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Found 4,160 Skills
Use as the fallback for custom HyperFrames HTML video composition authoring when no specialized workflow fits. Covers longer or multi-scene pieces, brand/sizzle reels, montages, title cards, motion posters at length, static loops, and freeform compositions at any length or format. Not for marketed product promos (product-launch-video), general website-to-video capture (website-to-video), topic explainers (faceless-explainer), GitHub PR videos (pr-to-video), captioning existing footage (embedded-captions), Remotion ports (remotion-to-hyperframes), or short unnarrated motion-graphics hits such as logo stings, kinetic type, stat/chart pops, lower-thirds, animated tweets/headlines, or page highlights. If a specialized workflow clearly fits the input, prefer it (see /hyperframes-read-first); use this only as the input/length-agnostic fallback.
Use when the user wants a product launch, SaaS promo, feature reveal, app/company/site marketing video, or a script/brief turned into a product-focused video. Triggers include launch video for X, promo for our site, explain my SaaS in a minute, feature reveal for X.com, and turn this script into a 60s promo. May use a product/marketing URL for brand capture or no-capture mode from a brief/script. Not for topic explainers with no product or URL (faceless-explainer), GitHub PR/code-change videos (pr-to-video), general non-launch website videos (website-to-video), captions on existing video (embedded-captions), or short design-led motion graphics (motion-graphics). When product-vs-topic or launch-vs-general-site is unclear, do not assume — start at /hyperframes-read-first.
Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human
Use the Orca CLI to orchestrate worktrees and live terminals through a running Orca editor. Use when an agent needs to create, inspect, update, or remove Orca worktrees; inspect repo state known to Orca; or read, send to, wait on, or stop Orca-managed terminals. Triggers include "use orca cli", "manage Orca worktrees", "read Orca terminal", "reply to Claude Code in Orca", "create a worktree in Orca", or any task where the agent should operate through Orca instead of talking to git worktrees and terminal processes directly.
Capture a general website/URL and turn it into a HyperFrames video (site tour, showcase, or social clip from the site's own visuals). Uses headless Chrome screenshots + brand assets. Use when intent is general — portfolio/blog/landing-page showcase or social clip from the site. NOT for: product/SaaS launch or promo (→ /product-launch-video, even from a URL); topic explainer with no site (→ /faceless-explainer); GitHub PR (→ /pr-to-video); adding captions to existing video (→ /embedded-captions); short unnarrated page-highlight motion graphic (→ /motion-graphics). Unclear launch-vs-general-site? Ask one question or start at /hyperframes-read-first.
When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see page-cro.
Provides a comprehensive guide for writing production-ready Golang tests. Covers table-driven tests, test suites with testify, mocks, unit tests, integration tests, benchmarks, code coverage, parallel tests, fuzzing, fixtures, goroutine leak detection with goleak, snapshot testing, memory leaks, CI with GitHub Actions, and idiomatic naming conventions. Use this whenever writing tests, asking about testing patterns or setting up CI for Go projects. Essential for ANY test-related conversation in Go.
Functional programming helpers for Golang using samber/lo — 500+ type-safe generic functions for slices, maps, channels, strings, math, tuples, and concurrency (Map, Filter, Reduce, GroupBy, Chunk, Flatten, Find, Uniq, etc.). Core immutable package (lo), concurrent variants (lo/parallel aka lop), in-place mutations (lo/mutable aka lom), lazy iterators (lo/it aka loi for Go 1.23+), and experimental SIMD (lo/exp/simd). Apply when using or adopting samber/lo, when the codebase imports github.com/samber/lo, or when implementing functional-style data transformations in Go. Not for streaming pipelines (→ See golang-samber-ro skill).
Implements dependency injection in Golang using samber/do. Apply this skill when working with dependency injection, setting up service containers, managing service lifecycles, or when you see code using github.com/samber/do/v2. Also use when refactoring manual dependency injection, implementing health checks, graceful shutdown, or organizing services into scopes/modules.
Structured logging extensions for Golang using samber/slog-**** packages — multi-handler pipelines (slog-multi), log sampling (slog-sampling), attribute formatting (slog-formatter), HTTP middleware (slog-fiber, slog-gin, slog-chi, slog-echo), and backend routing (slog-datadog, slog-sentry, slog-loki, slog-syslog, slog-logstash, slog-graylog...). Apply when using or adopting slog, or when the codebase already imports any github.com/samber/slog-* package.
Structured error handling in Golang with samber/oops — error builders, stack traces, error codes, error context, error wrapping, error attributes, user-facing vs developer messages, panic recovery, and logger integration. Apply when using or adopting samber/oops, or when the codebase already imports github.com/samber/oops.
Create comprehensive, standardized documentation for object-oriented components following industry best practices and architectural documentation standards.