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Found 1,291 Skills
MSW `.map` / `.ui` / `.gamelogic` / `.model` 에셋과 `world.yaml` 을 버전 고정된 `@choigawoon/msw-vfs-cli`(npx) 로 읽고·탐색·편집·변환하는 스킬. '맵 구조 확인', '맵 엔티티 목록', 'UI 계층', 'HP바/텍스트 조사', 'entity 값 수정', '컴포넌트 추가/삭제', '.model 값 편집', 'YAML export/import', 'world 빌드', '.map/.ui/.gamelogic/.model 파일 분석' 요청 시 사용. L1(경로 기반 VFS) + L2(entity 단위) + .model + YAML/World 모두 지원.
Terminal-first JTBD engine for founders and product people. Interview fast, kill jargon, capture real switching forces (Push/Pull/Habit/Anxiety), score opportunities, and export structured artifacts (JSON + one-pager + messaging angles + GTM brief). Use when the user says "help me figure out what to build", "analyze these customer reviews", "what are people actually hiring this for", "I need messaging for my product", "turn this interview into insights", "what should I prioritize", or any variation of articulating what a project does, why it matters, who it's for, or converting interview/review/transcript signal into a decision-grade brief. Also triggers on "describe my project", "JTBD", "jobs to be done", "switching forces", or "mine these reviews".
This skill should be used when analyzing Wispr Flow voice dictation history for self-reflection, work patterns, mental health insights, or productivity analytics AND when managing the Wispr Flow dictionary (adding terms, fixing mishears, exporting/importing, suggesting improvements). Triggered by requests like "/wispr-analytics", "analyze my dictations", "what did I dictate today", "wispr reflection", "add to wispr dictionary", "improve dictation", "wispr suggest", "export wispr dictionary", or any request to review voice dictation patterns or manage dictation quality.
Convert normalized timed transcript data into subtitle artifacts such as SRT and VTT. Use this when a stable normalized transcript JSON already exists and the main job is subtitle chunking, timing normalization, and export packaging.
Add strict Nature/CNS citations to manuscript text by splitting long passages into citable segments, searching only accepted flagship and subjournal titles from Nature Portfolio, the AAAS Science family, and Cell Press, filtering by publication time range, and exporting one reference-manager-ready output by default. Use this skill whenever the user asks to input text and automatically get references, add citations to a paragraph/manuscript, find Nature-series or CNS support for statements, create text-to-reference correspondence, "分段引用", "自动给出引用", "Nature系列引用", "CNS及子刊", "支撑文献", "补引用", "找引用", or export EndNote/RIS/ENW/Zotero RDF.
Stellar Assets (classic) + trustlines + Stellar Asset Contract (SAC) bridge to Soroban. Covers asset issuance, distribution, authorization flags, clawback, regulated assets, trustline management, and the SAC interop layer that exposes classic assets as Soroban tokens. Use when tokenizing real-world assets, issuing stablecoins, managing trustlines, or bridging classic assets to Soroban contracts.
Complete guide to implementing the Syncfusion QueryBuilder component in ASP.NET Core applications. Use this when working with visual query/filter builders, rule-based filtering UI, SQL/JSON/MongoDB query generation, drag-and-drop rule reordering, or import/export of filter conditions using Syncfusion EJ2 TagHelpers.
Author/validate/export Google's DESIGN.md token spec files.
Activate when reviewing or modifying dependency resolution, lockfile schema, package downloaders, signature/integrity checks, file integration cleanup, or anything that could expose APM to dependency confusion, typosquatting, malicious packages, or token leakage.
Stereo depth estimation using FoundationStereo. Predicts disparity maps from stereo image pairs for 3D reconstruction. Use when training, evaluating, exporting, or running inference for a TAO FoundationStereo model. Trigger phrases include "train stereo depth", "FoundationStereo", "stereo disparity estimation", "3D reconstruction from stereo".
Real-time stereo depth estimation using FastFoundationStereo (FFS), the distilled bp2 commercial variant of FoundationStereo. Predicts disparity maps from stereo image pairs with ~10× lower latency than full FoundationStereo. Use when training, evaluating, exporting, or running inference for a TAO FastFoundationStereo (FFS) model. Trigger phrases include "train fast stereo", "real-time stereo disparity", "FastFoundationStereo", "distilled stereo depth".
Sparse4D for multi-camera temporal 3D object detection and tracking. Uses sparse queries with deformable attention across camera views and time for end-to-end 3D perception, with an instance bank for temporal tracking. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Sparse4D model. Trigger phrases include "train Sparse4D", "multi-camera 3D detection", "temporal 3D tracker", "sparse query 3D perception".