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概要と使いどころ
Frappe-specific search and discovery guidance for finding benches, apps, remotes, sites, ports, hooks, DocTypes, builder DocTypes, and frontend surfaces quickly. Use when the task starts with locating or classifying Frappe context.
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。
Investigation flow (Glob -> Grep -> Read), evidence-based research with file:line references, structured output format for AI consumption. Use for pattern discovery, implementation research, and codebase investigation.
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。
Product management workflows covering the full work lifecycle — discovery, strategy, execution, launch, and growth. Write PRDs, plan OKRs, and structure meeting notes. Useful beyond PMs — applicable to any knowledge worker managing projects, stakeholders, or strategy. Triggers: /write-prd, /plan-okrs, /meeting-notes
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。
Harness-neutral, discovery-only Gaia curation extension. A Sol/Terra-class orchestrator preflights capacity, shards safe volume work to configurable Luna workers, converges risky cases, and stops at human L4 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。
End-to-end Gaia curation pipeline orchestrator. Routes each phase to its dedicated skill and keeps you on track from first discovery to closed intake. Use when starting a fresh curation run or when you want a single skill to hold the sequence together without duplicating each phase's instructions. Trigger phrases: "/gaia-full-pipeline", "run the full pipeline", "start a curation from scratch", "take this skill through the full pipeline", "curate end-to-end", "pipeline run", "full curation flow". Fused from: gaia-curate + gaia-curate-chain + gaia-curate-dynamic + gaia-curate-trending + gaia-bot-curate + gaia-draft-curate + ev-pipeline + gaia-ingest + gaia-intake-close.
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。
Discovery-only global trending extension for Gaia. Snapshots configured external skill sources, prioritizes five-candidate pages for L4 review, and stops before trust, evidence, intake, or registry mutation.
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。
Fixed-topology, discovery-only extension for Gaia curation. Atomically checkpoints each candidate transition, retries only the failed field, and stops at human L4 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。
Discovery-only Gaia curation for one manually selected source page. Fetches and normalizes up to five real SKILL.md candidates, deduplicates and maps them for human L4 review, then stops without evidence scoring or registry mutation.
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。
Builds a hand-sculpted stop-motion CLAY ad on the Novoads REST API as a STORYBOARD: five to eight beats, each rendered from its own key frame, a storyteller narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's arc (named protagonist, inciting moment, social beat, quiet despair, sculpted clay infographic, discovery, transformation, resolution card), and also recreates a found clay ad by reading the reference video locally with ffmpeg and Whisper. Use for ANY clay or stop-motion ask at ANY length: "claymation ad", "stop-motion ad", "clay ad", "a quick clay ad", "plasticine characters", "make an ad like this clay one", or a reference video with sculpted clay characters in it. There is no one-call tier here, so ffmpeg is required. Not for the smooth 3D animated look (use pixar-ad, which covers every Pixar-style length), talking-head UGC (novoads-api), or a static image ad.
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。
This skill provides systematic bug detection and discovery capabilities for VS Code extensions. Use when searching for hidden bugs, analyzing code for potential issues, investigating suspicious behavior, performing code audits, or proactively finding bugs before they manifest. Covers static analysis patterns, dynamic analysis techniques, code smell detection, and systematic codebase investigation.
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。
Deep codebase exploration, architectural research, and solution discovery. Use when investigating problems, understanding complex flows, or evaluating technical approaches without jumping straight into code mutation or TDD.
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 a structured discovery session to build an Allium specification through conversation. Use when the user wants to create a new spec from scratch, elicit or gather requirements, capture domain behaviour, specify a feature or system, define what a system should do, or is describing functionality and needs help shaping it into a specification.
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 and characterize regulatory elements (enhancers, promoters, silencers, insulators, super-enhancers) using ENCODE data and the cCRE catalog. Use when the user wants to find candidate regulatory elements, identify active enhancers in a tissue, map promoter states, classify chromatin states with ChromHMM, identify super-enhancers with ROSE, understand the functional validation hierarchy (CRISPR > MPRA > reporter), or characterize non-coding genomic regions. Covers the full workflow from ENCODE cCRE lookup through chromatin state segmentation to functional validation and enhancer-gene linkage. Use this skill for ANY regulatory element discovery, classification, or characterization task.
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 for de novo and known motif enrichment analysis of ENCODE ChIP-seq and ATAC-seq peaks using HOMER and MEME Suite. Use when users need to discover TF binding motifs in peaks, validate ChIP-seq targets, or find co-binding partners. Trigger on: motif analysis, HOMER, MEME, de novo motif, motif enrichment, findMotifsGenome, AME, MEME-ChIP, known motif, TF binding motif, co-factor, motif discovery.
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。
Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE data.
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。
Orchestrates 6-phase SDLC pipeline (discovery, requirements, architecture, workstreams, implementation, summary) for guided feature development. Use when user runs /core:develop command, requests spec-driven development, wants to create implementation plans with architecture decisions, or mentions "SDLC", "spec-driven", "plan feature", "development pipeline". Supports plan persistence, wave-based resume, autonomous mode, and architecture/implementation verification.
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 manage Volcengine cloud resources using the Volcengine CLI (`ve` command). Supports all Volcengine services including ECS, VPC, CLB, RDS, Redis, and more. Trigger this skill whenever the user asks to create, query, modify, or delete cloud resources on Volcengine, mentions the `ve` command, says "volcengine CLI", or describes infrastructure tasks such as "create an ECS instance", "set up a VPC", "list security groups", "allocate an EIP". Also trigger on Chinese prompts mentioning "火山引擎" or "火山" (e.g., "火山引擎上有哪些 ECS"、"查一下我火山的云服务器"、 "火山引擎创建一个 VPC"、"火山的 Redis 实例列一下"). Also trigger when the user encounters errors from `ve` commands and needs troubleshooting help. Also use for TOS bucket/object operations, tosutil (sometimes written tosutils), Ark CLI / arkcli model discovery, inference, generation, endpoints, fine-tuning, plans, or usage, and TLS (日志服务) / volclog log search, analysis, ingest, export, or LogCollector collection, through `ve tosutil`, `ve arkcli` and `ve volclog`.
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 native Linux packages (.deb / .rpm / .apk / .pkg.tar.zst) from a PKGBUILD or yap.json project using the yap-mcp Model Context Protocol server. Use this skill whenever the user asks to "build a package", "make a deb/rpm", "cross-compile for arm64/aarch64", "sign a release", generate SBOMs, install a built artifact, or diagnose why a yap build failed. The yap MCP server exposes async builds with buildID polling, validation, dependency-graph inspection, and artifact discovery.
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 loss prevention — data discovery, classification, policy enforcement across endpoint, network, and cloud.
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 consumer ordering experiences — discovery, cart, checkout, tracking, and reorder flows that convert.
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。
ChIP-seq analysis — peak calling, differential binding, motif discovery, and QC with phantom-peak metrics.
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。
Deploy cloud access security brokers — shadow IT discovery, SaaS governance, and cloud data protection.
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。
Optimize content for AI answer engines (AEO/GEO): citation-friendly structure, factual precision, and measuring AI visibility. Use when AI search drives discovery.
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 provides a Facebook URL or asks to read personal posts, comments, reactions, friends, timelines, profiles, stories, feeds, groups, events, or saved items, or to publish personal text posts, comments, and replies, or to discover public events happening near a place, nearby, or in a local area on a date, or to create, edit, publish, or delete their own Marketplace listings. To find, browse, or buy Marketplace listings, use shopping instead. Use pages commands for managed Facebook Page discovery, insights, native draft editing/deletion, same-draft publication, approved posts and native scheduling.
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。