296 skills · sorted by relevance
Build and verify Adaptive navbar for Documentation and knowledge with Bootstrap v5.3 using a working semantic implementation, responsive RTL/LTR behavior, theme tokens, test plan and design verification.
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Expert en technologies éducatives avancées (LMS, MOOC, adaptive learning, gamification, analytics, accessibilité)
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EdTech Specialist IA — Expert en technologies éducatives (LMS, SCORM, adaptive learning, gamification, assessment)
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Expert en technologies éducatives avancées (LMS, MOOC, adaptive learning, AI tutoring, assessment, DZ context)
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Windows アプリ開発 (WinUI 3 / Windows App SDK) のテスト・性能・アクセシビリティ・スレッド。 MSTest, xUnit, NUnit, WinAppDriver, Appium, Playwright, WebView2 テスト, CI, WACK, MSIX サイドローディング, version adaptive。LoggingChannel / ETW, WPT, WPA, プロファイリング, GC, 起動性能, XAML 最適化, ListView/GridView 仮想化。UI Automation, AutomationProperties, automation peers, キーボード操作性, ハイコントラスト, Narrator。DispatcherQueue, DispatcherQueueTimer, WinRT 非同期パターン, async/await, ConfigureAwait, スレッドプール, STA/MTA, デッドロック回避, バックグラウンドタスク。
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Tests genotype-environment associations and identifies adaptive loci while correcting for the four-confound landscape (structure, demography, background selection, sampling design) using LFMM2 with mandatory K via sNMF cross-entropy elbow (LEA 3), BayPass Core/AUX/C2/IS with Omega covariance matrix, RDA / pRDA for polygenic adaptation (Forester 2018; requires imputed genotypes), OutFLANK with trimmed FST null, pcadapt, gradient forests (Ellis-Smith-Pitcher 2012, NOT mis-cited Ellis-Manel), Capblancq & Forester 2021 RDA Swiss-army-knife, genomic-offset prediction with Lind & Lotterhos 2025 three-regime caveat, Lotterhos-Whitlock sampling optima, Wang & Bradburd 2014 IBD vs IBE, and Circuitscape + ResistanceGA. Use when identifying adaptive loci across gradients, choosing K for LFMM2, deciding among GEA methods, predicting maladaptation with the novel-environment caveat, distinguishing IBD vs IBE, or optimizing sampling design.
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Tests genotype-environment associations and identifies adaptive loci while correcting for the four-confound landscape (structure, demography, background selection, sampling design) using LFMM2 with mandatory K via sNMF cross-entropy elbow (LEA 3), BayPass Core/AUX/C2/IS with Omega covariance matrix, RDA / pRDA for polygenic adaptation (Forester 2018; requires imputed genotypes), OutFLANK with trimmed FST null, pcadapt, gradient forests (Ellis-Smith-Pitcher 2012, NOT mis-cited Ellis-Manel), Capblancq & Forester 2021 RDA Swiss-army-knife, genomic-offset prediction with Lind & Lotterhos 2025 three-regime caveat, Lotterhos-Whitlock sampling optima, Wang & Bradburd 2014 IBD vs IBE, and Circuitscape + ResistanceGA. Use when identifying adaptive loci across gradients, choosing K for LFMM2, deciding among GEA methods, predicting maladaptation with the novel-environment caveat, distinguishing IBD vs IBE, or optimizing sampling design.
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An innate exploratory drive that guarantees no graph node remains permanently invisible to an agent population. After a warm-up period (step > 3), each agent fires a coverage scan with probability |unseen_nodes| / |all_nodes|. When triggered, the agent teleports directly to the globally unseen node with the highest belief uncertainty, works it, and returns control to the normal action-selection loop. Probability is self-annealing: it starts near 1.0 when almost everything is unseen and decays toward 0.0 as coverage saturates, requiring no manual schedule. The mechanism is "innate" (hard-coded into the agent step loop) as distinct from the "adaptive" EFE path, which requires local neighbors and learned precision weights. Together they form a two-layer exploration architecture: adaptive for locally-guided foraging, innate for topological completeness.
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Skill converted from mcp-create-adaptive-cards.prompt.md
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Implements responsive design systems with mobile-first breakpoints, container queries, fluid typography, and adaptive layouts using Tailwind CSS. Use when users request "responsive design", "mobile-first", "breakpoints", "fluid typography", or "adaptive layout".
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Design task-specific workflows for repeated agent work, with pass/fail checks, progress records, and handoff notes. Identify when a temporary workflow should become a shared skill that teammates can run and evaluate again.
Automatically gathers the past 24 hours of activity from connected services into one morning dashboard, bringing together meetings, pending replies, tasks, and development updates in visual modules suited to each type of information.
Implement agents that use recorded task outcomes to choose future approaches. ReasoningBank supports matching past patterns, comparing strategies, retaining experience in AgentDB, and tracking how strategy success and learning change over time.
Build agent memory with ReasoningBank and AgentDB. Record actions and outcomes, retrieve similar experiences, assess results, and consolidate memories into reusable patterns so agents can draw on past work when making decisions.
Extract website content into Markdown, HTML, or plain text with Scrapling. Handle JavaScript-rendered pages and anti-bot challenges, or write Python crawlers that follow links, collect structured data, and resume interrupted runs.
Create or update a SOUL.md file that defines an AI partner’s behavior through a guided conversation. Clarify communication style, autonomy, honesty, and expectations, then review a concise English profile before saving it with setup_agent.
Turn a complex goal into an executable plan by checking each action’s requirements, expected results, and estimated effort. Tracks dependent tasks, verifies outcomes, and revises the remaining plan when conditions change or actions fail.
Build agent memory with ReasoningBank and AgentDB. Record actions and outcomes, retrieve similar experiences, assess results, and consolidate memories into reusable patterns so agents can draw on past work when making decisions.
Build agents that record task outcomes and use past experience to choose future approaches. Implement pattern matching, strategy comparisons, persistent learning records, and metrics for checking how recommendations and results change over time.
Plan experiments before collecting data. Helps choose study designs, randomly assign subjects or samples, organize treatment combinations, and generate reproducible schedules while checking for confounding and repeated measurements incorrectly counted as independent samples.
Build web interfaces that adapt to screen and component widths. Use CSS Grid, flexible text and spacing, and container queries, which respond to a component’s available space, to adjust layouts, images, navigation, and tables.
Set up Cisco Duo multi-factor authentication for VPN, RDP, SSH, and web applications. Configure access rules based on users and device health, introduce security keys, and establish authentication monitoring and emergency access procedures.
Build and improve Windows desktop apps with C#, WinUI 3, and the Windows App SDK. Guidance covers development setup, native interface design, implementation, troubleshooting, packaging choices, and verification through both builds and actual app launches.
Coordinate game audio work from creative direction through sound specifications, accessibility requirements, technical planning, and code integration. Combine the participating agents’ outputs into an audio design document for a chosen feature or area.