2,155 件 ・ 関連度順
概要と使いどころ
Reviews all your Google Ads extensions — sitelinks, callouts, structured snippets, call extensions, image extensions, price extensions — across every campaign. Flags what's missing, what's underperforming, what's outdated, and writes replacements based on your best performing ads and landing pages. Platform: Google.
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。
Replicate the 7 programmatic SEO plays that took Zapier, Clay, Composio, Gamma, Mintlify, HeyGen and HubSpot to
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。
Show an HTML chart, table, diagram, mockup, demo, or report inline in BB chat: write a small page directly in the reply as an inline-vis fenced block, or show a workspace or thread-storage HTML or Markdown file with the inline-vis directive.
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 this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, speech generation (TTS), voice design, voice replication, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. Covers SDK usage and best practices for Gemini models and agents in Python and TypeScript.
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 styling UI for replit.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.
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。
Skeptical review of outside contributions to public repos. Use when reviewing, ranking, or replying to public GitHub pull requests or issues from outside contributors, or when the user says "larp-detector".
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 or refine Chinese technical notes and articles in a concise, evidence-led voice. Use for substantive drafting or rewriting, not every Chinese reply.
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。
Show results as interactive UI inside Codeg's chat (cards, tables, charts, tabs, accordions, badges, progress bars, simple forms) by writing a json-render spec code block in your reply. Use when the user invokes this skill or asks to see something as a card, table, chart, dashboard or other visual layout in Codeg.
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。
Sample-size and statistical power calculations for planning studies. Use whenever someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for designs with no formula — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Use this skill even when the request only mentions an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-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。
Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity
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 or rewrite text in plain, layman-readable English in the spirit of ASD-STE100 Simplified Technical English: short sentences, active voice, simple tenses, one word one meaning, condition before command, every technical term defined at first use, no AI slop. Default mode is Plain. Strict mode applies full STE vocabulary compliance when the user names STE, ASD-STE100, or compliance. Use for documentation, READMEs, runbooks, procedures, error messages, release notes, incident reports, API guides, and explanations for readers outside the field. Also use when the user says "STE", "Simplified Technical English", "ASD-STE100", "plain English", "layman's terms", "explain it simply", "no jargon", "de-slop", "make this readable", "write for non-native readers", or asks for docs that translate well. The same rules govern the reply: answer first, prose only.
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。
Deterministic debugging with rr record-replay. Use when debugging crashes, ASAN faults, or when reverse execution is needed. Provides reverse-next, reverse-step, reverse-continue commands and crash trace extraction.
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。
Score observed price trend, confirmation, risk and participation without forecasting a price. Use when the user asks to momentum following with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 option candidates and score components, with funding, expiry and assignment risks. Use when the user asks to options strategies with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Separate reported claims from impact inferences, with related assets and next checkpoints. Use when the user asks to news impact with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 published research and institutional views with sources, dates and related assets. Use when the user asks to research reports with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Score ETF trend, risk, liquidity, cost and available tracking and theme signals while preserving data gaps. Use when the user asks to etf strategy with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 research records you provide to see changes in facts, scores and judgments. Use when the user asks to investment review with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Extract report views, ratings, key assumptions and risks with sources and dates. Use when the user asks to research report breakdown with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 a contribution schedule and calculate a supplied price-path cost basis without predicting returns. Use when the user asks to dollar-cost averaging with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 auditable grid from a price range, current price and capital. Use when the user asks to grid plan with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Aggregate user-supplied disclosed buys and sells by source without automatically copying trades. Use when the user asks to smart money tracking with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Score Hong Kong and China A-share dividend candidates across yield quality, durability, cash flow, valuation and momentum. Use when the user asks to dividend strategy with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Connect fundamentals, sentiment and risk to supporting and opposing evidence. Use when the user asks to stock opportunities with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。