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Use when the user asks to "track where my emails are actually landing after I send", "read my seed-list inbox vs spam vs promotions results", "trend my Gmail Postmaster / Microsoft SNDS reputation", or "did placement drop after my last send"; produces a per-provider inbox/spam/promotions placement read, a domain/IP reputation trend from Postmaster + SNDS, a send-over-send delta with named regressions, and a reusable SEND-S placement snapshot on your own exported telemetry. Not for the pre-send SPF/DKIM/DMARC auth pre-flight — use deliverability-qa; not for computing the EQS or running the vetoes — use email-quality-auditor. 邮件收件箱落点监测/收件箱vs垃圾邮件/Postmaster声誉趋势

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Generate paid-ad image assets from a validated creative brief and brand profile using an explicitly configured image provider. Triggers on: generate ads, generate ad images, create ad creatives, create ad images, make ad images, generate visuals, make campaign visuals, generate images from campaign brief.

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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.

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State management architecture for Flutter using Riverpod, Provider, and BLoC patterns. Use when choosing a state solution, implementing reactive state, resolving rebuild issues, or structuring MVVM/BLoC architecture.

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Covers Flutter testing across all three layers: unit tests (business logic, ViewModels, repositories), widget tests (UI rendering, interactions, golden regression), and integration/E2E tests (full app flows, native OS interactions). Use this skill when writing any Flutter test, setting up mocking with mocktail or mockito, implementing golden file tests, debugging async failures (pumpAndSettle timeouts, Timer leaks, FakeAsync deadlocks), fixing cross-platform golden pixel diffs in CI/CD, testing state management (Riverpod/BLoC/Provider), handling permission dialogs or native system UI with Patrol, or troubleshooting MediaQuery/Theme missing errors in widget tests.

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Take an agent-written app from repo to live production on the user's OWN accounts, with providers they choose (hosting, database, auth, payments, email, domain/DNS). The human connects accounts and approves changes; supported wiring operations run through a local CLI and produce verification evidence with explicit limits. Use when the user wants to ship, deploy, go live, launch, publish, or put their app online, or asks to wire up env vars, webhooks, auth settings (signup, email confirmation, password policy), a real signup → confirmation email → login journey, password recovery, account isolation between two users, auth redirects, email DNS or a custom domain.

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Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.

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Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code int...

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Use for Nauthilus authentication and identity-provider work touching OIDC, OAuth2, SAML, MFA, TOTP, WebAuthn, recovery codes, LDAP-backed identity, browser login and consent flows, token/session/flow state, `private_key_jwt`, introspection, discovery metadata, endpoint-specific client authentication, and security-sensitive auth tests.

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Model sports rules, event formats, prediction types, scoring implications, lock rules, data requirements, and provider constraints for FriendlyBet. Use when adding or comparing sports such as football, basketball, American football, tennis, tournaments, leagues, playoffs, brackets, weekly picks, or World Cup-specific logic.

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Plan or review FriendlyBet architecture, implementation, schema, data flows, scoring, provider integrations, static/PWA behavior, Supabase/RLS impact, migrations, automation, and technical sequencing. Use when a task asks how to build, refactor, generalize, integrate, test, or safely ship FriendlyBet code.

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Review FriendlyBet quality, regression risk, test plans, release readiness, version bump discipline, scoring/locking correctness, provider fallback behavior, and dirty-worktree safety. Use before shipping app code, scoring changes, migrations, sports integrations, copy updates, PWA cache changes, or any risky user-facing flow.

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Control FriendlyBet operating cost, free-tier viability, provider/API cost, GitHub Actions/Supabase/Vercel usage, documentation hygiene, company memory updates, playbook maintenance, and skill validation. Use when evaluating cost, operational burden, tooling, internal docs, company memory, or whether agent profiles should become full skills.

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React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

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Bu Flutter template'inde uctan uca yeni feature iskelesi kurar — lib/feature/<ad>/ klasor yapisi, Freezed state + Cubit, StatelessWidget ya da StatefulWidget+ViewModel view, BlocProvider yerlesimi (global state_initialize mi lokal mi), TypedGoRoute, LocaleKeys cevirileri, AppPaddings/textTheme/colorScheme token'lari ve zorunlu <feature>.md modul dokumani. Kullanici "yeni feature ekleyelim", "su sayfayi projeye gore yaz", "cubit + state + view kur", "feature iskeleti cikar", "scaffold a feature" dediginde kullan.

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How to upgrade `alchemy` and the `effect` constellation across this repo and keep them consistent for consumers: which packages pin what, why `effect` and every `@effect/*` companion move as one set, what breaks in a typical upgrade, and how to verify a standalone `npm install` still resolves a single `effect`. Use when asked to upgrade or bump alchemy or effect, when a deploy dies inside an alchemy provider with a `TypeError` naming a missing combinator, when `check:npm-effect-resolution` fails, or when deciding whether the alchemy patch is still needed.

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Monitor for API billing errors and alert the owner and admin immediately. Use when: an API billing error is detected, a peer PA reports a billing error, or during routine health checks. Handles detection, notification, and fallback model switching. Model-agnostic: works with any LLM provider (Anthropic, OpenAI, Google, etc.).

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 generating cloud architecture diagrams as code — creating, modifying, or reviewing infrastructure diagrams using the Python Diagrams library. Covers AWS, Azure, GCP, Kubernetes, on-premises, and SaaS provider nodes. Generates PNG/SVG architecture diagrams from Python code with Graphviz rendering.

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Use when working with Coveo — coveo enterprise search platform management including sources, indexes, query pipelines, machine learning models, usage analytics, and security providers. Covers indexing health, query performance, ML model status, content freshness, and license utilization.

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Use when working with Cloudhealth — cloudHealth by VMware multi-cloud cost management and governance. Covers cost reporting, rightsizing recommendations, governance policies, budget tracking, reserved instance management, and compliance auditing. Use when analyzing cloud spend across providers, enforcing tagging policies, or tracking budgets.

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Use when working with Cert Manager — cert-manager certificate lifecycle management. Covers certificate issuance, issuer configuration, ACME challenges, certificate renewal, troubleshooting failed issuance, and trust management. Use when managing TLS certificates in Kubernetes, debugging issuance failures, configuring ACME providers, or monitoring certificate expiration.

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Use when working with Azure Cdn — azure CDN management covering profiles, endpoints, custom domains, caching rules, origin groups, and performance analytics. Supports Microsoft, Verizon, and Akamai CDN providers within Azure. Use when managing Azure CDN endpoints, analyzing cache performance, configuring delivery rules, or troubleshooting content delivery.

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 working with Prowler — prowler cloud security assessment tool. Covers AWS, Azure, and GCP security posture assessment, CIS benchmark evaluation, compliance frameworks (PCI-DSS, HIPAA, SOC2), multi-account scanning, and remediation guidance. Use when assessing cloud security posture, running compliance audits, or investigating security findings across cloud providers.

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 working with Aws Ecs — aWS ECS cluster health, service status, task analysis, capacity provider management, and deployment tracking. Covers service stability, task failure investigation, container insights, resource utilization, and scaling 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。