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概要と使いどころ
Multi-agent research orchestration: split a research goal into parallel sub-goals, run each via headless `claude -p` subprocesses, aggregate results into a polished report file. Use for systematic web/document research, competitive or industry analysis, batch link/dataset processing, and long-form evidence synthesis. Triggers: "深度调研", "deep research", "wide research", "多 Agent 调研", "系统调研".
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 cloned narration for the content workspace. Use local IndexTTS2 with the canonical lossless Pluviobyte reference for every local video, voice audition, digital-human narration, and subtitle-ready audio render. Preserve MiniMax only for public-facing articles or tutorials that teach users to connect through the relay service; never use MiniMax for local video production.
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。
dontbesilent 交互式学习。把一个课题拆成连续学习文章，根据用户在上一篇中的反馈调整下一篇的深度、角度和节奏。 触发方式：/dbs-learning、/dbs-learn、/交互式学习、「带我学一个课题」「继续下一篇」「根据我的反馈写下一篇」 Interactive learning workflow. Builds an adaptive sequence of learning articles based on user feedback. Trigger: /dbs-learning, /dbs-learn, "teach me a topic", "continue the next lesson"
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。
When provisioning, setting a limit, or committing an estimate under uncertainty, size a buffer to residual error and the cost of breach—not to the optimistic edge.
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 the local AST-derived code graph (functions, classes, calls, imports) for structural codebase questions — what calls X, what does Y import, where is Z defined, blast radius of a change. The graph rebuilds automatically after each agent turn; use hivemind_graph_search and hivemind_graph_neighborhood tools (no manual build step).
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 $hephaestus-network, /hep-network, or /agentlas-network, mentions @Hephaestus, or asks Agentlas to staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams. The active host LLM staffs each turn; the exact roster remains goal-bound until explicit completion.
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。
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Answers questions about storage access tiers (hot, cool, cold, archive), when to use each tier, and tier comparison. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics. Includes lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, storage tiers, hot cool cold archive, storage tier comparison, when to use storage tiers, lifecycle management, Azure Storage concepts. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).
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 Unreal Engine 5 gameplay with Blueprint visual scripting: Blueprint Classes, the Event Graph and Construction Script, variables/functions/macros, and Blueprint communication (Cast, Interfaces, Event Dispatchers). Use when working in Blueprints, wiring an event graph, deciding how Blueprints talk to each other, or when the user mentions Blueprint, BP, event graph, construction script, or a Blueprint .uasset.
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。
Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets. Engine- neutral method that pairs with each engine's profiler. Use when the user mentions performance, optimize, low/dropping FPS, frame drops, stutter, lag, profiler, frame budget, draw calls, batching, garbage collection/GC spikes, object pooling, or "the game runs slow".
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。
Find what is actually working in the user's niche on YouTube and rank it by how far each video beat its own channel, then name the formula. Use for "what's working right now", "find viral videos in my niche", "why did this blow up", competitor research, or a swipe file.
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。
Turn a user-owned coverage CSV and reviewed press-clip captures into an honest, source-linked earned-media dashboard and a motion-designed highlight reel (MP4) that scrolls each real article to the client's sentence and highlights it. Use for coverage reports, earned-media dashboards, campaign recaps, or coverage videos; requires local files and composes press-clip instead of scraping articles itself.
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。
Decide which single journalist at one publication to approach first with a pitch. Fit-checks each candidate through journalist-fit-check, then ranks the survivors on the comparative signals that separate colleagues at the same masthead (topic ownership, format match, staff vs. contributor, publishing cadence, recent story types, source-type match), and returns one first pick with tailoring notes plus a held fallback order.
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。
Draft crisis holding statements, journalist Q&A posture, and what-not-to-say guidance from confirmed incident facts, with a hard legal-counsel gate. Builds each statement through proven crisis-comms frameworks (holding-statement anatomy, SCCT, CAP order, the legitimate non-answer, bridge/flag/block).
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。
Triage inbound journalist source queries and draft a response only when the user's expertise is a real fit. Runs each query through proven source-request lenses (4-gate fit triage, credential-standing test, deadline read, BLUF/inverted-pyramid drafting), kills weak fits, asks for missing proof, and never auto-sends.
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。
Consolidate freshness-gated newsjack signals and route them by client standing before angle generation. Collapses any remaining same-story duplicates, decides strong/partial/none standing with a journalist-shape sanity check, and sorts each story into pitch_ready, big_story (always-surfaced suggestion), or watch. Never writes angles or pitches, and never drops a fresh big story.
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 headline candidates from a story's raw facts: news-style headlines, press-release headlines, and pitch subject lines. A pure generation skill — it finds the charge in the facts, then runs ten proven moves (consequence, picture, number-as-hero, two-beat turn, naming, reader's-own-story, open question, voice, sound, sized claim), each calibrated by real, verified headlines that made history.
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。
Turn a live article URL into a press clip that looks like the real coverage — the publication's own logo, fonts, photos and layout kept intact, the ads and clutter removed, and (for a roundup) just the client's section. Renders to PDF. You inspect each site and tailor the removal; the bundled script carries no site-specific logic.
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。
Set up a lightweight Google Alerts-style coverage tracker for any number of keywords. Creates a tracker config with each keyword and what it actually means, then hands recurrence to the user's agent harness.
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。
Performs a structured five-stage code review covering requirements compliance, correctness, code quality, testing, and security/performance. Each stage uses targeted checklists and categorized feedback (Blocker/Major/Minor/Nit) with actionable suggestions and rationale. Use when the user asks for code review, PR feedback, pull request review, or wants their code checked for bugs, style issues, or vulnerabilities — triggered by phrases like "review my code", "check this PR", "review my changes", "pull request review", or "code feedback".
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。
Run all reference benchmarks under benchmarks/eval/ and refresh the reference-table cells in benchmark_*.py. Auto-detects host hardware (H200/H100/H800/...). For each row's matching hw entry: replace cells in place. For new hardware or a new workload tag: append a new row to the section's table. Local-Pipeline-Result tables are skipped. One slash command runs everything end-to-end and auto-commits.
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。
Test quality review drawing on twelve classic engineering books — with primary focus on xUnit Test Patterns, The Art of Unit Testing, How Google Tests Software, and Working Effectively with Legacy Code — that diagnoses structural problems in an existing test suite: brittleness, mock abuse, coverage illusions, slow execution, poor readability. Triggers when: user asks about test quality, shares test files for review, or expresses frustration: "tests keep breaking whenever I change anything", "our tests take forever", "tests pass but bugs still reach production", or "we have too many mocks". Do NOT trigger for: writing new tests from scratch (use the regular test-writing workflow) or testing framework/syntax questions — this skill reviews an existing suite for structural quality problems, not individual test authoring.
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 Thinking learning curriculum covering nine progressive modules across the full Problem, Solution, and Implementation Space methods plus a shared manufacturing reference scenario for teaching and practice
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。
Maintain the existing May Shorts teaching compositions using their legacy face-mode, scene-overlay, and karaoke-caption patterns. Use only when working on those examples or explicitly requesting this legacy scaffold. For new reels, Shorts, or short advertisements, use short-form-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。