「delivery」の検索結果

Enforces staged execution discipline on large tasks: a written stage plan, parallel delegation where the runtime supports it, a failable verification check at each stage, and a skeptical self-review before delivery. Trigger when the user explicitly asks OR when the task objectively spans multiple files, sources, or sessions. Do NOT trigger on ordinary multi-step requests that a direct attempt handles fine (autonomous triggering only; explicit invocation always runs).

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AFA design, scope-to-fee matching, negotiation preparation, health check, and scope dispute assessment for in-house legal ops teams managing outside counsel arrangements. Design fee structures (fixed, capped, collar, blended, phased, success). Assess whether scope supports a proposed AFA. Prepare commercial positions for fee negotiations. Review existing AFAs against delivery data. Assess OOS claims and build dispute response. Trigger on: 'structure the fee', 'move off hourly', 'design an AFA', 'does scope support a fixed fee?', 'negotiate the fee', 'renegotiate the arrangement', 'is our AFA holding?', 'fee health check', 'cap is being approached', 'firm is claiming OOS', 'is this in scope?', 'is this OOS?', 'AI should reduce the cost', 'blended rate vs fixed', 'collar arrangement', 'phased fees'.

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Transforms reading-oriented prose into listening-optimized text for flat, neutral vocal delivery — TTS, podcasts, audiobooks, CLE audio. Carries a legal layer: case citations, section symbols, subsection lettering, Latin terms and footnotes are unspeakable as written, so a brief, opinion, statute, contract or memo needs them expanded, restructured or stripped before it can be listened to — and quoted authority is never rewritten. Use when converting written content for audio, preparing oral argument by ear, producing CLE or client-facing audio, or making a document listenable on a commute. Triggers on "make this listenable," "convert for audio," "optimize for reading aloud," "prepare for TTS," "make an audio version," "podcast script," "read this aloud." Supports English, French, Spanish, Italian, German and Portuguese; outputs plain text, ElevenLabs audio tags, or SSML for Amazon Polly, Google or Azure.

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Predicts access barriers in a learning task before delivery, given a learner variability profile. Distinguishes between barriers addressable through design and those requiring specialist support.

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Create an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.

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Expert knowledge for Azure Event Grid development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring Event Grid/MQTT namespaces, securing endpoints, routing events, integrating Functions/Service Bus, or troubleshooting delivery, and other Azure Event Grid related development tasks. Not for Azure Event Hubs (use azure-event-hubs), Azure Service Bus (use azure-service-bus), Azure Notification Hubs (use azure-notification-hubs), Azure Web PubSub (use azure-web-pubsub).

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Check whether an x402 payment endpoint is reliably delivering value before spending USDC on it. Returns paid delivery rate, active incidents, latency, and a clear proceed/warn/block recommendation.

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Diagnostic audit for a running cold email program. Checks domain authentication (SPF/DKIM/DMARC), inbox health/reputation from Smartlead, bounce rate by inbox type, and optionally runs a spam placement test via Smartlead's Smart Delivery API. Outputs markdown report + CSV with per-domain/per-inbox scores and concrete action items. Use when reply rates drop, when bounces spike, when onboarding someone else's account, or as a weekly/monthly health check.

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Use when the user mentions GPT Image 2.0 or GPT Image 2.5, gpt-image-2, gpt-image-2.5, gpt_image_2_5, GPT-Image-2 prompts, the Flare / Sunburst variants, a transparent-background image, or wants to generate an image with GPT Image 2.0 or 2.5. Covers when to prefer GPT Image 2.5 over 2.0 (transparent background, xhigh/max quality, extra aspect ratios — from platform and OpenAI facts), the CLI-vs-MCP disagreement on gpt_image_2, the three-format prompt taxonomy (Format A structured JSON for UI mockups and layout-dense images; Format B dense cinematic prose for single-subject scenes; Format C auto-derive meta-prompt for theme-only concepts), per-format craft patterns, output conventions, the 6-item pre-delivery checklist, and cross-surface workflow context (companion static-ads-workflow.md for ad recreation; higgsfield-marketing-studio cross-surface-workflow.md §3 for ms_image / DTC Ads Higgsfield-native alternative).

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Prevent Terraform/OpenTofu hallucinations by diagnosing and fixing failure modes: identity churn, secret exposure, blast-radius mistakes, CI drift, and compliance gate gaps. Use when generating, reviewing, refactoring, or migrating IaC and when building delivery/testing pipelines.

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Deliver implementation PRs across Avibe, avibe-backend, avibe-docs, avault, and vault-sandbox. Required for branch and scope discipline, Codex review, CI, circuit breaking, and user-facing close-out, regardless of agent backend.

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Demonstration preparation, audience-tailored presentations, feedback collection, and business outcome measurement. Load when preparing demos or measuring business value delivery.

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Advanced distributed patterns - event sourcing, CQRS, saga, stream processing, append-only log, exactly-once delivery, sequencer, double-entry ledger, erasure coding, order book, watermarks

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Weekdays. The only routine in this kit that opens a screen inside an account that can spend, and everything it does there is read. It confirms the primary conversion event still fired inside the read window before it trusts any other figure, then reads yesterday's spend, delivery, and result rows at account, campaign, ad set, and creative level and appends one row per object per day to the daily metrics ledger with the screen, the date range, and the read date beside every figure. It creates nothing, saves nothing, activates nothing, and spends nothing, unless you released the channel.

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Dung khi so lieu marketing dang xau va can biet TAI SAO — chan doan theo 5 lop tu tracking, delivery, creative, landing den chat luong audience, roi ra action plan 48h. Kich hoat khi user nhac 'so dang xau', 'CPMess cao qua', 'ROAS thap', 'chan doan root cause', 'tai sao khong ra don', 'ads dot tien'. Khong dung cho — audit CAU HINH tai khoan ads va cham Health Score thi dung skill 21-audit-ads-performance; viet bao cao cho nguoi khac doc thi dung skill 07-bao-cao-marketing; chan doan rieng mot trang thi dung skill 68-cro-audit-trang.

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Use when marketing numbers look bad and the user needs to know WHY — layered root-cause diagnosis across tracking, delivery, creative, landing page, offer, and audience quality, 5-Whys, regional benchmarks for US, EU, SEA, and LATAM, and a 48-hour action plan. Covers dropshipping ROAS and BE-ROAS. Trigger on 'why is CPA so high', 'my ads are not converting', 'ROAS dropped', 'we are burning budget', 'performance is bad this month', 'diagnose the funnel'. Also use when the user pastes a screenshot of numbers with no question attached. Not for — auditing account configuration and scoring health, see `21-ads-audit-global`; writing a report someone else reads, see `07-marketing-report-global`; turning a raw export into insight, see `13-data-analysis-global`.

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将自媒体创作里程碑保存成文件，管理版本、核验路径、生成完整发布包并更新内容索引。用于保存平台第一版完整成稿、多平台合集、短视频脚本、分镜、定稿、发布包和复盘报告，或用户说“保存一下、整理交付、归档、生成发布清单”时。标题微调、删一句和临时候选不单独保存新版本。

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Reviews a completed change for acceptance, regressions and release risk; read-only, not a whole-codebase audit.

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Build dual-write notification services with database persistence and FCM push delivery in NestJS. Use when creating notification entities, sending push via FCM, or implementing in-app notification feeds.

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Integrate push and local notifications using FCM and flutter_local_notifications in Flutter. Use for notification delivery or presentation; defer badge-only UI and notification-service tests.

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Define the delivery metrics contract for agent-assisted SDLC — DORA four plus per-stage indicators derived from artifact and git history, and the control bands that turn metric drift into a routed intake. Use when reporting cycle time, plan adherence, or defining response thresholds.

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Implement WorkManager and background processing correctly on Android. Use when creating Worker classes, scheduling tasks, choosing between WorkManager and Foreground Services, or setting up Hilt in workers; defer FCM and notification delivery to android-notifications.

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50+ named UX rules with numeric thresholds, 30+ UI styles catalog, industry anti-patterns, pre-delivery checklist

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Email delivery infrastructure - DNS authentication (SPF/DKIM/DMARC), subdomain isolation, provider abstraction, template systems, bounce handling, warmup strategy, and deliverability monitoring.

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。