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概要と使いどころ
Detects fail-open insecure defaults (hardcoded secrets, weak auth, permissive security) that allow apps to run insecurely in production. Use when auditing security, reviewing config management, or analyzing environment variable handling.
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。
Discover the active AWS profile, region, account, and caller identity before SageMaker or AWS work. Use when local AWS context is needed or unspecified; do not use for cloud-agnostic model planning.
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。
Build and publish a Gradio Hugging Face Space for a user-provided image or video LoRA, including pipeline selection and model-card settings. Use for LoRA demos; use huggingface-spaces for general Space work.
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。
Brand-consistent asset sets from DESIGN.md — hero, section illustrations, icon sets, OG image — generated through whichever channel the user actually has (grok build image_gen, Codex $imagegen, Gemini, xAI/Recraft/OpenAI keys) as recorded by omd:setup, with a provenance and cost ledger. No channel → prompt pack + manual queue, never stock. Trigger: '이미지 세트 만들어', '에셋 생성', 'generate assets', 'hero image', '아이콘 세트', 'OG 이미지'.
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。
Brand-consistent asset sets from DESIGN.md — hero, section illustrations, icon sets, OG image — generated through whichever channel the user actually has (grok build image_gen, Codex $imagegen, Gemini, xAI/Recraft/OpenAI keys) as recorded by omd:setup, with a provenance and cost ledger. No channel → prompt pack + manual queue, never stock. Trigger: '이미지 세트 만들어', '에셋 생성', 'generate assets', 'hero image', '아이콘 세트', 'OG 이미지'.
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。
Verify Open Claude Code package integrity, release tests, and automation evidence. Use when asked whether an OCC release is published, tested, or fully automated.
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。
Coroutine patterns, Flow operators, Jetpack Compose state management, Ktor routing, and Kotlin Multiplatform shared code.
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。
薪资谈判教练。模拟前 FAANG 招聘官 + 薪酬策略师，把「拿到 offer → 签字」这一步拆成 6 个动作：Offer 诊断（Base / RSU / Sign-on / Bonus 每项标 LOW/MED/HIGH leverage）→ 谈判杠杆图（我的力量 / 招聘官的力量 / 弱点）→ 策略排序（Base → RSU → Sign-on → Bonus，按 context 调整）→ 脚本生成（电话 / 邮件 / 招聘官回话模拟）→ Counter 模拟（"这是最好的了" / "预算固定" / "会考虑其他候选人" 三种硬回答）→ 最终建议（要什么 / 别推什么 / 何时停）。三步：贴 offer → 说 context（有没有竞争 offer / deadline / 级别 / 风险偏好 / 最看重什么）→ 自动生成并打开一份 HTML Negotiation Playbook。关键词：salary negotiation, offer negotiation, comp negotiation, RSU, sign-on, base salary, counter offer, competing offer, TC, total comp, 薪资谈判, offer 谈判, 谈薪, 反 offer, 加薪, 谈 package, levels.fyi, 招聘官话术, recruiter script。
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。
求职工具包。把「找岗位 → 签 offer」拆成六个独立子 skill：⓪ Job Hunt 批量发现岗位，① Job Description 解码具体 JD，② Resume 定向简历，③ BQ 准备行为面试，④ Offer Compare 对比多份 offer，⑤ Salary Negotiation 谈 package。任何求职相关请求（找工作、该不该投、改简历、准备面试、选 offer、谈薪）都从这里进，再路由到对应子 skill。关键词：求职, offer, career, job hunt, LinkedIn jobs, JD, resume, CV, behavioral interview, BQ, STAR, offer compare, salary negotiation, 薪资谈判, 选 offer。
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 Nano Banana Pro (Gemini 3 Pro Image) prompts for e-commerce product photography. Given a user-uploaded product photo, this skill identifies the main subject, asks the user to choose a scene type, then outputs a professional, ready-to-paste English prompt optimized for Nano Banana Pro's image-to-image capabilities. Use this skill whenever the user uploads a product image and wants to generate an e-commerce photo, product shot, commercial image, or marketing visual using Nano Banana Pro / Gemini. Trigger phrases include: "ecom shot", "电商图", "产品图", "商品图", "product photo", "e-commerce image", "make a product shot", "generate a Nano Banana prompt for this product", "帮我做一张电商主图", "白底图", "商拍", "产品摄影", "hero shot", "packshot", or any request involving turning a casual product photo into a professional commercial image. Also trigger when the user mentions Nano Banana / Gemini image generation with a product photo.
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 storyboard image boards and matching video-generation prompt scripts for specific scenes in a short video plan. Use this skill whenever the user asks to create a storyboard, storyboard image, video prompt script, scene prompt, image-to-video prompt, shot board, or per-scene video-generation package, especially when they specify a scene number, duration, or an existing video plan. This skill saves outputs as storyboard/scene-XX.png and storyboard/scene-XX.md and enforces grid sizing, timing labels, and strict character, wardrobe, prop, and location continuity.
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 approved tutorial context packs exist and the run needs the final article-first tutorial deliverable.
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。
Define evidence-first table schemas for a survey: what each table must answer, row unit, columns, and which evidence-pack fields are required to fill it.
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 `output/DRAFT.md` (or `output/SNAPSHOT.md`) from an approved outline and evidence packs, using only verified citation keys from `citations/ref.bib`.
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。
Fill `outline/tables_index.md` from `outline/table_schema.md` + evidence packs (NO PROSE in cells; citation-backed rows).
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。
Extract per-subsection “anchor facts” (NO PROSE) from evidence packs so the writer is forced to include concrete numbers/benchmarks/limitations instead of generic summaries.
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。
Create per-subsection evidence packs (NO PROSE): claim candidates, concrete comparisons, evaluation protocol, limitations, plus citation-backed evidence snippets with provenance.
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。
Evidence self-loop for surveys: read evidence bindings + evidence packs, then write an actionable upstream TODO plan (which stage/skill to fix) before writing more prose.
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 one survey-quality paragraph from evidence packs (tension → contrast → evaluation anchor → limitation).
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。
Seed `outline/claim_evidence_matrix.md` from outline+notes; claim-matrix-rewriter rewrites it later from evidence packs.
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。
Rewrite `outline/claim_evidence_matrix.md` as a projection/index of evidence packs (NO PROSE), so claims/axes are driven by `outline/evidence_drafts.jsonl` rather than outline placeholders.
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。
Train strict project ownership from repo-local docs/ai memory and central LLM Wiki project entities. Use when Codex or Claude Code should initialize a learning question bank, quiz or grade the user, run code tracing or failure drills, record misconceptions, schedule spaced repetition, or generate Markdown/JSON mastery dashboards without replacing llm-wiki or ai-project-memory.
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。
Query and maintain the user's local LLM Wiki from any Codex or Claude Code conversation or project. Use when the user asks to search personal knowledge, recall prior research or decisions, answer from the wiki, create durable notes, ingest a source into the wiki, update topic/concept/entity/question pages, write back useful answers, or run wiki lint/reindex 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。
Jetpack Compose animation foundations - animate*AsState, AnimatedVisibility, Crossfade, updateTransition, SharedTransitionLayout, gestures.
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。