Video & Animation

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Evidence-informed marketing and founder-led sales decisions and execution. Use when the user needs to understand customers or markets; choose audiences, positioning, value, pricing, packaging or offers; diagnose weak or changing performance; create or critique marketing communication or brand identity; prioritize founder-led sales; plan or diagnose marketing channel execution across pages, email, social, paid media, search, or commerce; test, localize, or retain learning. Also use when symptoms imply these jobs, such as unclear differentiation, uncertain targeting, weak conversion, conflicting marketing signals, unclear commercial fit, or stalled buyer progress. Do not use for generic writing, mechanical content operations, product-roadmap, legal, finance/accounting, CRM administration, or unrelated technical work.

Record browser or Web UI interaction demos as optimized GIFs using the available browser-control workflow, optional Playwright Videos for higher capture frame rates, and deterministic encoding, then attach the GIF to a pull request with `gh --attach`, falling back to a dedicated assets branch where attach cannot apply. Use when asked to make, record, or generate a GIF that demonstrates a browser workflow, and for every pull request that changes product-user-visible GUI behavior, which MUST inclu

Fetch and display the full transcript from a Loom video URL. Use when the user wants to get or read a Loom transcript.

Use this skill whenever the user wants to create a finished video from a topic, title, idea, prompt, or script with MoneyPrinterTurbo. This includes short-form, voice-over, educational, marketing, social-media, and stock-footage videos. Also use it when the user mentions MoneyPrinterTurbo, provides this Skill URL, asks an AI agent to install or configure MoneyPrinterTurbo, needs missing API keys identified, wants a failed generation repaired, or wants a generated MP4 located and delivered. Use t

Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

Use when reproducing a UI bug or verifying a fix by driving a real VS Code window end to end and capturing evidence. Writes a scenario file, runs it against a dev build or installed Insiders, and produces a captioned video, per-step screenshots, a Playwright trace, and an HTML report to attach to an issue or pull request.

Plan and run multi-agent video production pipelines.

Secures container registry images (ECR, ACR, GCR, Docker Hub) by scanning with Trivy and Grype, signing with Cosign and Sigstore, configuring registry access controls, and building CI/CD pipelines that block unscanned or unsigned images. Use when establishing registry security controls or enforcing scan/signature checks before image promotion.

Turn vague "what did I do?" into evidence-backed impact statements for performance reviews, self-reviews, promotion packets, and weekly updates. Uniquely mines Copilot CLI session logs to reconstruct forgotten work, plus git commits and GitHub PRs. Enforces a 3-part impact contract (action → result → evidence). Works standalone with zero dependencies. Trigger for: "brag", "log work", "what did I do", "backfill my work history", "performance review", "self-review", "self assessment", "write impac

Run `@metaharness/darwin evolve <repo>` to mutate a harness's seven policy surfaces (planner/contextBuilder/reviewer/retryPolicy/toolPolicy/memoryPolicy/scorePolicy), sandbox-score each variant, and promote only measured wins. The model is frozen; the harness evolves. Closes the loop ADR-150 opens (score+genome describe; evolve changes). Degrades gracefully when @metaharness/darwin is absent (ADR-150 + ADR-153 architectural constraints).

Use when applies to CSS and JavaScript implementations of modals, overlays, pop-ups, cookie banners, newsletter sign-up dialogs, and promotional overlays. Check for `position: fixed`, `position: absolute` with large z-index, backdrop overlays, and JavaScript that shows modals on page load or shortly after. Consider both SEO impact (Google) and accessibility (WCAG focus management).

Use this plugin when the user wants a "Product Promo · 30s" HyperFrames motion video — Multi-scene 30-second product promo: problem-type intro, brand reveal, benefits flowchart, product surfaces, value pillars, foundation, CTA outro. Forked from Nate Herk's hyperframes-student-kit (linear-promo-30s); brand-specific copy + assets replaced with generic placeholders.

Audit README.md sections against the shortlist rules — re-verify every entry's verdict with live data, promote or demote challengers, restructure oversized use cases, prune, and evaluate proposed additions. Fire when the maintainer asks to audit, sweep, prune, re-check, or maintain sections, or asks whether an entry (or a proposed one) deserves its slot.

Run or recover OpenClaw macOS release signing, notarization, appcast, and asset promotion.

Use when recreating a real website

Use to refine already functional HyperFrames videos by improving fluidity, CTR, clicks, scrolls, transitions, overlaps, rhythm, and visual focus without rewriting the whole project.

Use to create a 9:16 commercial video in HyperFrames from a website or product page, with user journey, carousel, benefits, price, CTA, and final render.

Package an existing talking-head / interview / podcast video with timed, designed GRAPHIC OVERLAY cards — kinetic titles, lower-thirds, data callouts, quotes, side panels, picture-in-picture — synced to the transcript, on a 16:9 / 9:16 / 4:5 canvas of your choice; the clip plays untouched underneath. Trigger on

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Port an existing Remotion (React) composition

Gate fine-tuned checkpoints with drift budgets, paired comparison, and forgetting checks before promotion. Use after a training run produces a checkpoint, when deciding whether a tuned model ships, or when a promoted model needs re-gating against updated goldens.

Turn a GitHub pull request (a PR URL, owner/repo#N, or

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