223 skills found · Page 4 of 8
gooseworks-ai / render-apple-notes-chatAssemble an Apple Notes list video ad from a note + end-card JSON — a frame-accurate fake iPhone screen recording of a short list being typed into Apple Notes (character by character, key pops, blinking caret, the note scrolling up as it fills) crossfaded into a checklist end card (the note's picks…
gooseworks-ai / render-offer-adRender a punchy ~12s vertical (9:16) music-only direct-response OFFER ad as a 4-beat kinetic-typography film — HEADLINE slam → real PRODUCT drop → CLAIM/proof → CTA pill — from one config of copy slots, a real product photo, a brand palette, fonts, bpm, and beat split.
gooseworks-ai / render-imessage-chatRender a configurable iMessage conversation inside a properly framed phone, then a brand end card. Uses the original send/receive sounds and a shared frame timeline for text, typing, scrolling and sound.
gooseworks-ai / render-hypermotionAssemble the FREE steps of the product-hypermotion + kinetic-typography video format — dice ONE Seedance 2.0 hypermotion clip into 5-6 segments and intercut them with PIL kinetic-typography spec/CTA cards (italic skew, 1.08x outline echo, 3D extrusion, slam-with-shake, inversion flash) plus a real-l…
gooseworks-ai / render-logo-equation-cardRender the logo-equation card ad (7s, 9:16) — partner icon + brand icon joined by a plus sign as an equation, a two-line "= outcome" headline, four numbered steps, and a CTA that hard-cuts in at 2s, on a static black card over timelapse b-roll, no voice.
gooseworks-ai / render-absurdist-explainerAssemble an absurdist animated-explainer video ad (~38s, 9:16) from per-scene i2v clips + their measured VO windows — retime each clip to its VO, re-encode every segment to identical 30fps/libx264/yuv420p so the concat demuxer never drops frames, concat, build a REAL-product PIL end card (never AI)…
gooseworks-ai / render-flat-vector-explainerAssemble the FREE steps of the flat-vector-explainer video format — a flat-illustration host character (who, where, tone, voice and music come from the recipe choices) walks a countable N-step product routine, one step per beat, and Remotion composites every chip/numeral/tagline/slate/CTA as an anim…
gooseworks-ai / render-ig-live-galleryRender an 'Instagram-Live social-proof gallery' video from a config — ~5 real brand product stills each framed as an Instagram-LIVE card (IG gradient-ring avatar, username, verified check, red LIVE badge, viewer count, close X, a short claim-free live-comment feed, an empty 'Add a comment…' bar, and…
gooseworks-ai / render-mosaic-grid-revealRender a 'mosaic-grid-reveal' video from a config — a real-DOM FULL-BLEED N×N mosaic of real product tiles that pops in one tile at a time (scatter order, ease-out-back overshoot), the grid clears, then the brand wordmark builds line-by-line followed by a sub-label, tagline, and CTA; frame-stepped v…
gooseworks-ai / render-multiworldAssemble a silent, music-led 3-world product-tour ad — trim and hard-cut-concat the per-world WIDE-arrival + top-down-macro clips, composite the HTML/Playwright brand end card (approved headline + handwritten product labels + arrows) over an AI flat-lay background, and mux one music bed into a 720x1…
gooseworks-ai / render-cosmic-mythology-voiceoverAssemble a cosmic-mythology-voiceover reel from a config — one spoken voiceover carries the whole narrative while N curated stills in one chosen look are weighted beat-synced across the delivered VO duration (cut_dur = VO_dur times weight over the weight sum, so emotional beats hold longer), Ken-Bur…
huytieu / release-videoTurn a product release (the list of shipped items plus real screen recordings) into a motion recap video and one explained demo per feature, with sound effects tied to on-screen motion and a composed music bed.
BankrBot / coinheroList tokens on CoinHero via consignment deals on Base — deposit ERC-20 inventory, earn USDC when the protocol buys your token for CoinHero card games
BankrBot / gem-minerStake $GEM tokens on Gem Miner (gemminer.app) to earn yield and unlock the in-game earn/cashout system
BankrBot / rider-battleCreate and accept $RIDER wager battles in the Bankr CryptoRider game on Base, claim winnings or refunds, see open challenges, and view monthly & all-time leaderboards — all from a tweet
BankrBot / cattownInteract with Cat Town — a Farcaster-native game world on Base. Covers KIBBLE staking (stake, claim, unlock, unstake, leaderboard, deposit history); live world state (season, weather, time of day, weekend flag); fishing drops filtered by world state; Isabella's weekend fishing competition with live…
brycewang-stanford / aamas-artifact-evaluationUse when packaging AAMAS multiagent code, environments, opponent and population sets, random seeds, game definitions, and logs as anonymous supplementary evidence or a public post-acceptance release, even without a separate artifact badge, so that game-theory and MARL reviewers can inspect and re-ru…
brycewang-stanford / aamas-author-responseUse when drafting an AAMAS rebuttal to preliminary OpenReview reviews, covering the double-blind constraint, the no-new-results and no-revised-paper norms, how to answer game-theory, MARL, and systems reviewers at once, and how to give the area chair a clean acceptance rationale within a short respo…
brycewang-stanford / aamas-experimentsUse when designing or auditing AAMAS experiments - self-play and population-based training, opponent selection, equilibrium and regret metrics, game-theoretic simulations, ablations, seeds, hyperparameters, compute, and claim-to-evidence fit - with emphasis on experiments that probe the interaction…
brycewang-stanford / aamas-reproducibilityUse when strengthening AAMAS reproducibility evidence for interaction claims, including proofs and game definitions, opponent and population sets, self-play protocols, random seeds, compute, uncertainty on strategic outcomes, baselines, and consistency between what the paper claims about agents and…
brycewang-stanford / aamas-review-processUse when explaining or planning around AAMAS peer review, covering OpenReview review release, the double-blind rebuttal on preliminary reviews, area-chair discussion, the mixed game-theory, MARL, and systems reviewer pool, the public posting of reviews and decisions, and how acceptance criteria weig…
dpearson2699 / ios-accessibilityBuild and audit SwiftUI, UIKit, and AppKit accessibility for VoiceOver, Voice Control, Switch Control, Full Keyboard Access, Dynamic Type, focus restoration, labels/traits/actions, traversal, custom rotors, NSAccessibility, XCTest checks, adaptive system preferences, and App Store accessibility decl…
dpearson2699 / weatherkitFetch WeatherKit current, minute, hourly, and daily forecasts; weather alerts; iOS 18+ changes, historical comparisons, summaries, and statistics; and required Apple Weather attribution
dpearson2699 / shareplay-activitiesBuild shared real-time experiences using GroupActivities and SharePlay
dpearson2699 / tabletopkitBuilds multiplayer spatial board games using TabletopKit on visionOS
gamedev-skills / audio-designImplement game audio practice — bus/mixer architecture and gain in decibels, ducking (sidechain), adaptive/dynamic music via layering and re-sequencing, SFX variation, and beat synchronization. Engine-neutral
gamedev-skills / camera-systemsBuild game cameras that feel good — 2D follow with a deadzone, look-ahead, smoothing, and level-bounds clamping; 3D third-person orbit with collision and first-person look; plus multi-target framing and a shake hook.
gamedev-skills / game-aiDesign NPC and enemy decision-making with finite state machines, behavior trees, steering behaviors, and A* pathfinding — engine-neutral algorithms that pair with the detected engine's navigation API
gamedev-skills / game-feelAdd "juice" and game feel that makes actions satisfying — screen shake, hit-stop/freeze frames, tweened/eased motion, squash & stretch, knockback, and layered audio-visual feedback — as engine-neutral techniques that pair with the detected engine's tween, particle, and camera APIs
gamedev-skills / performance-optimizationFind and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets.
