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Reverse JavaScript-based custom DSL/VM interpreters, non-standard WASM-like runtimes, and risk-control engines. Use when analyzing IIFE or switch-based opcode dispatchers, extracting instruction tables, recovering bytecode semantics, capturing VM state at runtime, or reconstructing execution flow.
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 for free/open reverse engineering with Ghidra (headless or GUI), including decompile, cross-refs, and optional Ghidra MCP workflows when IDA is unavailable.
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 for authorized macOS and Mach-O reverse engineering including codesign, Objective-C/Swift recovery, endpoint security surfaces, and Apple platform malware analysis.
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。
Add captions or subtitles to an existing single-subject talking-head video without editing the footage. Use for plain verbatim captions, cinematic captions embedded behind the subject, VFX captions, “炸/特效/酷炫字幕,” or a named identity from the 35-style catalog. Route by visual identity, not by backend engine. The quiet `anchor` rail is the default; embed every word only when the user explicitly wants a fully cinematic treatment. The workflow runs locally end to end, including transcription and subject matting; split multi-shot footage before applying 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。
Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.
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 for authorized reverse engineering of browser extensions (Chrome/Firefox) including manifest analysis, background workers, and extension-based credential or traffic logic recovery.
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。
Your AI research and engineering brain trust. 59 named personas across 8 cells covering frontier labs, applied product, model architecture, reasoning/RL/agents, alignment and interpretability, theory and science of DL, multimodal and…
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 an immersive scroll-scrubbed "fly through the world" landing page for any industry or brand using Higgsfield. As the visitor scrolls, a pre-rendered camera flies from outside each scene into its interior, then flows on to the next scene with NO cuts — one continuous connected flight (Emons-style isometric diorama world, or any art direction you pick). The skill interviews the user for the topic, the story beats/sections, and brand kit, then generates cohesive scenes + seamless camera clips with Higgsfield and wires a portable, framework-agnostic scroll-scrub engine. The video chain renders through Monid by default (Seedance 2.0, pay-per-clip USD — capability re-checked each build, see Step 4) with Higgsfield credits as the fallback biller. Use when the user wants a "3D world" / "browse-through-the-industry" hero, a scroll cinematic, a diorama landing, or to turn a business into a scrollable world.
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 building AI features into a product: LLM integration, RAG pipelines, guardrails, streaming, AI UX, prompt engineering, or AI cost control. Treats prompts as code and validates every model 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。
Clone any website into a pixel-perfect single-file HTML prototype. Extracts design tokens, assets, CSS computed styles, interaction patterns, and content via Playwright. Outputs a self-contained HTML file with real data injection. Use when the user wants to clone, replicate, reverse-engineer, or create a pixel-perfect copy of any website or web app. Provide one or more target URLs as arguments.
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 repeatable AI prompt or workflow into a structured, shareable skill for the affiliate-skills GitHub repository. Use this skill when the user wants to create a new skill, write a SKILL.md, convert a prompt to a skill, share a skill via the GitHub repo, or document an AI workflow. Also trigger for: "create a skill", "write a skill", "make this a skill", "turn this into a skill", "publish skill", "add skill to list", "write SKILL.md", "skill from prompt", "document this workflow", "package this as a 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。
Convert YouTube videos to SEO-optimized blog posts. Extract video title, description, and content, then generate a search-engine-friendly blog post with embedded video, cover images, optimized metadata, structured Markdown sections, clean resource blocks, and canonical 5-8 keywords. Auto-generates English filenames and saves to the configured Hexo blog posts directory. Includes tag management rules to maintain a clean, consistent tag taxonomy.
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。
Review a diff or file through the Chisle lens: flag over-engineering, speculative abstractions, reinvented stdlib, and verbose code that a lazier approach would shrink. One finding per line, no praise. Use when the user says "chisle review", "review this for bloat", or invokes /chisle-review.
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。
Detect and investigate bulk registration abuse on SaaS platforms. Given access to a user database (or exported CSV/JSON), run a multi-dimensional anomaly analysis — email domain clustering, registration tempo, UA fingerprinting, session structure, usage patterns, and credit consumption — to produce a scored abuse report with actionable recommendations. Use when investigating suspicious sign-up spikes, credit fraud, free-tier abuse, or account farming.
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 laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
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。
Evaluation criteria and scoring for data engineering artifact reviews
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 a launch needs a repeatable EXECUTION playbook — a T-30 to D+7 timeline, per-function checklists for content, design, ads, sales, and engineering, a launch-day war room, an escalation matrix, and roll-back criteria. Trigger on 'launch playbook', 'launch checklist', 'launch day plan', 'launch SOP', 'war room', 'we launch in two weeks and nothing is organized'. Also use when a GTM strategy exists and nobody knows who does what on the day. Not for — the strategy and beachhead choice, see `59-go-to-market-global`; the campaign brief, see `02-campaign-brief-global`; the post-launch review, see `63-campaign-retrospective-global`; a live crisis, see `66-crisis-playbook-global`.
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。
Collect auditable public X/Twitter posts by controlling the user's already logged-in Chrome, searching X's rendered web interface, scrolling visible results, and extracting original post text and metadata from DOM into normalized JSONL. Use for VOC research, social listening, multilingual keyword discovery, competitor monitoring, or historical search when X requires the user's browser session and cookies, credentials, internal GraphQL, paid APIs, or search-engine snippets must not be exported or used. X data layer of the bggg VOC suite (shared project folder; orchestrated by industry-orchestrator, reported by bggg-voc-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。
Zero-config goal-to-tasks engine. Takes any goal (software, pentest, business, learning), runs adaptive discovery, generates a validated spec, parses into TaskMaster tasks, creates an implementation plan, and executes with built-in CDD verification. Use when user says "PRD", "product requirements", "I want to build", or any goal-driven phrase.
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。
The Atlas engine — turn any goal into a validated PRD and an executable, verified task graph. Brand-name entrypoint; a thin alias for the `go` orchestrator. Use when the user types /prd:atlas, says "I want to build", or asks for a PRD / task-driven build.
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。
Expert AI art prompt engineer for Midjourney and Stable Diffusion. Generates high-quality prompts including unified batch illustrations, marketing designs, interactive compositions, and structured framework prompts with translations.
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。
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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。
Generates images and text via reverse-engineered Gemini Web API. Supports text generation, image generation from prompts, reference images for vision input, and multi-turn conversations. Use when other skills need image generation backend, or when user requests "generate image with Gemini", "Gemini text generation", or needs vision-capable AI 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。
Converts X (Twitter) tweets and articles to markdown with YAML front matter. Uses reverse-engineered API requiring user consent. Use when user mentions "X to markdown", "tweet to markdown", "save tweet", or provides x.com/twitter.com URLs for conversion.
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。