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Expert-level composites engineering covering fiber reinforced polymers, matrix materials, laminate theory, manufacturing processes, failure modes, and composite design.

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Think and work like an expert Composites Engineer. Use when a task calls for Composites Engineer judgment. Reasons from CLT/ABD laminate mechanics, Halpin–Tsai micromechanics, and CMH-17/NCAMP allowables through autoclave/OOA/RTM process control, ASTM D30 mechanical qualification, ultrasonic C-scan and CAI damage tolerance while treating fiber waviness, void content, under-cure, and quasi-isotropic strength traps as first-class failure modes.

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Use when working with the non-metallic engineering materials — polymers, ceramics, or composites — and you need to reason about structure, processing, or properties. Covers thermoplastics versus thermosets, chain structure, glass transition, and viscoelasticity in polymers; ionic and covalent bonding, sintering, brittleness, and Weibull statistics in ceramics; and fiber-reinforced laminates, matrix and reinforcement roles, the rule of mixtures, and anisotropy in composites. Reach for it to choose a plastic, understand why a ceramic fails, or predict the stiffness of a laminate.

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Creates and manages AWS CloudWatch composite alarms using the CloudWatch PutCompositeAlarm API. Builds alarm rule expressions from existing metric alarms with AND/OR/NOT logic for multi-signal alerting.

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End-to-end news-triggered signal composite. Takes any piece of news — an article, LinkedIn post, tweet, announcement, event, trend, regulation, product launch, acquisition, layoff, expansion, or any other public event — and evaluates whether the companies or people mentioned are ICP fits. If yes, identifies the connection between the news and your product, finds the right people to contact, and drafts personalized outreach using the news as the hook. Tool-agnostic. Accepts both company-level and person-level news triggers. AUTO-TRIGGER: Load this composite whenever a user shares a URL (LinkedIn post, article, tweet, blog post) or mentions a company/person they "came across", "saw", or "found" from any external source and asks about relevance, fit, ICP match, or whether to reach out. The user does NOT need to explicitly say "outreach" — any signal evaluation request from an external source triggers this.

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Assemble the FREE steps of the flat-vector-explainer video format — a flat-illustration host character (who, where, tone, voice and music come from the recipe choices) walks a countable N-step product routine, one step per beat, and Remotion composites every chip/numeral/tagline/slate/CTA as an animated DOM overlay ON TOP of the Kling i2v character clips (text is NEVER baked into a keyframe — i2v warps type), the closing 'N products' grid is a PIL composite of the REAL product photos (not AI), full-sentence VO drives word-by-word burned captions over a VO-forward music bed, and the ~50s animated silent master is re-cut to a 30s deliverable FROM the animated master (never a static intermediate). Documentation-grade — ships config.example.json + PIPELINE.md + a README of the free assembly; the paid gen steps (keyframes, Kling i2v, VO, music) are separate capabilities the recipe orchestrates. Use for the flat-vector-explainer format.

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Assemble a cosmic-mythology-voiceover reel from a config — one spoken voiceover carries the whole narrative while N curated stills in one chosen look are weighted beat-synced across the delivered VO duration (cut_dur = VO_dur times weight over the weight sum, so emotional beats hold longer), Ken-Burns-zoomed per still (scale 2x, center crop, zoompan, fade-in first and fade-out last), ffmpeg-concatenated, the VO composited under the picture (libx264 crf18 plus aac), the ONE on-screen hook line faded on over the open with a drawtext alpha window, and Whisper/VEED captions burned along the bottom — never in-world text on a still. This is the FREE deterministic assembly stage (weighted sequence plus Ken-Burns plus concat plus VO composite plus hook overlay plus caption burn); the VO and the stills come from create-vo-elevenlabs and create-image-fal. Use for the cosmic-mythology-voiceover format.

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Assemble a wordless macro-tabletop food-product sizzle ad from a config — normalize fps and SAR across ~4 photorealistic macro clips (hands tearing, flat lay, bite, box hero), concat them, apply a global anti-AI grain pass (eq plus hqdn3d plus noise), composite the audio (a non-diegetic instrumental music bed plus a couple of short diegetic SFX like a snap and a tear placed at measured cue points, loudnorm), composite a STATIC end card entirely in PIL (real logo PNG plus real product PNG plus a serif heritage headline plus a CTA — never AI-rendered text), and burn optional serif stat-callout pills at beats. This is the FREE deterministic assembly stage (normalized concat plus grain plus music and SFX mix plus PIL end card plus callouts); the macro keyframes, i2v clips, and music bed come from create-image-fal, create-video-fal, and create-music-elevenlabs. Use for the food-product-sizzle format.

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Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to the VO's product-name word-starts (Whisper word-level timestamps), then ~5 Playwright product overlay cards (real PDP-verified taglines) are composited onto the master each on its product-NAME word-start, the SEPARATE VO is mixed on top of a ducked music bed at loudnorm I=-14, clean-white 3-words/cue captions are burned, and the video closes on a flat-lay end card. This is the FREE deterministic assembly stage (re-cut to the VO word-starts, hard-concat, Playwright card render + card composite, VO plus music mix, caption burn, flat-lay end card); the VO, scene clips, product cutouts, and music come from create-music-elevenlabs / create-image-gpt-image-fal / create-video-fal. Use for the glassy-matte-grwm format.

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Assemble a split-screen creator ad from a config — a two-zone vertical composite where a supplied AI-creator lip-sync take fills the BOTTOM ~48% while real 16:9 product/demo clips run uncropped in the TOP ~52%, each top clip contain-fit with a darkened blurred cover-scale fill of the same clip (never black bars), a 3px brand-color divider between the zones, the creator slice cover-fit per the per-scene VO timing, scenes hard-concatenated with the body audio being the concatenated creator VO slices, an end card held on the last sharp frame ~3s, then the ASSEMBLED cut transcribed with local Whisper (not the raw VO — concat drops inter-scene silence) and word-level captions burned in the chosen style. This is the FREE deterministic assembly + caption stage (two-zone composite + blurred fill + divider + hard-concat + end card + captions); the VO comes from create-vo-elevenlabs, the anchor from create-image-gpt-image-fal, and the whole-VO lip-sync from a paid VEED Fabric 1.0 take (a no-atom upstream input). Use for the split-screen-creator format.

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Build, review, or improve Core Data persistence in apps that have not adopted SwiftData. Use when working with NSManagedObject subclasses, NSFetchedResultsController for list-driven UI, NSBatchInsertRequest / NSBatchDeleteRequest / NSBatchUpdateRequest for bulk operations, NSPersistentHistoryChangeRequest for persistent history tracking and multi-target sync, NSStagedMigrationManager for staged schema migrations (iOS 17+), NSCompositeAttributeDescription for composite attributes (iOS 17+), or when integrating Core Data threading with Swift Concurrency. For Core Data + SwiftData coexistence or migration, see the swiftdata skill instead.

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Assemble multiple plots into ONE publication-ready multi-panel journal figure (e.g. Figure 1 with panels A, B, C). Use whenever the user asks to combine, compose, or lay out several plots as a single composite figure — newly plotted from data or from already-rendered panels the user supplies (PNG/PDF). Ask the user to pick one of two approaches: (1) redraw every panel into one unified figure using independent, tightly packed `subfigures` (each sized to its own labels, so axes need NOT align), consistent style, correctly placed panel letters, and per-panel legends/colorbars; (2) composite already-rendered PNG/PDF panels onto a mosaic canvas and add panel letters (image compositing, not plotting). Both export vector PDF + high-DPI PNG. For a SINGLE plot from a data table, use the sibling `omics-plotting` skill instead.

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Use Adobe Firefly Services to generate, edit, expand, fill, match, composite, and upscale still images through the current REST APIs. Apply when selecting Firefly Image 5 versus Image 3/4 or custom models, implementing authenticated asynchronous image workflows, using style or structure references, building product composites, handling provenance and enterprise rights, or diagnosing Firefly image jobs in production. Exclude Firefly video, audio, and unrelated Creative Cloud APIs.

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Provider-independent VFX compositing direction for generated video, ads, trailers, product films, social clips, explainers, mixed-source edits, and image/video composites. Use when an agent must plan, brief, generate, integrate, repair, or quality-check visual effects composites involving plates, alpha/mattes, keying, roto, tracking, stabilization, matchmove, lighting/color integration, grain/noise/sharpness, shadows/reflections/contact, depth/atmosphere, AI-generated elements, clean plates, editor/colorist handoff, rights/safety, or compositing QA.

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Use when authoring or reviewing CI/CD pipelines — GitHub Actions workflows, reusable workflows, composite actions, OIDC federation to AWS/GCP, caching, artifacts, and pipeline security hardening. Triggers on edits to .github/workflows/**, action.yml, composite action definitions, or mentions of "CI", "CD", "pipeline", "GitHub Actions", "workflow", "OIDC", "runner", "deploy script", "release", or "build pipeline".

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Expert-level nanomaterials engineering covering synthesis, characterization, properties at nanoscale, nanocomposites, safety, and industrial applications of nanomaterials.

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Expert-level aircraft structures covering structural design philosophy, wing and fuselage analysis, fatigue and damage tolerance, composite structures, and certification.

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Windows アプリ開発 (Windows App SDK / WinRT) のファイル・設定・データ保存リファレンス。 Windows.Storage の StorageFile, StorageFolder, IStorageItem, FileIO, PathIO, CachedFileManager, DataReader, DataWriter。ApplicationData, ApplicationDataContainer, ApplicationDataCompositeValue によるローカル・ローミング設定。 FileOpenPicker, FileSavePicker, FolderPicker, StorageApplicationPermissions, KnownFolders によるファイルアクセスと権限。JsonObject, JsonArray, XmlDocument, SQLite, EF Core によるシリアライズと永続化。

Issue/PR の状態とプロジェクト Status の自動同期を設定する。モード A は `Fandhe-AI/actions/project-sync` Composite Action を使う `.github/workflows/project-sync.yml` を生成 (PAT または GitHub App トークン)。モード B は既存の不整合を一括補正。「自動同期セットアップ」「PR レビュー時に In Review 化」「ボードと Issue の状態を同期」などで使用。

Complete guide for xUnit test output and logging. Use when you need to implement test output, diagnostic logging, or ILogger alternatives in xUnit tests. Covers ITestOutputHelper injection, AbstractLogger pattern, structured output design. Includes XUnitLogger, CompositeLogger, performance test diagnostic tool implementations. Keywords: ITestOutputHelper, ILogger testing, test output xunit, test output, test logging, AbstractLogger, XUnitLogger, CompositeLogger, testOutputHelper.WriteLine, test diagnostics, logger mock, test log, structured output, Received().Log

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参考映像から測定した色やカットのリズムを使い、生成動画と既存映像を編集・合成して、数値で照合した完成動画と再編集用のタイムラインを作るスキル。

• 参考映像のスタイルで動画を作りたいとき
• 既存映像に生成クリップを追加したいとき
• 映像素材や3D小物の合成

Retrieve the composite country resilience score (0-100) and its domain/pillar breakdown for a single country. Use when the user asks how resilient a country is, or wants its numeric resilience score, trend, or per-domain breakdown.

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Retrieve composite country risk intelligence — Country Instability Index (CII), travel advisory level, and active sanctions exposure — for one country by ISO code. Use when the user asks how risky or unstable a country is right now.

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Composite Phase-2 audit worker (ADR-150). Bundles harness oia-manifest + threat-model + mcp-scan into one timestamped audit record stored in the `metaharness-audit` memory namespace. Designed for cron-scheduled drift detection.

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