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Found 83 Skills
Interactive prompt studio for HappyHorse 1.0 video generation. Guides users through scenario discovery with vivid examples, then assembles production-ready prompts in JP/CN/EN. Use when someone wants to create AI video content with HappyHorse but doesn't know where to start, or when they have a specific scenario and need a polished prompt. Covers manga drama, character PV, manga motion, virtual idol MV, and free-form scenarios.
Build an Expo React Native Android APK on GitHub Actions without EAS. Use when the user wants to build an APK/AAB from CI, set up a GitHub Actions workflow for expo prebuild + gradle assembleRelease, fix Android build failures in CI (Kotlin metadata mismatch, play-services-ads version conflicts, RNGMA/patch-package), download the APK artifact, or asks why the Android build fails with "incompatible version of Kotlin". Covers APK (release-signed via keystore, or debug-signed for quick tests) vs AAB (Play Store) choices and native dependency pinning. For signing/verify specifics (Play Console debug-mode rejections, apksigner vs jarsigner) see the android-release-signing skill.
Forced Analogy / Structural Transplant — map the problem onto a structurally similar system from a distant domain (immune system, air-traffic control, restaurant kitchen, jazz ensemble) and transfer its mechanisms back. Use when a solution works but feels derivative, when the industry playbook is exhausted, or when a system in nature or another trade already solves this shape of problem. Triggers include "analogy", "forced analogy", "how would a hospital/kitchen/airport handle this", "transplant from another industry", "structurally similar system". Do NOT use for analytical work like debugging, code review, or implementation tasks.
Writing, exploit — assemble raw material into a journey of beats, grounding each term before a beat leans on it.
Use when the user asks to "build a story bank", "collect our origin and customer stories", or "assemble reusable proof stories for the message"; assembles reusable narrative units — origin, founder, customer, transformation, and proof stories — each tagged to a claims-ledger ID and a message-house pillar, with every proof labeled Measured / User-provided / [needs source]. Not for authoring the message house or pillars — use message-system-architect; not for brand voice or naming rules — use brand-language-codifier; not for finished long-form prose — use content-writer; not for adjudicating whether a proof is true — use offer-claims-registry. 品牌故事库/起源客户转化/证据故事单元
Approach board for a problem or a decision. Dispatches independent seats — some generating candidate approaches, including one agent outside this process entirely, some attacking the assembled set comparatively — then verifies the surviving objections and reports a ranked recommendation with its trade-offs. An approach already on the table enters as one candidate among several. Autonomous; changes nothing.
Ingest tabular Parquet files into Rerun chunk streams with rerun.experimental.ParquetReader. Read when converting trajectory or sensor tables (LeRobot-style parquet, exported logs) into entities and components — column grouping, timeline/index columns, static columns, and lenses (DeriveLens) that assemble the typed components (Transform3D, Scalars) from the reader's grouped struct/scalar output. Builds on rerun-chunk-processing and rerun-data-model.
Build a premium, scroll-driven interactive landing page for any business: a service company, a physical product, a food brand, a drink brand. Scroll becomes the timeline. Video scrubs frame by frame under the wheel, sections pin and advance, rails pan sideways, headlines assemble line by line, the page ground shifts colour as you travel, and the pointer moves things that are not scrolling. Interviews the human first (their vibe, their journey, one unbroken world or distinct scenes, and what assets they already own), then picks a page grammar and a signature move so no two builds share a skeleton, generates photoreal assets through kie.ai or builds from the user's own footage and photos, writes real semantic HTML on a design-system floor, and verifies the result by screenshotting its own scroll. Use for "scrollytelling", "scroll animation site", "a site where scrolling plays a video", "Apple-style landing page", "3D scroll world", "interactive landing page", "make my brand a scroll experience", "make it feel different", "this looks like a template", "a unique scroll site", or any request for a site that should feel like an experience rather than a document.
End-of-session adversarial review loop. Assemble the session's work into a role-assigned, self-contained brief, then run independent reviewers in parallel — an isolated code-reader (the idea-validator agent) that reads the ACTUAL files and web-checks technology currency, plus an external-family model if you have one — synthesize where they agree vs diverge, apply the cheap-safe fixes immediately, record a measurable plan for the rest, and CHALLENGE reviewer claims you disagree with (never blind-accept). Use at the close of a substantive coding or design session, when the user says "session review", "review my session", "stress-test this session", or types /session-review. Skip for trivial one-off edits.
When you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's "work backwards from availability, not from a name you fell in love with" methodology. Uses Vercel CLI + whois + Domainr API + Namecheap API + agent-browser for the pieces each tool actually reliably supports (multi-tool ensemble because no single tool covers everything cleanly). 11-step workflow: budget → brainstorm → primary availability check → whois cross-check → Domainr aggregation → Namecheap price → aftermarket sweep (+ liveness probe for parked/dead domains, drop-watch for expiring ones) → bucket → negotiate → NAME research (trademark + socials) → buy. Triggers on "/domain," "find a domain," "check domain availability," "brainstorm a domain," "what .com is available for X," "domain hunt," "name my project," "is X.com available," "aftermarket price on X.com," "trademark check for X."
Score, grade, or evaluate things using AI against a rubric. Use when grading essays, scoring code reviews, rating candidate responses, auditing support quality, evaluating compliance, building a quality rubric, running QA checks against criteria, assessing performance, rating content quality, or any task where you need numeric scores with justifications — not just categories.