124건 · 관련도순
Use when cutting a release, writing a CHANGELOG entry, or summarizing what changed since a tag — when the repo's commits follow (or mostly follow) Conventional Commits and a mechanically-accurate section breakdown beats a model's reading of the diff.
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Manage an engagement buffer that ingests, prioritizes, rate-limits, deduplicates, and tracks state for incoming engagement items across platforms. Generates periodic digests and enforces cooldown periods. Composes with du-dum: du-dum sets the observation/action cadence, this skill manages the queue between beats.
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Monitor, cap, and recover from context accumulation in agentic systems. Covers per-cycle cost tracking, context window auditing, budget caps with enforcement policies, emergency pruning when approaching limits, and progressive disclosure integration to minimize token spend on routing. Use when running long-lived agent loops (heartbeats, polling, autonomous workflows), when context windows are growing unpredictably between cycles, when API costs spike beyond expected baselines, when designing new agentic workflows that need cost guardrails from the start, or when post-mortem analysis reveals a cost incident caused by context accumulation.
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Stock Screener — pre-built screens (growth, value, momentum, dividend, earnings beats) plus custom natural language criteria. Returns top 10-20 matches ranked by Screen Fit Score (0-100). Triggered by "trade screen growth/value/momentum/dividend/earnings" or "trade screen custom <criteria>".
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Produce a complete narrated MYTHIC SHORT FILM end-to-end on Unsora MCP in the layered cut-paper diorama style — stacked matte cardstock worlds, a strict three-colour palette, exposure that swings, paper wipes hiding every seam, landing on a face. Animation-movie storytelling, not an explainer: gods, monsters, heroes, folklore, origin myths and transformations, told in ten-second story beats with a mythic narrator, native paper foley, and one assembled MP4. Use whenever the user wants a myth, legend, fable, folktale or fairy-tale short, a cut-paper or papercraft animated story, "tell the story of X" as a video, a stop-motion-look mythic film, or says "run the cardstock diorama myth animation" or "run the diorama myth pipeline" — even with no story given, since the skill proposes myths itself. NOT for fact-driven explainers with charts and statistics (that is vox-motion-graphics).
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Turn any still image into a professional motion graphic through the Novoads API on Seedance 2.5. Covers how to read a reference image, motion vocabulary for any image type — UI, marketing hero, flat-lay, key art, collage, product, character — the prompt clauses that control camera, timing, frozen regions and text fidelity, and the upload mechanics. Use whenever the user supplies an image and wants it animated, moving, or turned into video — including "animate this", "turn this into a motion graphic", "make this move", "この画像動かして", "モーショングラフィックにして", "I want the cards to pop in", "I want the bars to slide up", or when they describe motion beats for a static image. Also use when asked to write a Seedance prompt for an existing image. Do NOT use for text-to-video with no source image, restyling existing footage (this skill takes no video input), cloning a reference video (use clone-video-ad), or a product photo that should seed a new scene rather than move as-is (use novoads-api).
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Builds a hand-sculpted stop-motion CLAY ad on the Novoads REST API as a STORYBOARD: five to eight beats, each rendered from its own key frame, a storyteller narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's arc (named protagonist, inciting moment, social beat, quiet despair, sculpted clay infographic, discovery, transformation, resolution card), and also recreates a found clay ad by reading the reference video locally with ffmpeg and Whisper. Use for ANY clay or stop-motion ask at ANY length: "claymation ad", "stop-motion ad", "clay ad", "a quick clay ad", "plasticine characters", "make an ad like this clay one", or a reference video with sculpted clay characters in it. There is no one-call tier here, so ffmpeg is required. Not for the smooth 3D animated look (use pixar-ad, which covers every Pixar-style length), talking-head UGC (novoads-api), or a static image ad.
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Builds a stylized 3D animated ad on the Novoads REST API as a STORYBOARD: four to six beats, each rendered from its own key frame, narration laid into the gaps, a music bed, captions burned on, assembled locally with ffmpeg. Carries the genre's beat formulas (anthropomorphized problem character, protagonist reveal, mascot mechanism scene, composited end card). Use for ANY Pixar-style, Disney-style, 3D animated or animated-film-look ad at ANY length: "Pixar style ad", "3D animated ad", "animated movie look", "cute 3D character ad", "a quick animated ad", "15 second animated ad", "30 second animated ad", "storyboard ad", "several scenes", "animated ad with a voice-over", "little mascots", or a product URL or photo for an emotional animated spot. No one-call tier, so ffmpeg is required. Not for stop-motion clay (use claymation-ad), talking-head UGC (novoads-api), video cloning, or static image ads.
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Generate AI music using ACE-Step 1.5 via ACE Music's free API. Use when the user asks to create, generate, or compose music, songs, beats, instrumentals, or audio tracks. Supports lyrics, style prompts, covers, and repainting. Free API, no cost.
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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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Call germline SNPs and indels with GATK HaplotypeCaller and the GVCF joint-genotyping workflow. Covers the local-reassembly + PairHMM mechanism (why HC beats pileup callers on indels), the -ERC GVCF reference-confidence model and <NON_REF> allele, BQSR-vs-DRAGSTR and --dragen-mode error modeling, allele-specific (AS_) annotations, and edge cases (ploidy, Mutect2 mitochondria mode, sex chromosomes/PAR, contamination gating). Use when deciding whether to use HaplotypeCaller vs a pileup or DRAGEN caller, whether BQSR still earns its place, whether to call per-sample GVCFs for a cohort, or how to handle non-diploid, mitochondrial, sex-chromosome, or contaminated samples. Not for post-calling filtering depth (see variant-calling/filtering-best-practices) or cohort joint-genotyping scaling (see variant-calling/joint-calling).
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Use when sequencing a launch — alpha / beta / GA waves, audience-by-wave logic, narrative beats per wave, engineering-readiness gates. Triggers on 'plan the launch', 'sequence GA'.
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Paseo reference for managing projects, workspaces, workspace scripts, agents, schedules, and heartbeats.
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Use the HyperFrames CLI development loop: init, add, catalog, capture, lint, check, snapshot, compare, grade-compare, preview, play, present, beats, keyframes, single or batch render, publish, cloud, cloudrun, feedback, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, auth, tts, and remove-background. Also use when diagnosing build or render failures. validate, inspect, and layout are deprecated aliases; use check. Covers local, HeyGen-hosted cloud, AWS Lambda, and Google Cloud Run rendering.
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Audit recent agent work for recurring manual patterns that have no skill yet, cross-check against installed skills and public skill catalogs (installing beats building), and propose the top two or three as before/after. Read-only analysis. Triggers: "/skill-gap", "what skills should I build", "audit my skills".
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Keep serialized build-in-public content continuous: read one canon file of season, arcs, beats and loops and say which narrative beat to advance next, so episodes chain into a series. Pairs with the episode adapter, which does the writing. Triggers: "/reality-show", "season state", "what arcs are open".
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Build a music-led video sequence by planning beats, creating or accepting an audio track, animating ordered visuals, and assembling a reviewable draft.
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Farm the stills and b-roll the beats need. Use at the assets stage, or when the user says "farm the assets", "find the images", or "get the b-roll".
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Animation storyboard: production-level frame states and scroll-beats production spec. Use when implementing, reviewing or testing animation storyboard for React, Vite, Next.js or Perfect_AI projects.
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Predict peptide-MHC class I binding and natural presentation with MHCflurry, NetMHCpan-4.1, and MixMHCpred to nominate candidate CD8 T-cell epitopes. Covers the binding-affinity (BA) vs eluted-ligand (EL/presentation) distinction, why %Rank beats raw nM for cross-allele work, the MS abundance bias that misranks low-expression neoantigens, allele-coverage inequity, and length bias. Use when scanning a protein or peptide set for class I epitopes, scoring neoantigen candidates, or choosing a binding predictor. For CD4/HLA class II see mhc-class-ii-prediction.
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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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Detect distant homologs using profile and structure-aware methods that go beyond standard BLAST. Use when sequence identity falls into the twilight zone (<35% pairwise), when BLAST fails to find homologs that should exist, when working at metagenomic scale (DIAMOND, MMseqs2), or when structure beats sequence (Foldseek). Covers PSI-BLAST (iterative PSSM), jackhmmer (iterative HMM), HHblits/HHsearch (profile-profile), DIAMOND, MMseqs2, and Foldseek (3Di structural alphabet, van Kempen 2024).
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Predict peptide-MHC class I binding and natural presentation with MHCflurry, NetMHCpan-4.1, and MixMHCpred to nominate candidate CD8 T-cell epitopes. Covers the binding-affinity (BA) vs eluted-ligand (EL/presentation) distinction, why %Rank beats raw nM for cross-allele work, the MS abundance bias that misranks low-expression neoantigens, allele-coverage inequity, and length bias. Use when scanning a protein or peptide set for class I epitopes, scoring neoantigen candidates, or choosing a binding predictor. For CD4/HLA class II see mhc-class-ii-prediction.
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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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