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概要と使いどころ
Compatibility alias for Loopy. Use only when an existing installation or older instruction explicitly invokes loop-library; use Loopy for new installations and requests. Provides the same discovery, recommendation, audit, repair, adaptation, guided crafting, bounded execution, run debrief, project loop saving, and publication-preparation 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。
Make AI-generated writing read as human-written, in fiction and in professional prose. Repairs the narrative architecture of fiction and stories (based on StoryScope, arXiv:2604.03136); routes professional text through domain rules for release notes, announcements, PR and issue replies, code-review comments, incident postmortems, tickets, work orders, technical articles, blog posts, and long-form journalism. Four operations - write, review (diagnose AI tells without editing), refactor (minimal in-place edits), recreate (full rewrite). Use when asked to humanize, de-AI, unslop, or strip AI flavor from any text; when writing or revising any of these document types; or whenever output must not read as machine-written.
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。
Electric neon glow effects with high-contrast color pairings for bold, attention-grabbing interfaces.
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 AI Document Intelligence SDK for Java (com.azure:azure-ai-documentintelligence). Use for extracting text, tables, key-value pairs from documents, receipts, invoices, IDs, or building custom document models. Triggers: "document intelligence java", "form recognizer java", "extract text from PDF java", "OCR document java", "analyze invoice receipt java", "custom document model java", "document classification java".
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。
Remove sequencing adapters from FASTQ files using Cutadapt and Trimmomatic. Supports single-end and paired-end reads, Illumina TruSeq, Nextera, and custom adapter sequences. Use when FastQC shows adapter contamination or before alignment of short reads.
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。
Supervised and unsupervised multi-omics integration with mixOmics. Includes sPLS for pairwise integration and DIABLO for multi-block discriminant analysis. Use when performing supervised multi-omics integration or identifying features that discriminate between groups.
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 copy number variants from targeted/exome sequencing using CNVkit. Supports tumor-normal pairs, tumor-only, and germline CNV calling. Use when detecting CNVs from WES or targeted panel sequencing 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。
Infer pathogen transmission networks and identify likely transmission pairs using TransPhylo and outbreak reconstruction algorithms. Estimate who-infected-whom from genomic and epidemiological data. Use when investigating outbreak transmission chains or identifying superspreaders.
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 homology-directed repair donor templates for CRISPR knock-ins using primer3-py. Create ssODN, dsDNA, or plasmid templates with optimized homology arms. Use when designing donor templates for precise insertions, tagging, or allele replacement.
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, repair, or migrate to Cloudflare Turnstile bot verification in an existing frontend and backend, including server-side Siteverify.
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 should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.
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。
Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores. Use when the user wants to execute a backtest, measure a rule they have described, obtain win rate / average win / average loss / max drawdown from real bars, or feed backtest-expert with measured numbers instead of estimates.
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 asks to "analyze competitors" or "竞品分析"; benchmarks competitor keywords, content, backlinks, AI citations, and traffic share into strengths, weaknesses, and an action plan. Not for a pairwise topic-coverage gap map — use content-gap-analysis. 竞品分析/竞争对手
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-feeling, benchmark-quality mobile app screens (Expo / React Native). Use when designing or implementing any mobile UI — screens, flows, onboarding, paywalls, tab bars, sheets, settings, empty states — or when polishing motion, navigation, typography, dark mode, or perceived performance. Enforces Apple HIG fidelity, semantic colors, native controls, anti-slop discipline, navigation semantics (push vs replace, modal vs sheet vs overlay, the one-way doors where back must not exist), purposeful Reanimated motion, a full-motion simulator-verified iteration loop, and a study-real-apps-first workflow (pairs with the Appllama MCP). Trigger on "build a screen", "make this screen better", "design the onboarding", "wire up this flow", "polish the UI", "make it feel native", or any mobile design/implementation 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。
Build and operate an Attio webhook receiver with raw-body HMAC verification, fast acknowledgement, durable queues, idempotent processing, retry awareness, and reconciliation. Use when implementing or repairing Attio event delivery. Trigger with "Attio webhooks", "Attio events", or "verify Attio signature".
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。
Establish a deterministic local EVM development loop with pinned forks, synthetic fixtures, and bounded Alchemy usage. Use when adding local chain tests or repairing flaky fork-based development. Trigger with "Alchemy local dev", "Hardhat fork with Alchemy", or "pin a mainnet fork".
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。
Select and prove the current Alchemy client, key type, network, and authentication boundary before integration work. Use when creating or repairing Alchemy connectivity. Trigger with "set up Alchemy", "configure an Alchemy API key", or "choose viem or Wallet APIs".
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。
Operate Alchemy Notify webhooks with raw-body HMAC verification, idempotent intake, durable processing, and safe lifecycle changes. Use when implementing or repairing blockchain event delivery. Trigger with "Alchemy webhook", "Alchemy Notify", or "verify X-Alchemy-Signature".
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。
Select and prove the correct Adobe authentication model, entitlement, product profile, and secret lifecycle before integration work. Use when creating or repairing Adobe credentials. Trigger with "set up Adobe auth", "Adobe OAuth server-to-server", or "Adobe user authentication".
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。
Organization-grade cloud and supply-chain attack-surface discovery: S3/GCS/Azure Blob bucket discovery via observed-name mining (CNAME/cert-SAN/Wayback) and bounded two-class permutation (6 prefixes x 15 suffixes on trusted tokens, bounded target-bound expansion on subdomain stems), existence (HEAD/GET) vs public-listing confirmation, object-key triage into 9 value tiers (database dumps, credentials, IaC state, kubeconfig, VCS dirs, config, archives, PII, logs), dangling-CNAME bucket-takeover detection, and the ownership-gated severity model that stops an unattributable public bucket from becoming a false CRITICAL; the fully offline AWS-account-ID recovery from a leaked AKIA/ASIA/AROA access key (base32 decode, runnable stdlib Python, canonical test vector, AWS-documentation-example-ID screening); dependency-confusion confirmation for npm/PyPI (internal-signal classifier -- private-registry binding vs org-namespace match -- paired with a read-only public-registry 404 check and the npm scope-claimability nuance the public search API misses); and passive cloud-native/container/Kubernetes/CI control-plane fingerprinting (Lambda URLs, API Gateway, Cloud Run, App Service, kubelet/etcd/K8s API/dashboard, Jenkins/GitLab/Argo CD) as an org-attribution and exposure surface. Passive/discovery only -- no exploitation, no credential submission, no active control-plane confirmation (a stage-6 validate_cloud active tier is described but out of scope). Use when enumerating a target's cloud storage footprint, recovering an AWS account ID from a leaked key, confirming a supply-chain dependency-confusion vector, or fingerprinting cloud-native/K8s/CI infrastructure for an authorized external recon engagement.
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 topic or finished script into a complete, publish-ready explainer video — led by an AI presenter from an authorized adult presenter image, or performed with no presenter in one of twelve explainer styles (nine visual styles and three narrative ones). Not for promos, ads, or footage montages. Use for new presenter or styled explainer videos and for continuing, revising, captioning, lip-sync repairing, or re-exporting an existing job. Use it whenever the user asks for 数字人口播 / 数字人讲解, for a 讲解视频 / 动画讲解 / 科普视频, asks which styles or templates are available (有哪些风格 / 看看风格 / 风格模板), or names one of the styles: 留白, 信号/科技感, 手帐/手绘, 立体书/纸艺, 波普漫画, 一镜到底/3D, 图纸与注脚, 黑板报, 黏土小城, 推演/动态图解, 案卷/调查复盘, 小剧场/生活场景. Keep model and provider selection capability-based and record the actual choices per job.
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, texture, rig, animate, stylize, convert, and download 3D assets for Three.js games via the Tripo API. Use for text-to-3D, image-to-3D, game-ready GLB/FBX, characters, creatures, buildings, props, weapons, terrain, auto-rigging, animation retargeting, model texturing, voxel/LEGO stylization, and low-poly conversion. Pair with threejs-image-generator for concept and texture references first.
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。
Traffic analysis and PCAP forensics playbook. Use when analyzing network captures including Wireshark filters, protocol analysis (HTTP/DNS/FTP/SMTP/USB/WiFi), data extraction, covert channel detection, PCAP repair, TLS decryption, and tshark command-line 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。
Establish durable brand and voice context for cross-skill consumption. Generates BRAND.md (audience, positioning, do/don't editorial rules, taboo phrases, competitor differentiation) and VOICE.md (existing persona JSON re-expressed as readable prose), both written to the project root. When present, the blog orchestrator auto-loads these files for write, rewrite, brief, outline, calendar, and strategy workflows. Pairs with blog-persona, which manages the structured persona JSON. Use when user says "blog brand", "create brand context", "brand voice doc", "BRAND.md", "VOICE.md", "establish editorial brand", "brand guidelines for blog".
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。