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Found 555 Skills
Run a full Flows app platform review against a React/TypeScript CDF codebase, following the cognitedata/dune-app-reviews scoring criteria. Produces three artifacts: review-files.md (per-file inventory), review-packages.md (dependency audit), and review-report.md (scored report with must/should/nice-fix items). Use when the user asks for a Flows app review, pre-submit review, approval review, app certification review, code quality audit, CDF platform review, or "run dune-review" on a codebase before submission.
Bronze/Silver/Gold layer design patterns and templates for building scalable data lakehouse architectures. Includes incremental processing, data quality checks, and optimization strategies.
Run holistic pedagogical review on lecture slides. Checks narrative arc, student prerequisites, worked examples, notation clarity, and deck pacing.
Guides users through AI video production on the Seedance platform — from creative ideation and asset preparation through storyboarding to production-ready prompts. Triggers on keywords such as Seedance, AI video, storyboard, camera movement, video extension, one-shot take.
Use when implementing data persistence in iOS apps with SwiftData or CoreData, encountering migration errors, performance issues with fetches, or choosing between persistence frameworks
Run a full Dune app platform review against a React/TypeScript CDF codebase, following the cognitedata/dune-app-reviews scoring criteria. Produces three artifacts: review-files.md (per-file inventory), review-packages.md (dependency audit), and review-report.md (scored report with must/should/nice-fix items). Use when the user asks for a Dune app review, pre-submit review, approval review, app certification review, code quality audit, CDF platform review, or "run dune-review" on a codebase before submission.
Enhance text storyboards into Seedance 2.0 video prompts one by one. Call this when the text storyboard is completed and needs to be converted into executable video prompts.
Profile a new tabular dataset before modeling. Find target leakage, missing data patterns, high-cardinality categoricals, near-constant features, redundant pairs, and non-linear relationships that Pearson correlation misses. Use whenever the user hands you a CSV or parquet and asks "what should I do with this?" Always run this skill before training any model on data you haven't seen before.
Conduct Exploratory Data Analysis (EDA) using descriptive statistics, visualizations, and data quality checks. Use this skill when the user has a dataset and needs to understand its structure, find patterns, detect anomalies, or prepare data for further analysis — even if they say 'what does this data look like', 'find interesting patterns', 'clean this data', or 'summarize this dataset'.
Generate cinematic film-style video prompts for Seedance 2.0 (Higgsfield). Use this skill when users want AI videos with cinematic, film-like, movie-quality, Hollywood-style, dramatic, or professional film-quality. Trigger words: cinematic, film-like, movie scene, dramatic lighting, depth of field, lens flare, anamorphic, letterbox, film noir, epic, stabilized camera, dolly shot, crane shot, or any cinematic video generation request. Use this skill even if users don't explicitly say "cinematic" but describe film aesthetics.
Vendor-neutral skill to audit application logs for potential sensitive-data leakage and redaction coverage.
Generate videos using ByteDance's Seedance model. It supports text-to-video and image-to-video functions, and calls APIs through the volcengine-ark SDK. This skill is activated when users need to generate videos, create video content, or produce videos based on text or images.