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概要と使いどころ
End-to-end R data analysis pipeline — exploration → cleaning → regression → publication-ready tables and figures. Use when user says "analyze this dataset", "run a regression on X", "explore this CSV", "full analysis workflow", "get me summary stats and a regression", or points at a `.csv`/`.rds`/`.dta` and asks for empirical results. Produces numbered R scripts in `scripts/R/` and outputs to `output/`.
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 or revise Chinese social-media covers through the registered Skill-封面 asset system, reusable styles, presenter identities, ratio-specific layouts, and exact replacement prompts. Use only when the user explicitly says“skill-cover”“Skill-封面”“实战风格”, requests the registered style/gesture assets, asks for simultaneous 3:4 and 4:3 registered-layout output, replaces a reference cover's person with the current digital-human frame, or extends this registered cover system. Do not use for a generic“制作封面/生成封面”request; generic cover requests belong to dog-skill.
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。
实操长片策划工作流（B站/YouTube 新赛道，实操+真人出镜）。产出可直接照着录的策划稿：测试题组（含可粘贴 prompt）、 结构时间轴（全身出镜段 vs PiP 段）、出镜口播稿、录屏操作清单、悬念与彩蛋设计。 Use when the user says 做实操长片, 实操视频, 实测视频, 对比实测, xx做成实操, 出个实测策划, 这个选题拍实操, or ra-选题 routes a 实操长片 立项 here. 策划稿落 `01-内容生产/视频工作台/制作中/<日期-主题>/策划稿.md`，frontmatter status 是与制作端交接的唯一状态机。
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 and composite HeyGen digital-human videos in the content workspace. Use whenever the user asks for a 数字人, 数字人5, HeyGen, AI 口播人物, 数字人小窗, 圆形头像口播, full-screen digital human, or asks to make a video that uses the existing avatar. Enforce Creator-plan CLI OAuth, the configured Digital Twin, local IndexTTS2 narration, Avatar III for an unspecified digital human but Avatar V whenever the named preset 数字人5 is requested, adaptive face measurement plus the approved human-reviewed visual-centering offset in the headroom_08 circular bottom-left layout unless full-screen is explicitly requested, subtitle-safe placement, credit-aware master reuse, final QC/archive routing, and mandatory pairing with `heygen-avatar-motion` before any motion prompt or paid generation.
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 anonymized frame-by-frame body and hand trajectories from an authorized reference video, with skeleton previews, confidence evidence, and machine-readable keypoints. Use when the user asks to 提取博主动作, 提取人体动作轨迹, 做姿态参考, 生成骨架视频, or prepare motion control data for an avatar; do not route graphic-animation replication here.
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 answering a question that needs data from a ktx-connected database - investigating, analyzing, "how many", "show me", "what's the breakdown of", finding records by value, exploring tables, comparing periods, explaining metrics, or any data-analysis request. Triggers even when the user does not say "analytics"; if the answer requires querying a configured ktx connection, this skill applies.
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。
Convert one changed historic-SQL table usage bucket into typed table usage evidence for deterministic _schema projection.
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 durable ktx wiki knowledge from staged Sigma data model specs and workbook summaries. Load for WorkUnits with unitKey sigma-data-models or sigma-workbooks.
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。
Identify recurring cross-table historic-SQL analytical intents from a bounded pattern shard and emit typed pattern evidence for deterministic wiki projection.
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。
Installs and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent integration, and verifies readiness. Use when the user asks an agent to add ktx to a project, connect data sources, install agent rules, ingest schema, or troubleshoot a local ktx install.
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。
Clone an existing video ad for a different product or offer. Analyzes the source video's style, pacing, camera work, dialogue, and tone, then adapts and generates a new Seedance 2.0 video customized for the user's product. End-to-end workflow: input video → analysis → adapted prompt → generation → delivery. Use when someone says "clone this ad", "make this ad but for my product", "recreate this video for my brand", or provides a video ad and a product image asking for a similar video.
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。
Analyze a reference video and reverse-engineer its style into a reusable Seedance 2.0 prompting template. The output is a new skill/formula (like seedance-2-ugc.md) that captures the video's structure, pacing, camera work, edit style, and tone so it can be recreated with any product, any person, in any setting. Use this whenever someone provides a video they want to use as a style reference, says "I want to make videos like this", "deconstruct this video", "turn this into a template", "analyze this style", or drops a video file and wants to recreate that format repeatedly.
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 designing how one canonical agent core runs across Codex, Claude Code, Gemini CLI, Cursor, and AGENTS.md-compatible tools.
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 types /prompts:hep-build or /agentlas-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package an existing local/external agent into Agentlas architecture.
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 types /hep-storm, mentions @Hephaestus storm, or asks to force-robustly drive a loop-worthy goal (apps, sites, agents, automations, debugging, multi-step research, data/report generation) to a verified finish. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs a verifier-first loop that does not stall, run away, or claim false success. Trivial questions are answered directly, not stormed.
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 types /hep-storm or /agentlas-storm, says @Hephaestus storm <goal>, or asks to drive a goal to verified completion through a force-robust Stormbreaker loop. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs each work packet as a verifier-first hardened loop that does not stall, run away, or claim false success. Use it for loop-worthy work — apps, sites, agents, automations, debugging, multi-step research, data/report generation. Trivial questions are answered directly, not stormed.
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 designing how one canonical agent core runs across Codex, Claude Code, Antigravity, Cursor, and AGENTS.md-compatible tools.
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。
Convert Next.js bundle analyzer data to NDJSON and explore 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。
Scrape BOSS直聘 (job listing site) via Chrome CDP. Searches jobs by keyword/city/filters, fetches JD details, outputs structured JSON/CSV with plaintext salary, and can summarize scraped results into a job-market prompt. Use when user wants to search/analyze jobs on BOSS直聘 or zhipin.com.
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。
Architect Unity 6.3 LTS data and decoupling with ScriptableObjects: config/data assets, shared runtime variables, event channels, and runtime sets/registries. Use when designing data-driven systems, replacing singletons/managers, creating .asset data with CreateAssetMenu, or when the user mentions ScriptableObject, SO architecture, or data assets.
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 branching dialogue and narrative — a node/choice graph with conditions, variables, and localization hooks — and choose between authoring tools Ink and Yarn Spinner or a custom data-driven runner. Engine-neutral. Use when the user mentions dialogue system, branching dialogue, conversation tree, choices, Ink (.ink), Yarn Spinner (.yarn), or NPC dialogue.
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。
Persist player data in Roblox with DataStoreService: GetDataStore, GetAsync/ SetAsync/UpdateAsync/IncrementAsync wrapped in pcall, load-on-join and save-on-leave plus BindToClose, retries, and OrderedDataStore leaderboards. Use when saving or loading persistent data in a Roblox experience — when the user mentions DataStore, DataStoreService, GetAsync, SetAsync, UpdateAsync, save player data, or leaderboards. For general Luau scripting use roblox-luau.
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 edit tile-based 2D levels in Godot 4.7 with TileMapLayer and TileSet: paint layers, set up collision/navigation/custom-data on tiles, autotile with terrain sets, and read/write cells from code (set_cell, get_cell_tile_data, local_to_map). Use when working with TileMapLayer nodes, .tres TileSets, autotiling, or migrating a deprecated TileMap node to TileMapLayer.
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。
Design data-driven Godot 4.7 games with custom Resource classes: define typed data with class_name + @export, save/load .tres/.res files, instance and duplicate resources, and load on demand with ResourceLoader (incl. threaded loading). Use when modeling items/stats/configs as data in a Godot project, creating .tres resources, or working with custom Resource subclasses and ResourceLoader/ResourceSaver.
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。