「experiment」の検索結果

Diagnose why a landing page, homepage, pricing page, or signup form is not converting, and produce a ranked fix list with a test plan. Runs a structured audit across motivation, value clarity, friction, anxiety, and CTA hierarchy rather than giving generic design opinions. Use when the user says "why isn't this page converting", "improve our conversion rate", "CRO", "conversion audit", "this page isn't working", "high traffic low signups", "people bounce", "review our landing page", or shares a URL and asks what is wrong with it. For rewriting the words only, see copy-review. For writing a new page from scratch, see landing-page-writer. For the statistics of running the test afterwards, see growth-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。

Generate A/B copy variants grounded in Eugene Schwartz's awareness and market-sophistication stages and John Caples' tested-headline discipline. Every variant declares its angle, the awareness stage it targets, and a falsifiable hypothesis, and the skill recommends which pair to test first and what delta counts as signal. Use when the user says "A/B test this", "write variants", "give me options", "test different angles", "copy variants", "ab copy", "test this headline", "multiple versions", "which version is better", or wants to test copy before publishing. For reviewing copy that already exists, see copy-review. For sample size and stopping rules, see growth-experiment. For diagnosing a page rather than its words, see page-cro. For full paid ad sets by platform, see ad-campaign-writer.

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。

Diagnose and draft or explicitly apply paid-ad optimizations using evidence, financial constraints, experiments, and capability-gated adapters. Use for campaign optimization, budget reallocation, bid changes, pausing or archiving ads, requests to delete campaigns, search-term or negative-keyword actions, creative rotation, or improving CPA and ROAS.

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 a professional paid-advertising strategy covering objectives, economics, platform selection, campaign architecture, audiences, budget, creative, measurement, experiments, governance, rollout, and reporting. Use for ad plan, media plan, PPC strategy, paid-social strategy, campaign architecture, advertising roadmap, or channel planning.

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 and model paid-media CPA, CPL, CPC, CPM, ROAS, MER, break-even targets, contribution margin, LTV:CAC, impression-share opportunity, budgets, forecasts, and experiment economics. Use for PPC math, ad calculator, break-even analysis, ROAS calculator, CPA calculator, budget forecast, LTV CAC, or MER.

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。

Help authors learn from exemplary ICLR, ICML, and NeurIPS papers through source-linked manuscript comparisons, concrete writing and experiment suggestions, and guided reflection. Use for research storytelling, contribution framing, paper comparison, figure planning, or research retrospectives. Not an acceptance predictor or a routine grammar/citation formatter.

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 professional paid advertising across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for account intake, source-grounded audits, strategy, budget and measurement planning, creative production, experiments, reporting, monitoring, and explicitly approved campaign changes. Also trigger on PPC, paid social, retail media, attribution, tracking, landing pages, cross-platform conversion totals, negative keywords or search terms, beta-feature scoring, stale platform claims, API-token or credential setup, campaign deletion, and safe Claude Ads installation or uninstall.

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 用户想根据论文、科研文档、研究文本、图注、开题/答辩材料或具备读图条件的参考图生成可复制的 AI 科研绘图提示词；触发场景包括论文配图、科研绘图、图形摘要、Graphical Abstract、机制图、技术路线图、实验装置图、模型架构图、多面板对比图、汇报总览图、参考图风格迁移、未知领域母版生成，或上传/引用 PDF、Word、LaTeX、Markdown、摘要、方法段、图注、课题说明、研究方案、参考图片。Also use when the user asks for scientific figure prompts, research illustration prompts, graphical abstract prompts, mechanism diagrams, technical roadmaps, experimental setup diagrams, model architecture diagrams, multi-panel scientific figures, paper/conference figures, or AI image prompts based on papers, research documents, abstracts, methods sections, figure captions, proposals, reference images, PDFs, Word docs, LaTeX files, Markdown files, or research plans.

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。

Chemistry expert covering organic, inorganic, physical chemistry, lab safety, and experimental techniques

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 creating publication-grade scientific figure images or prompts, including graphical abstracts, mechanism diagrams, anatomy diagrams, surgical step figures, experimental workflows, pathology mechanisms, device principles, and structured paper illustrations. If the user asks to generate the image, use ChatGPT image generation.

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。

AI Growth Hacker — north star metric, AARRR funnel, viral loop, experimentation framework, retention hook สำหรับ startup และ e-commerce ไทย

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。

Multi-file hypothesis testing with keep/discard loop, compound baselines, and experiment logging

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。

AI-powered SEO operations: keyword intelligence, competitor gap analysis, Google Search Console optimization, and trend detection. Use when asked to research keywords, analyze competitor content gaps, audit GSC performance, or detect trending topics. For growth experiments see growth-engine; for content optimization see autoresearch.

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 Karpathy-style autoresearch optimization on any content. Generates 50+ variants, scores with a 5-expert simulated panel, evolves winners through multiple rounds, outputs optimized version + full experiment log. Use when optimizing landing pages, email sequences, ad copy, headlines, form pages, CTA text, or any conversion-focused content. Triggers on "optimize this page", "run autoresearch", "score these variants", "A/B test this copy".

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 implementing analytics with PostHog in a TypeScript app — capturing events, identifying users, adding feature flags, tracking errors, or wiring API lifecycle telemetry. Triggers on edits to analytics integration files, or mentions of "PostHog", "analytics", "feature flag", "event tracking", "capture", "identify", "A/B test", or "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。

Scientific research engine with adversarial review, tree search, and serendipity detection. Use when: exploring hypotheses, validating findings against literature, running computational experiments with quality gates, or hunting for unexpected discoveries. Do NOT use for simple Q&A, code editing, or non-research tasks.

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。

Refine academic writing for computer science research papers targeting top-tier venues (NeurIPS, ICLR, ICML, AAAI, IJCAI, ACL, EMNLP, NAACL, CVPR, WWW, KDD, SIGIR, CIKM, and similar). Use this skill whenever a user asks to improve, polish, refine, edit, or proofread academic or research writing — including paper drafts, abstracts, introductions, related work sections, methodology descriptions, experiment write-ups, or conclusion sections. Also trigger when users paste LaTeX content and ask for writing help, mention "camera-ready", "rebuttal", "paper revision", or reference any academic venue or conference. This skill handles both full paper refinement and section-by-section editing.

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。

Code auditor that grades software projects and the agents/developers who built them. Produces structured JSON + Markdown reports with a standardized rubric. Evaluates architecture, correctness, testing, authorship cohesiveness, ghost code, and more. Optionally ingests tmux session logs for process evidence and interrogates agents about specific problems found. Use when asked to "audit", "grade", "evaluate", "review code quality", "rate this project", "score the agents", or "assess the codebase". Especially useful after Marcus multi-agent experiments to grade agent output and track quality over time.

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 signal-based forms in Angular v21+ using the new Signal Forms API. Use for form creation with automatic two-way binding, schema-based validation, field state management, and dynamic forms. Triggers on form implementation, adding validation, creating multi-step forms, or building forms with conditional fields. Signal Forms are experimental but recommended for new Angular projects. Don't use for template-driven forms without signals or third-party form libraries like Formly or ngx-formly.

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。

Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

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 whenever a task involves running parallel work on a git repository without conflicts — e.g. "fix this bug while I keep working on my feature", "run Claude on two branches at once", "work on this task in isolation", "create a throwaway branch for this experiment", or anything where two agents or sessions might edit the same files. Also trigger when the user asks to use worktrees directly, or when an agent needs its own isolated checkout so it can work without disturbing the main branch. Even if the user just says "do this in parallel" or "don't mess up my current work", consider worktrees.

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。

Align, run, audit, and publish GEODE benchmark comparisons against Agent-World arXiv 2604.18292v1 across MCP-Mark, BFCL V4, and tau2-bench. Use for Agent-World or AgentWorld comparison requests, cross-suite agent benchmark design, Tau2 comparator/profile diagnosis, paired thin-runtime-versus-GEODE experiments, mean-accuracy@8 replication, or benchmark comparability and artifact reviews.

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。

Experimental behavioral evaluator. Drives a running artifact via browser/curl/CLI and records rubric evidence; the runner is not yet a fully implemented automated evaluation system.

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。

Experimental/manual harness canary procedure. It records benchmark manifests and scores but does not provide a fully automated runner.

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。