1,052 件 ・ 関連度順
概要と使いどころ
Differential abundance and state analysis for cytometry data. Compare cell populations between conditions using statistical methods. Use when testing for significant changes in cell frequencies or marker expression 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。
Visualize copy number profiles, segments, and compare across samples. Create publication-quality plots of CNV data from CNVkit, GATK, or other callers. Use when creating genome-wide CNV plots, sample heatmaps, or chromosome-level visualizations.
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。
Differential binding analysis using DiffBind. Compare ChIP-seq peaks between conditions with statistical rigor. Requires replicate samples. Outputs differentially bound regions with fold changes and p-values. Use when comparing ChIP-seq binding between conditions.
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。
Comprehensive US stock analysis including fundamental analysis (financial metrics, business quality, valuation), technical analysis (indicators, chart patterns, support/resistance), stock comparisons, and investment report generation. Use when user requests analysis of US stock tickers (e.g., "analyze AAPL", "compare TSLA vs NVDA", "give me a report on Microsoft"), evaluation of financial metrics, technical chart analysis, or investment recommendations for American stocks.
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 "allocate my influencer budget", "optimize spend across tiers", or "compare budget scenarios"; produces a tier/platform/content allocation table, ROI and CPM/CPE projections, scenario comparisons, and mid-campaign reallocation moves. Not for building the full campaign plan — use campaign-planner. 达人预算分配/投放预算优化
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 "run a launch retro / post-mortem", "compare launch results vs targets by channel", or "decide what to keep or kill for the next launch"; produces a structured D1/W1/M1 retrospective — a per-channel actual-vs-target table (UTM-attributed own analytics as the truth column, platform self-reported numbers as reference, every figure labeled Measured / User-provided / Estimated), a 5-Whys chain on the single largest miss, keep / kill / change decisions per channel, 3-5 actionable learnings for the next launch, and an outcome snapshot submitted to the launch registry. Not for return math (CPA / ROI) — use roi-calculator; not for the stakeholder-facing report writeup — use report-generator; not for a metric deep-dive — use performance-analyzer. 发布复盘/渠道归因/5-Whys/keep-kill
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 influencer campaign performance", "compare influencers", or "find what content worked"; produces metric scorecards vs target and benchmark, platform/influencer/content rankings, engagement-quality and sentiment reads, conversion-attribution breakdowns, and ranked learnings. Not for dollar-level return math — use roi-calculator. 达人营销效果分析/投放复盘
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 platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (monthly) reconciliation workbook that de-dups stacked credit against an order-ID truth set, normalizes attribution windows and currency, compares attribution models, and reads incrementality from a geo/holdout test. Not for the point-in-time R2 veto or RQS gate — use ad-account-auditor; not for the ROI/ROAS ratio math itself — use roi-calculator; not for organic dark-social share attribution or GA4 direct-traffic decomposition — use dark-social-attributor. 付费广告归因对账/去重/增量
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 "read back" a paid campaign change, "did this ad change work", or "compare ROAS/CPA before and after"; reads ROAS/CPA against a control over a fixed readback window and returns a Promote / Keep-testing / Rollback / Unproven readback decision with the math delegated to roi-calculator. Not for RQS scoring or veto adjudication — use ad-account-auditor; not for the ROI ratio math — use roi-calculator; not for cross-channel rollups — use performance-analyzer. 付费广告复盘/ROAS回看/投放效果归因
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。
Compare UX patterns, features, strengths, and gaps across rival products. Use when you need to know what others actually do. For deliberately adopting their conventions, use `jakobs-law` (interaction-design).
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。
Migrate workloads from Heroku to AWS. Triggers on: migrate from Heroku, Heroku to AWS, move off Heroku, migrate Heroku Postgres to RDS, migrate Heroku Redis to ElastiCache, migrate Heroku Kafka to MSK, migrate dynos to Elastic Beanstalk, migrate dynos to Fargate, migrate Heroku Private Space, Heroku to ECS, leave Heroku, what-if workshop, compare migration scenarios, workshop mode. Runs a 6-phase process: discover Heroku resources live via the authenticated Heroku CLI (read-only, consent-gated) and/or from Terraform, Procfile/app.json, and billing exports, then clarify, design, estimate costs, generate artifacts, and collect feedback. Clarify must finish before Design, Estimate, or Generate. An optional post-Estimate what-if workshop reprices region/HA/compute/Graviton scenarios. Do not use for: GCP migrations (see gcp-to-aws), Azure migrations (see azure-to-aws), AWS-to-Heroku reverse migration, general AWS architecture advice without migration intent, or Heroku-to-Heroku refactoring.
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。
Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook discovery, security audits, dependency questions, and quick diagnostics — anything that needs a 5-30 second answer rather than a 5-8 minute deep investigation. Trigger words include cost, optimize, review, architecture, topology, what runbooks, show me, compare, audit, what if.
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。
Analyze DEX liquidity pools for TVL, volume, fees, impermanent loss, and LP profitability. Use when analyzing liquidity pools, calculating impermanent loss, or comparing DEX pools. Trigger with phrases like "analyze liquidity pool", "calculate impermanent loss", "LP returns", "pool TVL", "DEX pool metrics", or "compare pools".
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。
Calculate NFT rarity scores and rank tokens by trait uniqueness. Use when analyzing NFT collections, checking token rarity, or comparing NFTs. Trigger with phrases like "check NFT rarity", "analyze collection", "rank tokens", "compare NFTs".
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。
Compare multiple job offers side-by-side with total compensation 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。
Research, compare, and update shared AI model JSON for TypeScript, web, and Rust consumers. Covers text model tiers, image and video generation models, image tool models, release provenance, pricing data sourcing, and product-side catalogue cost estimates. Use when bumping model versions, adding new models, updating pricing, or auditing model specs against provider documentation.
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 analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.
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 analyze competitors' App Store strategy, find keyword gaps, or understand competitive positioning. Also use when the user mentions "competitor analysis", "competitive research", "keyword gap", "what are my competitors doing", or "compare my app to". For keyword-specific research, see keyword-research. For metadata writing, see metadata-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。
Add file-based observability, tracing, and run analysis to LLM/agent experiments — per-turn transcripts, tool calls and results, reasoning traces, token/cost accounting, per-episode artifacts, plus terminal viewers and a run-comparison report. Platform-agnostic: one small adapter covers OpenAI, Gemini/Vertex, Anthropic, LiteLLM, Tinker, vLLM, or any custom inference stack, and the same tooling then works unchanged. Use this skill whenever the user wants observability, tracing, logging, or run tracking for model experiments; asks why an agent failed a task or wants to replay/debug/diff an episode; wants to compare models, arms, or ablations; wants to instrument a new folder, repo, or platform ("add observability here", "do the same for Tinker/Gemini/OpenAI"); wants to import or tie in existing experiment results so old runs show up alongside new ones; or wants eval runner scripts where many models share one protocol. Reach for this even when they only say "log what the model is doing", "I can't tell what happened in this run", or "set up traces for this experiment".
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。
Establishes what a product is understood to be, for whom, and instead of what — then turns that into the messaging every other surface inherits. Use this when messaging is inconsistent across channels, when prospects misunderstand what the product does, when entering a new segment, when competitors are being compared against you unfavorably, or before any campaign, launch, or site rewrite.
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。
Evaluates where to spend limited capital — investment appraisal, hurdle rates, payback, and comparing proposals that are not alike. Use this to evaluate an investment or major purchase, compare competing funding requests, set a hurdle rate, decide between building and buying, or review whether past investments delivered what was claimed.
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。
Baidu E-commerce skill for cross-platform price comparison, review analysis, and purchase knowledge. Complete workflow from product discovery to purchase decision. Use when user wants to compare prices, read reviews, or make purchase decisions.
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。
Apply when facing a novel UI interaction or architectural decision with no precedent in the codebase. Build 2-3 competing prototypes and compare side by side before committing.
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。
Process, clean, and compare mass spectrometry (MS/MS) spectra with Matchms; use when you need reproducible spectral filtering and similarity scoring for metabolomics 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。