「agent-skills」の検索結果

Extract design tokens, text styles, and variables from a Figma design system and produce a design-tokens.json plus ready-to-use QML singletons. Use this skill whenever someone wants to pull their design system out of Figma — whether they say "export tokens from Figma", "get design tokens", "set up my design system", "read our Figma design system", "get Figma variables into QML", "pull our color palette from Figma", "import design tokens", "extract colors/typography/spacing from Figma", or similar. Trigger this skill at the start of any design-system workflow that involves a Figma source.

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Use to generate or update Qt 6 CMake projects or edit CMakeLists.txt, add sources/resources or define targets (executable, QML module, library).

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Generates standalone Markdown reference documentation for QML components and applications. Use this skill whenever you want to document QML files, create API reference docs for a QML component or module, document a Qt Quick application, or produce developer-facing documentation from .qml source code. Triggers on: "document this QML", "write docs for my QML", "create reference docs", "document QML component", "QML API docs", "document my Qt Quick component", "document my Qt app", or any time one or more .qml files are provided and documentation is needed. Works with single files, pasted code, or entire project folders. DO NOT use if the user asks for QDoc format output.

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Use when the user is investigating QML / Qt Quick performance — both vague complaints ("the UI feels laggy", "this is slow", "frames are dropping", "the app stutters") and explicit asks to profile, find hotspots, or optimize bindings, signals, or rendering. Runs qmlprofiler on a 2D QML application, parses the .qtd trace, and analyzes hotspots against the source with frame-time, memory, and pixmap-cache summaries. Does NOT cover Qt Quick 3D.

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Generates standalone Markdown reference documentation for any Qt/C++ source files — Qt Widgets classes, Qt Quick backends, Qt/C++ modules, plain C++ utilities, structs, free-function headers, and entry points like main.cpp. Use this skill to document any .h or .cpp file: Qt classes, plain C++ code, utility helpers, or application startup files. Triggers on: "document this class", "write docs for my C++", "document main.cpp", "C++ API docs", "document my Qt app", or whenever C++ or header files are provided and documentation is needed. Works with single files, pasted code, or entire project folders. DO NOT use if the user asks for QDoc format output.

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Design or audit UI for Qt/QML, Qt projects, web, or embedded MPU or MCU targets. Use when creating screens, layouts, navigation, or auditing UX.

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Structured code review through the shared OpenClaw agent-skills installation.

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GATK Best Practices for germline SNP/indel calling from WGS/WES BAMs. Per-sample HaplotypeCaller GVCFs, GenomicsDBImport, GenotypeGVCFs joint calling, VQSR or hard filters. Requires BWA-MEM2-aligned, markdup, BQSR BAMs. Use DeepVariant for a faster DL alternative; GATK is the NIH/ENCODE standard.

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Interactive visualization with Plotly. 40+ chart types (scatter, line, heatmap, 3D, geographic) with hover, zoom, pan. Two APIs: Plotly Express (DataFrame) and Graph Objects (fine control). For static publication figures use matplotlib; for statistical grammar use seaborn.

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Opentrons Protocol API v2 for OT-2/Flex: Python protocols for pipetting, serial dilutions, PCR, plate replication; control thermocycler, heater-shaker, magnetic, temperature modules. Use pylabrobot for multi-vendor.

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Statistical visualization on matplotlib + pandas. Distributions (histplot, kdeplot, violin, box), relational (scatter, line), categorical, regression, correlation heatmaps. Auto aggregation/CIs. Use plotly for interactive; matplotlib for low-level.

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Guide to quality filtering raw VCF files before computing summary stats (Ts/Tv ratio, variant counts, AF distributions). Covers detecting raw VCFs via FILTER column and QUAL inspection, QUAL-based filtering with bcftools, Ts/Tv interpretation, and when NOT to filter. Read before any variant-level QC task. See bcftools-variant-manipulation for advanced filters, gatk-variant-calling for caller config, samtools-bam-processing for upstream alignment QC.

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Best practices for single-cell RNA-seq cell type annotation including marker-based, reference-based, and automated classification approaches.

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Annotate and filter VCF variants with SnpEff and SnpSift. SnpEff predicts functional effects (HIGH/MODERATE/LOW/MODIFIER), genes, transcripts, AA changes, HGVS; SnpSift filters and adds ClinVar/dbSNP. Java CLI with Python subprocess integration. Use ANNOVAR for multi-database annotation; Ensembl VEP for REST API; SnpEff for fast CLI with pre-built genomes.

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GWAS and population genetics tool. Processes PLINK (.bed/.bim/.fam), VCF, and BGEN; runs QC (MAF, HWE, missingness), IBD estimation, PCA, and linear/logistic regression GWAS. Outputs Manhattan-ready summary stats. Use regenie or SAIGE for biobanks (>100k samples) needing mixed models.

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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.

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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.

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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.

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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.

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Detect somatic CNVs from WES/WGS/targeted BAMs (CNVkit v0.9.x). Bin coverage in target/antitarget regions, normalize vs reference, segment with CBS/HMM, call amps/dels, scatter/diagram plots, purity/ploidy, VCF/SEG export. CLI plus Python API (cnvlib). Use GATK CNV for deep WGS with population controls; use CNVkit for targeted/exome where antitarget bins matter.

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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.

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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.

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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.

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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.

日本語の概要は準備中です。原文の説明を表示しています。