191 件 ・ 関連度順
概要と使いどころ
Help users plan, coordinate, and execute product launches that cut through market noise. This guide covers everything from internal alignment and GACCS briefs to community engagement and viral mechanics.
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。
Plan, draft, audit, and publish posts and threads for X (Twitter). Use when the user wants to write a single tweet or an auto-numbered thread, build a long-form tweetstorm, remove AI tells from a draft, reverse-engineer the hook from a viral tweet, draft a reply or quote tweet, or plan a week of X content. Tweets and threads publish via the Publora API, which auto-splits long content into a numbered thread. User provides notes or a tweet URL, the skill drafts, the user approves, then it publishes.
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。
Monitor Twitter/X, Reddit, LinkedIn, and Hacker News for trending narratives, viral posts, and hot-button topics in your space. Maps trends to ad hook opportunities with timing urgency scores. Tells you what to run ads about right now while the topic is hot.
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。
Assemble a viral iOS "AirDrop" notification-carousel video ad (≈6–8s, 9:16) from a brand line plus 6–16 real product photos — a native AirDrop share-sheet card ("Brand would like to share a ___ · Decline / Accept") springs up and its preview window CYCLES through the products, landing on a range/lineup payoff with an Accept tap; a chime + soft per-swap ticks track the swaps. DETERMINISTIC assembly — an HTML card (real DOM text) rendered to PNG via headless Chrome, chroma-keyed, its magenta window refilled per-product in PIL, then animated + audio-synthed with FFmpeg. FREE (no paid model calls); the recipe supplies the brand line, product images, and payoff and gates the only optional paid step (a hero shot when the brand has NO usable photo → create-image-fal). Use for the airdrop-notification-carousel format.
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。
Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate skills.
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。
Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile), within-sample (TPM, FPKM/RPKM), variance-stabilizing (VST, rlog, log-CPM), GC-content correction (cqn, EDASeq), and single-cell (scran deconvolution, scanpy normalize_total). Encodes the composition-bias rationale, the "most genes not DE" assumption and its catastrophic failure modes (MYC amplification, apoptosis, viral host shutoff, prokaryotic stress), the "lengthScaledTPM is not TPM" naming trap, the "TPM is not for DE" rule, the blind=TRUE vs FALSE decision, ERCC spike-in normalization (SBN), and the single-cell zero-inflation breakdown of TMM/RLE. Use when choosing or applying normalization, debugging shifted-MA-plot diagnostics, handling zero-heavy single-cell data, or correcting GC bias.
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。
Assigns pathogen lineages (SARS-CoV-2 Pangolin UShER mode; Nextclade clade + QC; pango-designation alias resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage-fitness modelling (multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data and Nextclade dataset version pinning (mandatory; lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme churn (V3/V4/V4.1/V5.3.2/Midnight) with dropout regions, and recombinant X-prefix designation lag. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater into lineage frequencies with Freyja, tracking lineage frequencies over time, handling ARTIC primer dropouts, or running surveillance for SARS-CoV-2/influenza/Mpox/RSV/H5N1/measles.
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。
Supply Chain Bottleneck Analyzer for TikTok Shop sellers. Diagnose cash flow, inventory turnover, affiliate commissions, and return rates. Includes FBT cost analysis, influencer payout optimization, and viral product lifecycle management. No API key required for basic 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。
Product research for TikTok Shop — viral potential scoring, creator demand, category 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。
Trending product discovery — viral product analysis, category trends, seasonal opportunities on TikTok
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。
Inventory management for TikTok Shop — demand forecasting, viral stock planning, FBT optimization
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。
E-commerce content marketing strategy planner. Generates content calendars, topic ideas, and platform-specific strategies by analyzing customer reviews, trends, competitor content, and SEO opportunities. Two modes: (A) Build — create a full content strategy from scratch, (B) Audit — analyze existing content and find gaps. Supports TikTok, Instagram, YouTube, Pinterest, blog/SEO, and Amazon A+. No API key required. Use when: (1) planning content for a new product launch, (2) building a content calendar, (3) finding viral content ideas, (4) analyzing competitor content strategies, (5) extracting customer pain points for content topics.
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 the user wants to plan, implement, or optimize referral program strategy. Also use when the user mentions "referral program," "referral marketing," "user referral," "refer-a-friend," "word-of-mouth growth," "referral rewards," "referral tracking," "referral code," "referral incentives," or "viral loop." For referral landing copy, use landing-page-generator.
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。
Engineer growth systems: PLG motions, referrals, viral and retention loops. "design a referral program"
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 the user wants to create, optimize, or analyze a referral program, affiliate program, or word-of-mouth strategy. Also use when the user mentions 'referral,' 'affiliate,' 'ambassador,' 'word of mouth,' 'viral loop,' 'refer a friend,' or 'partner program.' This skill covers program design, incentive structure, and growth optimization.
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 the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' or 'viral content.' This skill covers content creation, repurposing, and platform-specific strategies.
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 referral/invite infrastructure with unique codes, deep link sharing, reward tracking, and fraud prevention. Use when user wants referral codes, invite friends flow, or viral growth mechanics.
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。
Trending products and rising categories discovery for Amazon sellers. Analyzes Best Seller Rank patterns, seasonal trends, new release momentum, and emerging niches. Identifies product opportunities before they peak. Use when the user asks about what's trending on Amazon, hot products, rising categories, seasonal opportunities, viral products, what to sell next, emerging niches, or early-mover opportunities. Also trigger for questions like 'what should I sell now?', 'what products are doing well?', 'find me trending niches', or 'what's hot on Amazon?'.
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。
Applies Geoffrey Moore's chasm-crossing strategy for B2B tech products moving from visionary early adopters to pragmatist mainstream. Use when a product has early traction but stalls before mainstream adoption, when planning a beachhead/niche strategy, when designing whole-product offerings, when positioning against established competitors, or when scaling from innovator usage to industry standard. Triggers include 'stuck between early adopters and mainstream', 'we need a beachhead', 'pragmatist customers won't buy', 'how do we go from 10 to 1000 customers'. NOT for PLG/freemium SaaS (Slack, Notion, Cursor), pure consumer apps, two-sided marketplaces, or AI-native products with bottoms-up viral adoption - their dynamics break the visionary-to-pragmatist sequence.
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。
Write X/Twitter threads that get bookmarked, shared, and drive affiliate clicks. Use this skill when the user asks about writing Twitter threads, X threads, tweet threads for affiliate marketing, or says "write a thread about X", "Twitter thread promoting X", "X thread for affiliate", "write tweets that go viral", "thread that sells without selling", "educational thread with affiliate CTA", "Twitter content for affiliate marketing", "how to promote X on Twitter", "write a thread my audience will bookmark", "tweet storm about affiliate product".
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。
Write short-form video scripts for TikTok, Instagram Reels, and YouTube Shorts that promote affiliate products with strong hooks, demos, and CTAs. Use this skill when the user asks about TikTok scripts, Reels scripts, Shorts scripts, short-form video for affiliate marketing, or says "write a TikTok for X", "script a Reel promoting X", "YouTube Shorts script affiliate", "60-second video script", "hook for TikTok affiliate", "write a video promoting X", "TikTok script that converts", "short video script for product review", "viral TikTok affiliate script", "how to promote X on TikTok".
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 WeChat public-account articles that break out above the account's average reads for account-growth topic selection. Use when the user asks to discover 公众号爆款, 微信低粉爆款, 平均阅读爆款, 起号选题, category-based WeChat hot articles, or article references filtered by month_read_avg rather than unstable follower_count.
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 brand faces a communications CRISIS or a campaign is failing in public — L1 to L5 severity classification, a first-four-hours process, response templates by type, an escalation matrix, a do-not-do list, holding statements, and a post-mortem. Trigger on 'PR crisis', 'crisis playbook', 'a complaint is going viral', 'bad reviews are spreading', 'our content caused backlash', 'we are getting attacked online'. Also use when the user forwards an angry thread and asks what to do right now. Not for — monitoring before anything blows up, see `15-social-listening-global`; diagnosing weak performance numbers, see `03-performance-eval-global`; the routine post-campaign review, see `63-campaign-retrospective-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。
Use when published content has to be audited — pull channel data, classify winners and losers by percentile across pillar, format, and hook, find the pattern behind performance, and decide what to keep, kill, or scale. Trigger on 'content audit', 'which posts are working', 'content performance review', 'why did that one go viral', 'our reach is dropping', 'evaluate what we posted last month'. Also use when the user only says content does not seem to work anymore. Not for — the plan for next period built on these findings, see `40-next-content-plan-global`; paid ad account review, see `21-ads-audit-global`; the stakeholder report, see `07-marketing-report-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。