Claude Code Skills · page 131

Python library for single-particle tracking (SPT) in video microscopy via the Crocker-Grier algorithm. Locate particles (fluorescent spots, colloids, vesicles, cells) per frame, link into trajectories, filter short tracks, and compute MSD for diffusion analysis. 2D/3D with subpixel accuracy; reads TIF stacks, AVI, image series via pims. Use for quantitative SPT and diffusion coefficient extraction from fluorescence or brightfield video.

Low-level Python plotting for scientific figures: publication-quality line, scatter, bar, heatmap, contour, 3D; multi-panel layouts; fine control of every element. PNG/PDF/SVG export. Use seaborn for quick stats, plotly for interactive.

Interactive scientific visualization with Plotly. Two APIs: plotly.express (px) for one-liner DataFrame plots, plotly.graph_objects (go) for trace-level control. 40+ chart types with hover, zoom, pan, animation. Exports HTML or static PNG/SVG/PDF via kaleido. Use for volcano plots with gene hover, dose-response dashboards, expression heatmaps, 3D molecular views. Use seaborn for stats; matplotlib for publication figures.

Guide for choosing and creating scientific visualizations for publications and talks. Covers chart-type selection by data structure, color theory for accessibility/print, figure composition, journal formatting (Nature, Cell, ACS), and common pitfalls. Consult when visualizing data or preparing submission figures.

Statistical visualization on matplotlib with native pandas support. Auto aggregation, CIs, grouping for distributions (histplot, kdeplot), categorical (boxplot, violinplot), relational (scatterplot, lineplot), regression (regplot, lmplot), matrix (heatmap, clustermap), grids (pairplot, FacetGrid). Use for quick statistical summaries; matplotlib for fine control; plotly for interactive HTML.

Guide for annotating statistical significance (p-value asterisks) on comparison plots. Covers standard notation (ns, *, **, ***, ****), matplotlib bracket+asterisk implementation, and use with seaborn box/violin/bar plots. Use when preparing publication-ready figures with significance markers.

Fast short-read DNA aligner for WGS/WES/ChIP-seq. 2× faster BWA-MEM successor; outputs SAM/BAM with read group headers for GATK. Primary plus supplementary records for chimeric reads. Use STAR for RNA-seq splice-aware alignment; Bowtie2 is a comparable alternative.

Read/write SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ. Region queries, pileup, variant filtering, read groups. Python htslib wrapper exposing samtools/bcftools CLI. Use STAR/BWA for alignment; GATK/DeepVariant for variant calling.

CLI toolkit for SAM/BAM/CRAM: sort, index, convert, filter, QC alignments. Core commands: view, sort, index, flagstat, stats, depth, markdup, merge. Required between alignment and variant/peak calling. Use pysam for Python-native BAM access; deeptools for normalized coverage tracks.

Splice-aware RNA-seq aligner producing sorted BAM and splice junction tables. Builds genome index, runs two-pass alignment for better junctions. Outputs sorted BAM, junctions (SJ.out.tab), stats (Log.final.out), optional gene counts. Use Salmon for fast pseudoalignment; STAR when a BAM is needed for variant calling, IGV, or ENCODE pipelines.

Annotate bacterial and archaeal genomes and plasmids with Bakta's Prodigal/HMM/diamond pipeline. Identifies CDS, ncRNA, tRNA, rRNA, tmRNA, sORFs, CRISPR arrays, oriC/oriV/oriT, and gaps against a curated UniRef-derived database. Produces NCBI-compatible GFF3, GenBank, EMBL, JSON, FASTA, TSV, and a circular genome plot. Use Prokka for legacy pipelines or non-bacterial kingdoms; PGAP for NCBI GenBank submission.

Annotate prokaryotic genomes (bacteria, archaea, viruses) via Prokka's BLAST/HMM pipeline. Identifies CDS, rRNA, tRNA, tmRNA, signal peptides against Pfam, TIGRFAMs, RefSeq. Outputs GFF3, GenBank, FASTA, TSV. Use PGAP for NCBI GenBank submission; Bakta for faster NCBI-compatible annotation.

Compute the bacterial pan-genome from Prokka/Bakta GFF3 annotations with Roary's CD-HIT + BLAST + MCL clustering pipeline. Builds gene presence/absence matrices, core/soft-core/shell/cloud partitions, multi-FASTA core gene alignments (with `-e`), and a pan-genome reference. Use Panaroo for higher-accuracy pan-genomes from highly fragmented assemblies, PIRATE for paralog-aware clustering, or PPanGGOLiN for graph-based partitioning.

GRN inference from expression via GRNBoost2 (gradient boosting) or GENIE3 (Random Forest). Load matrix, filter by TFs, infer TF-target-importance links, save network. Dask-parallelized to single-cell scale. Core SCENIC component.

Molecular biology toolkit: sequence manipulation, FASTA/GenBank/PDB I/O, NCBI Entrez, BLAST automation, pairwise/MSA alignment, Bio.PDB, phylogenetic trees. Use for batch processing, custom pipelines, format conversion, PubMed/GenBank queries. For quick gene lookups use gget; for multi-service REST APIs use bioservices.

Biopython sequence analysis: parse FASTA/FASTQ/GenBank/GFF (SeqIO), NCBI Entrez (esearch/efetch/elink), remote/local BLAST, pairwise/MSA alignment (PairwiseAligner, MUSCLE/ClustalW), phylogenetic trees (Phylo). Use for gene family studies, phylogenomics, comparative genomics, NCBI pipelines. For PCR/restriction/cloning use biopython-molecular-biology; for SAM/BAM use pysam.

Query ARCHS4 REST API for uniformly processed RNA-seq expression, tissue patterns, co-expression across 1M+ human/mouse samples. Retrieve z-scores, co-expressed genes, samples by metadata, HDF5 matrices. For variant population genetics use gnomad-database; for pathway enrichment use gget-genomic-databases (Enrichr).

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Cancer genomics (TCGA et al.) via cBioPortal REST API. Retrieve somatic mutations, CNAs, expression, clinical data (survival/stage/treatment) across thousands of studies. Use for TMB, oncoprints, survival analysis. For population frequencies use gnomad-database; for drug-gene interactions use opentargets-database.

Query the ClinPGx (formerly PharmGKB) REST API plus the CPIC PostgREST companion API for pharmacogenomic clinical annotations, CPIC/DPWG dosing guidelines, gene-drug pairs, variant-drug associations, FDA/EMA drug labels, and PGx pathways. Two-host architecture: api.clinpgx.org for annotation records, api.cpicpgx.org for genotype→recommendation lookups. No auth. For germline pathogenicity use clinvar-database; for somatic cancer PGx use cosmic-database or opentargets-database; for drug bioactivity use chembl-database-bioactivity.

Query NCBI ClinVar via E-utilities for variant clinical significance, pathogenicity, disease associations. Search by gene/rsID/condition/review status; returns ClinSig, submitter data, conditions, HGVS. For GWAS use gwas-database; for variant consequence prediction use Ensembl VEP.

Query COSMIC for cancer somatic mutations, gene census, mutational signatures, drug resistance variants. REST API v3.1 supports gene/sample/variant queries; free registration. For germline use clinvar-database; for drug-target data use opentargets-database or chembl-database-bioactivity.

Query NCBI dbSNP for SNP records by rsID, gene, or region via E-utilities and Variation Services REST API. Retrieve alleles, MAF, variant class (SNV/indel/MNV), clinical links, cross-DB IDs (ClinVar, dbVar, 1000G). Free; 3 req/sec (10 with key). For clinical pathogenicity use clinvar-database; for population frequencies use gnomad-database.

DepMap CRISPR gene effect (Chronos) analysis: sign convention for essentiality, per-gene NaN-safe Spearman correlation, data loading/alignment. For general NaN-safe correlation see nan-safe-correlation; for quality filtering see degenerate-input-filtering.

ENA REST API for sequences, reads, assemblies, and annotations. Portal API search, Browser API retrieval (XML/FASTA/EMBL), file reports for FASTQ/BAM URLs, taxonomy, cross-refs. For multi-DB Python use bioservices; for NCBI-only use pubmed-database or Biopython Entrez.

ENCODE Portal REST API for regulatory genomics: TF ChIP-seq, ATAC-seq/DNase-seq peaks, histone marks, and RNA-seq across 1000+ cell types. Search experiments by assay/biosample/target; download BED/bigWig; retrieve SCREEN cCREs by region or gene. Use to annotate variants with regulatory tracks, find open chromatin in a cell type, or fetch peak files for ChIP/ATAC analysis. For regulatory variant scoring use regulomedb-database; for GWAS associations use gwas-database.

Ensembl REST API for gene/transcript/variant annotations in 300+ species. Gene info by symbol/ID, sequence, cross-refs (HGNC, RefSeq, UniProt), regulatory features. For bulk local use pyensembl; for pathways use kegg-database.

NCBI Gene via E-utilities: curated records across 1M+ taxa. Official symbols, aliases, RefSeq IDs, summaries, coordinates, GO, interactions. Use for gene ID resolution and cross-species function queries. For sequences use Ensembl; for expression use geo-database.

NCBI GEO access via GEOparse and E-utilities. Search by keyword/organism/platform, download GSE series matrices, parse GPL annotations, extract GSM metadata, load expression matrices into pandas. For single-cell use cellxgene-census; for multi-DB access use gget-genomic-databases.

Unified CLI/Python interface to 20+ genomic databases. Gene lookups (Ensembl search/info/seq), BLAST/BLAT, AlphaFold, Enrichr enrichment, OpenTargets disease/drug, CELLxGENE single-cell, cBioPortal/COSMIC cancer, ARCHS4 expression. Spans genomics, proteomics, disease. For batch/advanced BLAST use biopython; for multi-DB Python SDK use bioservices.

gnomAD v4 population variant frequencies via GraphQL API. Allele counts and frequencies stratified by ancestry (AFR, AMR, EAS, NFE, SAS, FIN, ASJ, MID), gene-level constraint (pLI, LOEUF, missense z), and coverage. Identify rare or constrained variants. For clinical pathogenicity use clinvar-database; for GWAS use gwas-database.

NHGRI-EBI GWAS Catalog REST API for SNP-trait associations from published GWAS. Query studies, associations, variants, traits, genes, summary stats. Build PRS candidates, analyze pleiotropy, fetch stats for Manhattan plots. No auth.

JASPAR 2024 TF binding profiles via REST API and pyJASPAR. Retrieve PFMs/PWMs by TF name, JASPAR ID, species, or structural class. Scan DNA for TFBS; browse by taxon (human, mouse) or TF family (bHLH, zinc finger). Use for motif enrichment input, TFBS scanning, and regulatory sequence analysis. For ChIP-seq peak motif discovery use homer-motif-analysis; for regulatory variant scoring use regulomedb-database.

KEGG REST API (academic only). Pathways, genes, compounds, enzymes, diseases, drugs via 7 ops (info/list/find/get/conv/link/ddi). ID conversion (NCBI/UniProt/PubChem). Use bioservices for multi-DB Python.

Monarch Initiative knowledge graph REST API for disease-gene-phenotype associations and cross-species orthology. MONDO disease-to-gene/phenotype, HP phenotype profiles, cross-species comparisons. Use for rare disease gene prioritization and phenotype-based candidate ranking. For GWAS use gwas-database; for clinical pathogenicity use clinvar-database.

Retrieve mouse phenotype data from the Jackson Laboratory Mouse Phenome Database (MPD) via its REST API. Browse 520+ projects, look up per-project measure metadata, pull strain-level means (raw or LS-mean adjusted) and per-animal values, find measures by MP/VT ontology terms, and resolve strain nomenclature or gene coordinates. Use for QTL support, cross-strain comparison, mouse model selection, and ontology-driven phenotype discovery. Use monarch-database for disease-gene-phenotype knowledge graphs; ensembl-database for mouse genome annotations.

Query EBI QuickGO REST API for GO terms and protein annotations. Fetch term metadata by ID, search by keyword, walk ancestor/descendant hierarchies, download annotations filtered by taxon, evidence code, aspect. Use for GO resolution, ontology traversal, annotation retrieval before enrichment. Use gseapy-gene-enrichment for enrichment; uniprot-protein-database for proteins.

Query RegulomeDB v2 GET REST API to score variants for regulatory function and retrieve overlapping evidence (TF binding, histone marks, DNase peaks, footprints, motifs, eQTLs, chromatin state). Scores range 1a (strongest) to 7 (none). Use for GWAS hit prioritization, regulatory variant annotation, cis-regulatory discovery. Use clinvar-database for pathogenicity; gwas-database for trait associations.

Query ReMap 2022 TF ChIP-seq peak database via REST API and BED downloads. Retrieve TF peaks overlapping a region (chr:start-end), peaks near a gene, TFs by species, peaks filtered by biotype (promoter, enhancer), and BED files for a TF-cell type pair. Use for TF co-occupancy, regulatory annotation, and TF binding atlases. Use jaspar-database for PWM motifs; encode-database for ENCODE tracks.

Query UCSC Genome Browser REST API for DNA sequences, tracks, gene models, and conservation across 100+ assemblies. Retrieve sequence by region, list/fetch BED/bigWig tracks, chromosome sizes, RefSeq/GENCODE gene structures, PhyloP/PhastCons scores. Use for UCSC annotations; Ensembl REST API for Ensembl gene IDs and VEP variant annotation.

ETE Toolkit (ETE3): Python phylogenetic tree analysis and visualization. Parse Newick/NHX/PhyloXML, traverse/annotate nodes, render figures with TreeStyle/NodeStyle, integrate NCBI taxonomy, run PhyloTree comparative genomics. Use for species trees, gene family evolution, annotated tree figures.

De novo and known TF motif enrichment in ChIP-seq/ATAC-seq peaks via HOMER. findMotifsGenome.pl finds over-represented patterns vs background; annotatePeaks.pl assigns context (TSS distance, gene, repeat). Use after MACS3 to identify enriched TFs, annotate peaks with nearest genes, and validate ChIP-seq via the target motif.

Genomic interval ops on BED/BAM/GFF/VCF. Find overlaps, merge intervals, compute coverage, extract FASTA, find nearest features. Core for ChIP-seq peak annotation, region filtering, genome arithmetic. Use tabix for indexed single-region queries; use deeptools for normalized bigWig coverage.

NGS CLI for ChIP/RNA/ATAC-seq. BAM→bigWig with RPGC/CPM/RPKM, sample correlation/PCA, heatmaps/profiles around features, fingerprints. For alignment use STAR/BWA; for peak calling use MACS2.

Python library for genomic interval ML. Train/apply region2vec embeddings turning BED regions into vectors, index interval datasets for ML, search embedding space with BEDSpace, and evaluate embedding quality. Use for chromatin accessibility clustering, regulatory element classification, and cross-sample region comparison.

Rust-backed Python library for fast genomic token arithmetic and BED processing. High-performance BED I/O, interval set ops (intersect, merge, complement, subtract), region tokenization against a universe, universe construction. Use for preprocessing large BED collections and ML token vocabularies.

Poisson-model peak caller for ChIP-seq/ATAC-seq BAMs. MACS3 callpeak finds enriched regions (TF sites or histone marks) vs input/IgG; outputs BED narrowPeak/broadPeak for motif analysis, annotation, and differential binding. Use narrow peaks for TF ChIP-seq and ATAC-seq; broad for H3K27me3, H3K9me3, and other broad marks.

Guide to interpreting BUSCO completeness statuses: why Duplicated BUSCOs count as complete, parsing output files, computing/comparing completeness across proteomes/genomes, common counting mistakes. Use when running BUSCO QC, comparing assemblies, or reporting completeness. See also: prokka-genome-annotation for annotation workflows feeding BUSCO.

All-in-one FASTQ QC and adapter trimming. Auto-detects Illumina adapters, filters low-quality reads, corrects paired-end overlaps, emits HTML+JSON QC in one pass. 3-10x faster than Trim Galore/Trimmomatic. First step before STAR, BWA-MEM2, or Salmon.

Aggregates QC from 150+ bioinformatics tools into one interactive HTML report. Scans FastQC, samtools, STAR, HISAT2, Trim Galore, featureCounts, Kallisto, Salmon, Picard, GATK logs; merges per-sample stats with plots. For NGS pipeline-wide QC. Use FastQC directly for single-sample; MultiQC for multi-sample reporting.

Bulk RNA-seq DE with R/Bioconductor DESeq2. Negative binomial GLM, empirical Bayes shrinkage, Wald/LRT tests, multi-factor designs, Salmon tximeta import, apeglm LFC shrinkage, MA/volcano/heatmap viz. R gold standard. Use pydeseq2-differential-expression for Python; use edgeR for TMM normalization.

Counts RNA-seq reads overlapping GTF gene features. Takes sorted STAR BAMs plus GTF; outputs a per-gene tab-delimited matrix across samples. Handles strandedness (0/1/2), paired-end, multi-sample batch counting in one command, and outputs assignment statistics. Use Salmon for alignment-free quantification; use featureCounts when STAR BAMs already exist.

GSEA and over-representation analysis (ORA) for RNA-seq and proteomics. Wraps Enrichr for ORA against MSigDB, KEGG, GO, and 200+ databases; runs preranked GSEA on ranked DE gene lists. Outputs enrichment tables and running-score plots. Use after DESeq2 or edgeR for pathway-level interpretation.

Bulk RNA-seq DE with PyDESeq2: load counts, normalize, fit negative binomial models, Wald test (BH-FDR), LFC shrinkage, volcano/MA plots. Use for two-group comparisons, multi-factor designs with batch correction, multiple contrasts.

Ultra-fast RNA-seq transcript/gene quantification via quasi-mapping (no BAM). Builds a k-mer index from transcriptome FASTA, quantifies in minutes. Outputs TPM/count tables (quant.sf) with optional GC- and sequence-bias correction. Integrates with tximeta/tximport for DESeq2/edgeR. Use STAR when a genome-aligned BAM is needed.

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Annotated matrices for single-cell genomics. Stores X with obs/var metadata, layers, embeddings (obsm/varm), graphs (obsp/varp), uns. Use for .h5ad/.zarr I/O, concatenation, scverse integration. For analysis use scanpy; for probabilistic models use scvi-tools.

Automated scRNA-seq cell type annotation via pre-trained logistic regression. 45+ models: immune, gut, lung, brain, fetal, cancer microenvironments. Input normalized AnnData; outputs per-cell labels, majority-vote cluster labels, confidence scores. Use for fast, reference-backed annotation without manual marker inspection.

Query CELLxGENE Census (61M+ cells). Search by cell type/tissue/disease/organism; get AnnData, stream out-of-core, train PyTorch models. For your own data use scanpy; for annotated data use anndata.

Harmony batch correction for scRNA-seq and other omics. Removes batch effects from PCA embeddings while preserving biology. Run after PCA, before UMAP. Scales to millions of cells. Python (harmonypy, scanpy) and R (Seurat).

Consensus cell type annotation: runs 10+ algorithms (KNN-Harmony/BBKNN/Scanorama/scVI, CellTypist, ONCLASS, Random Forest, SCANVI, SVM, XGBoost) on a labeled reference and transfers labels via majority voting. Outputs per-method labels, consensus, agreement score. Use when single-method annotation is insufficient or you need ensemble uncertainty for novel states.

scRNA-seq with Scanpy: QC, normalization, HVG selection, PCA, neighborhood graph, UMAP/t-SNE, Leiden clustering, markers, cell annotation, trajectory inference. Standard scRNA-seq exploration.

Deep generative models for single-cell omics: probabilistic batch correction (scVI), semi-supervised annotation (scANVI), CITE-seq RNA+protein (totalVI), transfer learning (scARCHES), and DE with uncertainty. Unified setup→train→extract API on AnnData. Use harmony-batch-correction for fast linear correction without deep learning; muon for multi-modal MuData workflows.

Decision framework for manual marker-based, automated (CellTypist), and reference-based (popV) cell type annotation in scRNA-seq. Three-tier strategy: Tier 1 manual markers, Tier 2 CellTypist, Tier 3 popV ensemble transfer. Use when planning or troubleshooting annotation.

CLI for VCF/BCF: filter, merge, annotate, query, normalize, compute stats. Core post-variant-calling: quality filtering, multi-sample merging, rsID annotation, genotype extraction. Samtools companion in HTSlib. Use GATK for complex indel realignment during calling; use VCFtools for population genetics stats.

SST v4 (Ion) expert for managing AWS resources as code with the Pulumi-backed framework. Use when writing or editing sst.config.ts, building infra/ modules (sst.aws.Function/Bucket/Dynamo/Cron/Service/Router, sst.Secret, sst.Linkable, raw aws.* Pulumi resources), wiring resource links, scoping IAM, or running sst deploy/dev/diff/remove. Essential when the user mentions SST, sst.config.ts, $config, $transform, $interpolate, sst.aws.*, sst.Secret, Pulumi/Ion, "sst deploy", a failed SST deploy (ConflictException on a resource-type change, "Identifier '__filename' has already been declared", MalformedPolicyDocument on an Output<T>), or wants to scaffold/troubleshoot AWS infrastructure with SST. Also use when a request to "deploy my AWS stack" or "add a Lambda/bucket/table" is made in a repo that already contains an sst.config.ts (using $config) or an sst dependency. Do NOT use when the task is primarily AWS CDK, Terraform, raw CloudFormation, or SAM with no SST present — those have their own tooling.

把旅行行程做成美观、离线可读、手机优先的单文件 HTML（交互地图+每日时间轴+出发前订票提醒）。两种用法——只给目的地和天数让它帮你规划，或丢一份现成计划让它直接出页面。触发：旅行计划可视化、做旅行攻略网页、行程 HTML、travel plan visualization。

3Dmol.js WebGL molecular visualization emitted as self-contained HTML. Render structures (PDB/SDF/XYZ/MOL2/cube) with stick, sphere, cartoon, line, and surface styles; animate trajectories with a frame-delay (interval, ms) control; and animate vibrational normal modes via vibrate() from per-atom dx/dy/dz displacements or from precomputed frames. Output standalone HTML that loads 3Dmol from a CDN, with optional play/pause and speed controls. Use for transition-state imaginary-mode animations, MD or reaction-path playback, docking poses, and orbital/density isosurfaces. For static 2D chemical structure drawings use rdkit-chemdraw-cdxml; for 2D statistical plots use matplotlib or plotly.

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让 OS 在用户离开期间自主推进任务。支持三个子命令：start（启动）、stop（停止）、status（状态查询）。

启动持续工作模式——Leader自动循环领取和执行任务

组织多 Agent 会议全生命周期——创建会议、spawn 真实参与者、推进轮次、签到校验、结束汇总。当需要多方协作做决策、评审方案、辩论分歧、复盘项目、头脑风暴或方案评估时使用本技能。

Participate in AI Team OS meetings with structured discussion rounds

Auto-register as a team member when joining an AI Team OS project

在 AI Team OS 项目里使用 CC 内置 Workflow（ultracode）时，让工作流产出回写 OS 的标准做法。当 Leader 准备调用 Workflow 工具编排子 agent 时使用。

发布 AI Team OS 新版本的完整清单——预检、版本七处锁步、中英双语 CHANGELOG、双份 dist 构建、私有术语扫描、commit/tag、双仓推送、建 GitHub Release 条目并核对 latest 徽章、事后核对。当准备发版、补建漏掉的 Release 条目、或核对已发版本的线上状态时使用。

Battle-tested Playwright patterns for writing, debugging, and scaling reliable test suites. Use when you need guidance for E2E, API, component, visual, accessibility, or security testing, plus CI/CD, CLI automation, page objects, and migration from Cypress or Selenium. TypeScript and JavaScript.

Production-ready CI/CD configurations for Playwright — GitHub Actions, GitLab CI, CircleCI, Azure DevOps, Jenkins, Docker, parallel sharding, reporting, code coverage, and global setup/teardown.

Battle-tested Playwright patterns for writing and debugging reliable E2E, API, component, visual, accessibility, and security tests. Use when you need locator strategy, assertions, fixtures, network mocking, auth flows, trace debugging, or framework recipes for React, Next.js, Vue, and Angular. TypeScript and JavaScript.

Step-by-step migration guides for moving to Playwright from Cypress or Selenium/WebDriver — command mappings, architecture changes, and incremental adoption strategies.

Automates browser interactions for testing and validating your own web applications using playwright-cli. Use when you need terminal-first browser control for navigation, form filling, screenshots, tracing, bound browser sessions, debugging, or generating Playwright test code. Only use against applications you own or have explicit authorization to test.

Page Object Model patterns for Playwright — when to use POM, how to structure page objects, and when fixtures or helpers are a better fit.

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Use when reviewing code for security vulnerabilities, implementing authentication/authorization, handling user input, or discussing web application security. Covers OWASP Top 10:2025, ASVS 5.0, LLM Top 10 (2025), and Agentic AI security (2026).

Generate scroll-stopping viral hook video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants viral content, TikTok hooks, Instagram Reels openers, YouTube Shorts, attention-grabbing video, scroll-stopper, pattern interrupt, or any short-form video designed to maximize retention and views. Triggers on any mention of viral, hook, scroll-stop, retention, views, engagement, short-form, TikTok, Reels, Shorts.

Generate SaaS product launch and software demo video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants a product launch video, app demo, software walkthrough, feature showcase, startup promo, tech product reveal, or any SaaS/software marketing video. Triggers on SaaS, app, software, product launch, demo, feature, startup, tech, UI, dashboard, landing page video.

Generate personal brand and founder story video prompts for Seedance 2.0 on Higgsfield. Use for authority content, day-in-the-life, founder story, personal brand building, thought leadership, creator content, lifestyle videos, behind-the-scenes, or any video meant to build a personal brand presence. Triggers on personal brand, founder, creator, authority, lifestyle, behind the scenes, day in the life, thought leader.