「awe」の検索結果

Design normalized database schemas with tables, relationships, indexes, and constraints for any application domain. Use when the user requests database schema design or provides relevant inputs for this workflow.

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。

Place trusted contextual information into prompts or agent state using explicit boundaries, provenance, and templates. Use when relevant context has already been selected and must be inserted safely; use context-retrieval to find it or context-optimization to choose and order it.

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。

Classify, prioritize, and route incoming support tickets by extracting intent and entities, assigning severity, and generating initial responses. Use when the user requests ticket triage or provides relevant inputs for this workflow.

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。

Compress selected context to a target token budget while preserving decisions, evidence, constraints, and unresolved questions. Use when relevant material is already selected but too long; use context-optimization when selection, deduplication, and ordering are also required.

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。

Generate professional reports — sprint retrospectives, financial summaries, analytics dashboards, and incident postmortems — from structured data with templates, charts, and multi-format output. Use when the user requests report generation or provides relevant inputs for this workflow.

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。

Populate databases with realistic, reproducible test data for development, testing, and staging environments. Use when the user requests database seeding or provides relevant inputs for this workflow.

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。

Perform systematic exploratory data analysis to understand dataset structure, distributions, relationships, and anomalies before modeling. Use when a dataset is new, its quality is unknown, or the user requests open-ended profiling; use data-analysis instead for a defined hypothesis or decision question.

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。

Deploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.

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。

Set up and manage data labeling workflows using manual annotation tools, semi-automated pipelines, active learning, and programmatic weak supervision. Use when the user requests data labeling or provides relevant inputs for this workflow.

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。

Identify at-risk customer accounts by analyzing usage patterns, engagement signals, and support history to generate churn risk scores and intervention recommendations. Use when the user requests churn analysis or provides relevant inputs for this workflow.

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。

Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows. Use when deciding which agent actions require review, adding approve/reject or dual-control flows, preventing unauthorized autonomous effects, creating decision records, reducing rubber-stamping, or recovering safely from rejected, expired, or failed actions.

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。

Manage Git repositories and collaborative workflows — branching strategies, commit hygiene, conflict resolution, pull requests, hooks, and .gitignore management. Use when the user requests version control or provides relevant inputs for this workflow.

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。

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

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。

Think and work like an expert Herpetologist. Use when a task calls for Herpetologist judgment. Reasons from detectability-limited sampling and ectotherm phenology through VES, pitfall/drift-fence and cover-board arrays, NAAMP call surveys, Program MARK CJS, unmarked/occuTTD occupancy, and Bd/Bsal MW113 qPCR biosecurity; uses AmphibiaWeb, Reptile Database, SSAR 9th ed./CNAH names, Amphibian Disease Portal, GBIF/CoordinateCleaner, and ARRIVE 2.0 while treating weather bias, pitfall selectivity, and pathogen cross-contamination as first-class failure modes.

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。

All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps.

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。

Detect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter. Use when identifying bound TF sites within accessible regions, correcting Tn5 insertion bias before footprinting, choosing between cleavage-based and aggregate-based footprinters, or comparing differential TF activity between conditions.

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。

Computes and interprets treatment effect measures (OR, RR, RD, HR, NNT) with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen, MOVER, profile likelihood, Bender NNT) and reports marginal vs conditional estimands per FDA 2023 covariate adjustment guidance. Use when reporting treatment effects in confirmatory trials, comparing effect sizes across studies, or constructing forest plots.

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。

End-to-end DNA sequencing workflow from FASTQ files to variant calls. Covers QC, alignment with BWA, BAM processing, and variant calling with bcftools or GATK HaplotypeCaller. Use when calling variants from raw sequencing reads.

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。

End-to-end eDNA metabarcoding from raw amplicons to community ecology. Covers QC, primer removal, denoising with OBITools3 or DADA2, contamination filtering, taxonomy assignment, Hill number diversity, and constrained ordination. Use when processing environmental DNA samples for biodiversity assessment or ecological surveys.

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。

Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.

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。

Select restriction enzymes by criteria using Biopython Bio.Restriction. Find enzymes that cut once, don't cut, produce specific overhangs, are commercially available, or have compatible ends for cloning. Use when selecting restriction enzymes for cloning or analysis.

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。

Processes environmental DNA metabarcoding data from raw amplicon reads to species occurrence tables using OBITools3, DADA2, and taxonomic assignment against BOLD, MIDORI2, or MitoFish databases. Handles COI, 12S, rbcL, and ITS barcode regions with primer removal, denoising, chimera detection, and contamination filtering via decontam. Includes occupancy modeling (occumb) for detection probability correction. Use when analyzing eDNA from water, soil, or bulk samples for biodiversity monitoring. Not for 16S human microbiome (see microbiome/amplicon-processing).

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。

Predict B-cell and T-cell epitopes using BepiPred, IEDB tools, and structure-based methods for vaccine and antibody design. Identify immunogenic regions in antigens. Use when designing vaccines, mapping antibody binding sites, or predicting immunogenic peptides.

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。

Mark and remove PCR/optical duplicates using samtools fixmate and markdup. Use when preparing alignments for variant calling or when duplicate reads would bias analysis.

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。