「cta」の検索結果

Writes conversion-focused landing page copy - headlines, subheads, value propositions, feature and benefit blocks, social proof, FAQs, and CTA button text - using PAS, AIDA, or StoryBrand. Use when the user wants words for a landing page, sales page, product or pricing page, waitlist page, homepage hero, or ad-to-page flow, including rewriting weak copy, generating headline or CTA variants for A/B tests, or turning a product description into page sections. Use landing-page-optimizer instead for auditing an existing page's performance, and a frontend skill for building the page itself.

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Inject Call-to-Action blocks into Astro site content with intelligent placement strategies. Use when the user wants to add CTAs, newsletter signups, product promotions, or any content blocks to blog posts. Supports multiple placement strategies (end, after 50%, after 60%), content scoring for relevance, and dry-run preview.

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Use Hume Octave for emotionally expressive speech and voice production: text-to-speech, voice design, voice cloning, voice conversion, streaming/realtime TTS, multilingual narration, dialogue continuity, timestamps/lip-sync, safety/rights review, and production QA.

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Browser automation powers web testing, scraping, and AI agent interactions. The difference between a flaky script and a reliable system comes down to understanding selectors, waiting strategies, and anti-detection patterns. This skill covers Playwright (recommended) and Puppeteer, with patterns for testing, scraping, and agentic browser control. Key insight: Playwright won the framework war. Unless you need Puppeteer's stealth ecosystem or are Chrome-only, Playwright is the better choice in 2025. Critical distinction: Testing automation (predictable apps you control) vs scraping/agent automation (unpredictable sites that fight back). Different problems, different solutions. Use when "playwright, puppeteer, browser automation, headless, web scraping, e2e test, end-to-end, selenium, chromium, browser test, page.click, locator, playwright, puppeteer, browser, automation, testing, scraping, headless, e2e, selenium, web-testing" mentioned.

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Conversion Rate Optimization auditing for landing pages, signup flows, checkout funnels, forms, and CTAs. Identifies friction points, runs heuristic evaluations, produces prioritized recommendations using ICE/PIE frameworks. Use when the user asks about conversion optimization, funnel analysis, landing page audits, form optimization, CTA testing, or checkout improvement.

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Landing page audit and optimization for conversion. Covers above-the-fold design, value propositions, CTAs, social proof placement, form design, page speed, and mobile optimization. Use when the user asks about landing page optimization, conversion rate improvement, page audits, or CTA 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。

🔨 Andru.ia Skill-Smith (The Forge) workflow skill. Use this skill when the user needs Ingeniero de Sistemas de Andru.ia. Diseña, redacta y despliega nuevas habilidades (skills) dentro del repositorio siguiendo el Estándar de Diamante and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

🔨 Andru.ia Skill-Smith (The Forge) workflow skill. Use this skill when the user needs Ingeniero de Sistemas de Andru.ia. Diseña, redacta y despliega nuevas habilidades (skills) dentro del repositorio siguiendo el Estándar de Diamante and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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数据工程 — 数据平台从业者的认知操作系统, 覆盖把数据从源系统搬运成可靠 / 可查询 / 可信赖形态供分析 / ML / 数据产品消费的全生命周期 (生成 → 摄取 → 存储 → 转换 → 服务 + 安全/数据管理/DataOps/数据架构/编排/软件工程 六条暗流, Reis & Housley 框架): 摄取与集成 (批 + CDC 变更数据捕获 Debezium + EL 工具 Fivetran/Airbyte/Meltano/dlt + Kafka Connect + schema drift) / 存储与文件表格式 (对象存储数据湖 + 列存 Parquet/ORC/Arrow/Avro + 开放表格式 Apache Iceberg/Delta Lake/Apache Hudi + lakehouse + 分区/compaction) / 转换与建模 (ELT dbt/SQLMesh + Spark + 维度建模 Kimball + Inmon + Data Vault + 大宽表 OBT + 渐变维 SCD + 增量模型 + 语义/指标层) / 编排与工作流 (Apache Airflow/Dagster/Prefect/Mage/Kestra/Apache DolphinScheduler + DAG + 幂等 + 回填 backfill + 数据资产调度) / 批流与实时 (Apache Kafka/Apache Flink/Spark Structured Streaming/Kinesis/Pulsar/Redpanda + Lambda vs Kappa + watermark/窗口/exactly-once + 流式 SQL Materialize/RisingWave + 实时 OLAP ClickHouse/Apache Druid/Apache Pinot/StarRocks/Apache Doris) / 数仓与查询引擎 (Snowflake/BigQuery/Redshift/Databricks SQL/Trino/Presto/DuckDB/Polars + 存算分离 + MPP) / 数据质量测试与可观测性 (dbt tests/Great Expectations/Soda + 数据契约 + Monte Carlo data downtime + 新鲜度/量/schema 异常检测) / 数据治理编目与血缘 (DataHub/Amundsen/OpenMetadata/Unity Catalog + 列级血缘 + PII 分类 + 访问控制 + GDPR) / DataOps 与可靠性 (数据 CI/CD + 转换版本控制 + 环境隔离 + 幂等重处理 + 数据 SLA/SLO + 计算存储 FinOps) / 数据架构范式 (现代数据栈 + lakehouse + data mesh + data fabric + 去中心化 vs 中心化所有权) / 分析工程角色 (dbt 时代连接数据工程与分析的桥) — 不含 数据科学/ML 建模本身 (是下游消费者) / BI 仪表盘制作 (serving 下游) / 数据分析报表为终点 / 'data engineer = 跑 Hadoop 的' 过时窄化 / 通用后端应用开发 (平行学科) (Data Engineering — the cognitive operating system of practitioners who design, build, and operate the data platform: moving data from source systems into reliable, queryable, trustworthy form for analytics / ML / products, covering (a) the data engineering lifecycle (generation → ingestion → storage → transformation → serving, with the undercurrents security / data management / DataOps / data architecture / orchestration / software engineering — Reis & Housley framing), (b) ingestion & integration (batch + CDC change-data-capture with Debezium, EL tools Fivetran / Airbyte / Meltano / dlt, Kafka Connect, API + file + database sources, schema drift handling), (c) storage & file/table formats (object storage data lakes, columnar formats Parquet / ORC / Arrow / Avro, open table formats Apache Iceberg / Delta Lake / Apache Hudi, lakehouse architecture, partitioning / compaction / Z-ordering), (d) transformation & modeling (ELT with dbt / SQLMesh, Spark, dimensional modeling Kimball, Inmon CIF, Data Vault, One Big Table / wide tables, normalization vs denormalization, slowly changing dimensions, incremental models, the semantic / metrics layer), (e) orchestration & workflow (Apache Airflow, Dagster, Prefect, Mage, Kestra, Apache DolphinScheduler, DAGs, idempotency, backfills, data-aware / asset-based scheduling), (f) batch vs streaming & real-time (Apache Kafka, Apache Flink, Spark Structured Streaming, Kinesis / Pulsar / Redpanda, the Lambda vs Kappa debate, watermarks / windowing / exactly-once, streaming SQL Materialize / RisingWave, real-time OLAP ClickHouse / Apache Druid / Apache Pinot / StarRocks / Apache Doris), (g) warehouses & query engines (Snowflake, BigQuery, Redshift, Databricks SQL, Trino / Presto, DuckDB, Polars, decoupled storage & compute, MPP), (h) data quality, testing & observability (dbt tests, Great Expectations, Soda, data contracts, Monte Carlo / data downtime, freshness / volume / schema anomaly detection, unit / integration testing of pipelines), (i) data governance, catalog & lineage (DataHub, Amundsen, OpenMetadata, Unity Catalog, column-level lineage, PII / data classification, access control, GDPR / data privacy), (j) DataOps & reliability (CI/CD for data, version control of transformations, environments, idempotent reprocessing, SLAs / SLOs for data, cost / FinOps for compute & storage), (k) data architecture paradigms (modern data stack, data lakehouse, data mesh, data fabric, decentralized vs centralized ownership), (l) the analytics engineering role (the dbt-era bridge between data engineering and analysis); N

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Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".

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Use when the user has one or more video clips and wants to add post-production on top — AI-generated cover as first frame, HTML/CSS captions synced to SRT, kinetic illustration overlays at hook moments, chapter chips, end-card CTA, or any other timed motion graphics. Most often used as the downstream of `/wjs-segmenting-video` — pick up where that skill stopped (raw cropped clip + per-clip SRT) and produce the upload-ready MP4. Backed by HyperFrames so everything compiles to ONE final encode — no cascade of re-encodes. Triggers — "加封面", "加字幕", "加动画", "加 CTA", "做后期", "post-production", "title card", "kinetic captions", "end card".

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Use when working on landing pages — creation, copywriting, design, optimization, or conversion rate improvement. Covers hero sections, above-the-fold content, value propositions, CTAs, landing page templates, and high-converting page structure. Applies to sales pages, lead capture pages, product pages, and marketing site pages. Use this skill for landing page copy, landing page design, landing page optimization, CTA writing, conversion rate optimization, hero section content, value proposition work, and any page builder or landing page template 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。

用户要起草一条 X 短内容(推文/帖子)、不知道用什么结构或类型时;或问"怎么发一条教人用 XX 的帖""怎么排版推文能让更多人收藏""what structure should I use for a tweet / how to write a tutorial post"时。先按目标指标选四类型之一(故事→涨粉 / 列表→收藏 / 观点→互动 / 教程→忠诚),再用 Hook-Body-CTA 三段骨架起草;资源/工具类可套爆款公式(工具+场景+三步)。不适用于:已有草稿想检查五件套完备性(→x-five-piece-checklist)、想把公告腔改写成帮助式语言(→x-three-translations)、想按读者功能分类预测传播上限(→x-content-archetypes)、纯信息查询(如推文字数上限)。

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Audit and rewrite a Facebook Page for 2026: Page name, username and vanity URL, profile picture and cover photo, Intro/About and category, the CTA button (Shop, Book, Sign Up, Contact matched to your goal), pinned post, tabs order, and contact/link fields. Triggers on "review my Facebook Page", "fix my Page about", "optimize my cover", "set my CTA button", "Page audit". Converts a default Page into one that turns a visitor into a follower or a lead. Not for writing Page posts (use fb-post-writer).

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Query the Open Targets Platform GraphQL API for target-disease associations, genetic and clinical evidence, tractability and safety liabilities, target prioritisation metrics, known drugs and mechanisms of action, and disease ontology. Use this skill for target identification and validation, target-disease evidence review, druggability assessment, drug repurposing, and resolving gene, disease, and drug names to Ensembl, MONDO, and ChEMBL identifiers. Also trigger when a query mentions Open Targets, platform.opentargets.org, association scores, tractability buckets, or api.platform.opentargets.org.

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Analiza textos aplicando pensamiento crítico — el marco de los 8 elementos del pensamiento y los estándares intelectuales universales de Richard Paul y Linda Elder — y detecta las falacias lógicas graves presentes. Úsala siempre que el usuario comparta un texto (pegado o en un archivo) y pida analizarlo críticamente, detectar falacias, evaluar argumentos, identificar sesgos, o preguntas como "¿qué problemas tiene este argumento?", "¿es sólido este razonamiento?", "analiza esto", "dame una crítica". También actívala cuando el usuario comparta un artículo de opinión, un post, un discurso, un ensayo o cualquier texto argumentativo y quiera evaluar su calidad argumentativa.

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Systematic fuzzing across two dimensions: (1) content discovery — hidden directories, files, backup/source leaks, HTTP verb enumeration, 401/403 bypass via path manipulation; (2) input validation — auth/token stripping, type confusion, boundary value analysis, HTTP parameter pollution, header fuzzing, cookie fuzzing, mass assignment discovery, and entropy/predictability analysis of any generated value. Works on any domain. Chains from /web-exploit or /pentester; chains into /business-logic when boundary violations, predictable IDs, or mass assignment are confirmed.

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Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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Redacta un pull request para la rama actual rellenando la plantilla de PR del repositorio en función de los cambios de la rama. Úsalo cuando la persona pida abrir/crear un PR, preparar un pull request o escribir la descripción de un PR (p. ej. "abre un PR", "redacta el pull request de esta rama"). No hace merge.

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Designs the first screen visitors see — the hero section. Layout patterns (split, centered, asymmetric, full-bleed), navbar design, headline typography, CTAs, background treatments (gradients, video, particles, 3D), scroll cues, and above-the-fold conversion strategy. Activate on 'hero section', 'landing page hero', 'above the fold', 'first impression', 'homepage header', 'navbar design', 'hero layout', 'landing page design'. NOT for full multi-page site architecture (use web-design-expert), not for SEO content strategy (use seo-visibility-expert).

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Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.

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Suggests CSII with good adherence to monitoring and dosing for adults with type 2 diabetes mellitus who have poor glycemic control despite intensive insulin therapy, oral agents, other injectable therapy, and lifestyle modifications. Trigger phrases include 'T2DM on multiple injectables still uncontrolled' and 'Consider pump for insulin-requiring T2DM failing other therapies'.

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Chicago CTA L train arrivals, bus predictions, and service alerts.

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解释火山 AI 音视频互动的产品能力、适用边界与最新官方文档；生成或修改 VoiceChat/Aibot 配置；并帮助用户搭建、运行和分阶段排查最小 InteractAI VoiceChat Web Demo。

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。