backed findings, optional multi-dimensional scoring, and prioritized changes; treat the result as diagnostic guidance, not official certification or a universal standard.
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。
Stylized art direction for Blender with shape language, exaggeration, color harmony, NPR rendering, and hand-painted asset workflows. Use for non-photorealistic game and animation projects.
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。
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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。
Generate comprehensive, developer-friendly API documentation from code, including endpoints, parameters, examples, and best practices
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。
After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.
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。
Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.
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。
把已验证的传播机制转成适合目标账号的内容选题，并完成生成、迁移、评分和筛选，让选题自然连接人设、产品或门店。用户要从低粉爆款、垂直样本、邻近受众或跨赛道内容中寻找新选题时使用。 English: Turn validated content mechanisms into topics that fit the target account, then generate, adapt, score, and filter them while connecting naturally to the persona, product, or store. Use to find ideas from low-follower breakouts, niche examples, adjacent audiences, or other categories.
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。
只读检索小红书公开内容，并把账号数据、标题、封面、互动量、作者近期内容和低粉爆款整理成可追溯证据。用户要求查公开账号或笔记数据时使用；不得点赞、收藏、评论、发布、删除或导出登录凭证。 English: Read-only research for public Xiaohongshu content, collecting traceable evidence such as account data, titles, covers, engagement, recent posts, and low-follower breakout examples. Use for public account or post research; never like, save, comment, publish, delete, or export credentials.
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。
为已经确定的小红书内容设计封面文字和画面布局，包括关键词、人物与场景位置以及 A/B 方案。用户要做小红书封面、参考爆款封面，或检查封面是否符合账号视觉调性时使用。 English: Design cover copy and visual composition for an approved Xiaohongshu post, including keywords, subject placement, scenes, and A/B options. Use to create or review a cover against successful examples and the account's visual style.
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。
教学过程中自动捕获和记录学习者的概念疑难点（"为什么/是什么/怎么推/什么意思"类型的问题），保存到进度文件的"概念疑难点记录"区，形成考前回顾清单。
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。
Use when the user needs engineering or research-paper figures: system architecture diagrams, algorithm workflows, hardware schematics, benchmark charts, ablation plots, figure briefs, redraws, image edits, or exact publication-style plots from numeric data. Covers Gemini, Nano Banana, OpenAI image models, and local plotting workflows.
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。
Multi-state harmonized privacy compliance program. Common requirements matrix across all US state privacy laws, state-specific deltas, unified privacy program architecture, and implementation strategy for operating across California, Virginia, Colorado, Connecticut, Texas, Oregon, Montana, and Kentucky.
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。
Guide to implementing homomorphic encryption for privacy-preserving computation under GDPR. Covers scheme selection (BFV, BGV, CKKS, TFHE), Microsoft SEAL, IBM HELib, and Google FHE transpiler. Includes performance benchmarks, parameter tuning, and basic HE example code for encrypted arithmetic operations.
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。