「ema」の検索結果

E-Mail-Entwürfe auf die Merkmale prüfen, mit denen Spamfilter Werbepost erkennen, und empfangene Nachrichten auswerten, die im Junk gelandet sind. Nutze diesen Skill, wenn eine Mail vor dem Versand geprüft werden soll, wenn jemand wissen will, warum eine Nachricht im Spam- oder Junk-Ordner gelandet ist, oder wenn Betreff, Text, HTML und Kopfzeilen einer Mail auf Aufbau- und Inhaltsfehler durchgesehen werden. Prüft unter anderem Linktext gegen Linkziel, defekte Abmeldewege nach RFC 8058, erfundene Thread-Bezüge, sichtbare Seriendruckreste, versteckte Zählpixel, Domainstreuung sowie unbelegte Zahlen und Superlative. Sagt keine Zustellung voraus und ist kein Werkzeug, um Filter zu umgehen. Für die Frage, ob eine Kaltakquise-Mail überhaupt versendet werden darf, ist cold-email zuständig.

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Expert guide for autonomous API schema drift detection, OpenAPI / gRPC breaking change monitoring, self-healing SDK adapter generation, and zero-downtime client-server synchronization / Panduan ahli deteksi drift skema API otonom, pemantauan breaking change OpenAPI / gRPC, pembuatan adapter SDK self-healing, dan sinkronisasi client-server tanpa downtime.

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Implements email service abstraction with SendGrid provider. Includes template support, localization, async sending, and domain event integration for transactional emails.

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Piaget's constructivism, schema theory, and cognitive development as practical tools for curriculum design. Covers assimilation, accommodation, equilibration, the four stages (sensorimotor, preoperational, concrete operational, formal operational), conservation tasks, schema-based reading and problem-solving, and the distinction between developmental readiness and domain-specific expertise. Use when designing age-appropriate material, diagnosing why a learner is not assimilating new content, or building on prior knowledge.

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Emit Postgres.sql and SQLite.sql from a single schema spec so tools work across both drivers without duplicating DDL by hand. Use when designing a schema that needs to support both shared Postgres deployments and zero-config SQLite. Reduces two-file sync burden to a single source edit.

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爆款拆解复刻：把抖音/TikTok 爆款带货视频（链接、转写或口述结构）拆成 8 维结构与 5-beat 节拍，再映射到你的商品，输出拆解表 + 3 个复刻角度 + 可渲染 storyboard.json。Use when the user says 爆款, 拆解, 复刻, 对标, 仿拍, viral remake, breakdown, swipe file, copy structure, 竞品视频, remake a TikTok/Douyin product video, or wants to replicate a viral ecommerce short's structure with their own product.

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CatColab Schemas - database schema modeling distinguishing entities (tables) from attributes (columns). Foundation for ACSets (Attributed C-Sets) and AlgebraicJulia data structures.

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GTM prospecting, enrichment, outreach, and Deepline Play work/audits. Providers: adyntel,affinity,ai_ark,akta,allegrow,amplemarket,apify,attention,attio,aviato,bettercontact,bigquery,bluesky,bounceban,brave,browserbase,builtwith,cbinsights,clay,clickhouse,cloudflare,contactout,contextdev,crunchbase,crustdata-v3,customer_db,databricks,dataforseo,datagma,dealroom,deepline_ip_to_company,deepline_native,deeplineagent,discolike,dropleads,edges,emailbison,emailguard,enformion,enigma,exa,findymail,firecrawl,fireflies,firmable,forager,fullenrich,fundable,generic_http,getleads,gong,google_ads_audiences,google_workspace,govfiles,grain,hackernews,harvestapi,heyreach,hubspot,hunter,icypeas,instantly,intercom,ipqs,kaspr,kernel,leadmagic,lemlist,limadata,linkedin_ads_audiences,luma,lusha,meta_audiences,millionverifier,nooks,notion,openmart,opensosdata,openwebninja,outreach,parallel,peopledatalabs,pitchbook,podscan,polymarket,postgres,predictleads,prospeo,quickenrich,rapidapi,redshift,rocketreach,salesforce,salesforge,….

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Snapshot test email templates using Verify to catch regressions. Validates rendered HTML output matches approved baseline. Works with MJML templates and any email renderer.

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High-precision semantic search and content retrieval via Exa API. Use when: (1) Deep research requiring semantic understanding, (2) Code documentation and examples lookup, (3) Company/professional research, (4) AI-powered comprehensive research tasks, (5) URL content extraction with structured output. Triggers: "research", "find papers", "code examples", "company info", "LinkedIn profiles", "deep analysis". Differentiator: Exa excels at semantic/neural search while grok-search is better for real-time news and general web content.

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Semantic codebase search, code indexing, and prompt enhancement via standalone CLI. Use when: (1) Semantic code search with natural language queries, (2) Code indexing for remote codebase retrieval, (3) Prompt enhancement with codebase context, (4) Before grep/find/glob operations for better accuracy, (5) Complex requirements clarification, (6) Large codebase navigation. Triggers: "search context", "enhance prompt", "find code that", "index project", "clarify requirements". IMPORTANT: Always use ace-tool BEFORE grep/find/glob for semantic-level code location.

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Develop and direct female-audience AI short dramas through role-specific workflows for showrunning, screenwriting, casting and original character design, art, performance, cinematography, storyboarding, sound, post, continuity, and asset handoff. Use when the user asks for 女频短剧、微短剧、言情或非言情女性向故事、女主成长、关系戏、职业戏、女性群像、选题、剧本、改稿、选角定妆、分镜运镜、生图/生视频制作说明、项目圣经或跨工种协作。

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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。

VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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SQLite database expertise for migrations, multi-tenant patterns, transactional safety, FTS5 virtual tables, and schema evolution. Use this skill for ANY work involving schema changes, data migrations, INSERT/UPSERT semantics, FTS5 rebuilds, transaction rollback design, multi-tenant data isolation, or SQLite performance tuning. Triggers include: writing migration SQL, modifying `_import_table`-style importers, designing UNIQUE/PK constraints, adding indexes for JOINs, debugging "rows missing" / "wrong count" / "stuck for hours" symptoms in SQLite-backed systems.

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Generates email sequences for different contexts. Currently supports event follow-up sequences. Produces ready-to-send emails with subject lines, body copy, and timing guidance.

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Use when you want an email sequence, especially event follow-up emails with timing guidance and ready-to-send copy.

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Use when creating outreach sequences, writing cold email campaigns, building multi-channel cadences, designing follow-up flows, or crafting signal-triggered messages. Triggers: 'build an outreach sequence', 'write a cold email sequence', 'create a cadence', 'outreach for [signal]', 'email sequence', 'follow-up sequence', 'multi-channel outreach'.

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aerc is a terminal-based email client written in Go with first-class support for IMAP, SMTP, JMAP, Maildir, and Notmuch. It features Vim-like keybindings, email threading, HTML rendering, built-in patch management, and deep UNIX integration through pipes and commands.

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Strategic marketing leadership guidance for B2B SaaS and technology companies. Covers go-to-market strategy, product marketing, content marketing, demand generation, SEO, community building, event marketing, PR, partnerships, and pricing strategy. Use when planning marketing strategy, launching products, building brand awareness, driving demand, or scaling marketing operations. Use for "marketing plan", "GTM strategy", "content strategy", "demand gen", "product launch marketing".

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Expert GTM marketing copywriter for emails, content, and social media. Use when writing marketing emails, email sequences, newsletters, blog posts, LinkedIn posts, Twitter/X threads, social content, brand copy, or personal brand content. Use for launch announcements, product updates, thought leadership, and engagement copy.

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Builds strip and tail-end fund models with remaining portfolio analysis, unfunded obligation treatment, and duration-adjusted pricing. Use when modeling strip deals, evaluating tail-end portfolios, or analyzing remaining value.

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Structures book-building analysis with demand tiers, allocation methodology, and price sensitivity assessment. Use when managing book-building, analyzing investor demand, or optimizing allocation strategies.

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Maps institutional investor targeting with AUM analysis, sector allocation preferences, and historical participation patterns. Use when targeting investors, analyzing demand profiles, or building investor marketing lists.

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。