「alignment」の検索結果

Verify GDD, UX, Architecture, and Epics alignment before production. Use when the user says "check readiness" or "implementation readiness"

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Build product roadmaps with quarterly planning, feature prioritization, dependency mapping, and stakeholder alignment. Create actionable roadmaps that communicate strategy and guide execution.

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ACTIVATE when drafting all-hands speeches, investor updates, quarterly letters to stakeholders, press statements, CEO announcements, crisis communications, customer updates, or any mission-critical communication to employees, investors, customers, or media. Executive communications require persuasion, clarity, emotional intelligence, and alignment with company values and strategy.

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。

Final quality pass before shipping. Fixes alignment, spacing, consistency, and detail issues that separate good from great.

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。

当需要为 AI 系统设计多层安全防线、内容过滤策略和伦理边界时调用此 skill。典型场景包括：设计拒绝策略与升级机制、防御 prompt 注入攻击、实现领域特定安全规则（教育、医疗、金融等）、定义 AI 的价值观锚点。 不适用于：定义工具操作权限（应使用 tool-specification）、定义 AI 身份（persona-design）、调整输出风格（personality-system）。 关键 trigger 信号：AI 涉及敏感话题、需要设计"拒绝回答"策略、存在 prompt 注入风险、特定行业合规要求、需要多层防御而非单一规则。

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Think and work like an expert Molecular Geneticist. Use when a task calls for Molecular Geneticist judgment. Reasons from sequence-as-hypothesis, reference context (genome build, MANE/RefSeq transcript, HGVS), and allele-level molecular consequence through ACMG/AMP-ClinGen criteria, IGV/VEP/SpliceAI/gnomAD/ClinVar review, MIQE-compliant qPCR/ddPCR, and Sanger/NGS validation while treating allele dropout, pseudogene/paralog misalignment, FFPE deamination, contamination and barcode bleed, and transcript/build mismatch 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。

Think and work like an expert Electronic Materials Engineer. Use when a task calls for Electronic Materials Engineer judgment. Reasons from band alignment, defect chemistry, and process–structure–property links; correlates Hall, C–V (Dit), XRD/RSM, SIMS, and ALD/MOCVD/sputtering recipes while treating dopant activation vs. chemical dose, high-κ trap charging, and reliability (NBTI/TDDB) 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。

Think and work like an expert Computational Neuroscientist. Use when a task calls for Computational Neuroscientist judgment. Reasons from encoding/decoding, GLM/LNP spike-train likelihood, mean-field E-I balance, and neural manifolds through NEST/Brian/NEURON/BMTK, GPFA/LFADS, Brain-Score alignment, and trained-RNN reverse engineering while treating spike-sorting contamination, model non-identifiability, nested-CV leakage, and task-optimization≠mechanism as first-class failure modes.

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Think and work like an expert Crop Protection Scientist. Use when a task calls for Crop Protection Scientist judgment. Reasons from IPM, EIL/ET, and FRAC/HRAC/IRAC MoA rotation through GEP/EPPO efficacy trials, CDMS label law, BBCH timing, DRT application, PPDB/fate modeling, and MRL/GAP alignment while treating resistance, drift, herbicide carryover, and abiotic mimicry 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。

Think and work like an expert Automotive Engineer. Use when a task calls for Automotive Engineer judgment. Reasons from vehicle-level requirements, regulatory limits, energy/exergy budgets, and distribution-based durability through DFMEA/DVP&R, DoE calibration (INCA, CANape, HIL), Pacejka tire and multibody models, rainflow fatigue, and source-path NVH analysis while treating undocumented build-level and cal-ID deltas, unmet emissions preconditioning and OBD readiness, ADAS sensor misalignment, and cross-domain torque-arbitration conflicts as first-class failure modes.

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Operate AudioShake's cloud source-separation service (developer.audioshake.ai) to split a recording into stems. Use when a task involves isolating vocals, drums, bass, guitar, piano, keys, strings, or winds from music; separating dialogue / music / effects (DME) for film-TV post-production, localization, and dubbing; splitting a mixed recording into one stem per speaker; lyric transcription or word-level alignment; music detection/identification; or speech denoise/dereverb. Covers the Tasks API job lifecycle (assets, targets, formats, polling vs webhooks, credits, limits), choosing which stem targets a production actually needs, reviewing separated stems for bleed / artifacts / transient smearing / phase problems and repairing them, the rights and consent questions raised by separating copyrighted or third-party recordings, and the decision boundary for when a local open model such as Demucs is the better route than the API. Not for generating or synthesizing new audio, mixing, or mastering.

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Provider-independent performance direction for generated video, avatar/spokesperson clips, animation, ads, film scenes, social content, and voice-led media. Use when an agent must cast or direct synthetic performers, avatars, animated characters, talking heads, AI video characters, or voice performances; plan acting beats, objective/obstacle/action, blocking, gesture, eye-line, facial expression, body language, lip-sync, voice alignment, rehearsal prompts, iteration, continuity, consent, and performance QA.

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。

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。

Compute evolutionary distances and build phylogenetic trees using Biopython Bio.Phylo.TreeConstruction. Use when creating distance matrices from alignments, building NJ/UPGMA trees, generating bootstrap consensus, or needing quick exploratory phylogenies before running full ML 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。

Preprocessing and harmonization of multi-omics data before integration. Covers normalization, batch correction, feature alignment, and missing value handling across data types. Use when preparing multi-omics datasets for integration analysis.

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Process Hi-C read pairs using pairtools. Parse alignments, filter duplicates, classify pairs, and generate contact statistics from Hi-C sequencing data. Use when processing raw Hi-C read pairs.

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Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.

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。

Project gene annotations across genomes using TOGA (Kirilenko 2023 whole-genome-alignment chain-based projection with intactness classification), CESAR 2.0 (Sharma & Hiller 2017 codon-aware exon projection), LiftOff (Shumate & Salzberg 2020 reference-based annotation transfer), Liftover (UCSC), GeMoMa (Keilwagen 2019 evidence-based projection), and Comparative Annotation Toolkit (CAT). Use when transferring annotations from a well-annotated reference to query genome(s), classifying gene-loss vs gene-intact across many genomes at scale, building Zoonomia-style comparative annotations across hundreds of mammals or birds (Kirilenko 2023), detecting pseudogenization, projecting alternative isoforms, or selecting between WGA-anchored (TOGA) vs ortholog-based (LiftOff) annotation transfer strategies.

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。

Preprocess CLIP-seq reads (eCLIP, iCLIP, iCLIP2, iCLIP3, irCLIP, PAR-CLIP, FLASH) with protocol-specific UMI extraction, adapter trimming, length filtering, and post-alignment PCR-duplicate collapse. Use when raw CLIP FASTQ must be turned into deduplicated, crosslink-preserving BAM input for peak calling; choosing between two-pass and single-pass adapter trimming; deciding minimum read length; or mapping UMI patterns to specific eCLIP/iCLIP/iCLIP2/iCLIP3 library preps.

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Preprocesses cell-free DNA sequencing data including adapter trimming, alignment optimized for short fragments, and UMI-aware duplicate removal using fgbio. Applies cfDNA-specific quality thresholds and fragment length filtering. Use when processing plasma cfDNA sequencing data before downstream analysis.

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Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. Use when calling germline variants from ONT or PacBio alignments, particularly when high accuracy is needed for clinical or research applications.

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Generates standardized quality control reports by aggregating metrics from FastQC, alignment, and other tools using MultiQC. Use when summarizing QC metrics across samples, creating shareable quality reports, or building automated QC pipelines.

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Convert raw Nanopore signal data (FAST5/POD5) to nucleotide sequences using Dorado basecaller. Covers model selection, GPU acceleration, modified base detection, and quality filtering. Use when processing raw Nanopore data before alignment. Note: Guppy is deprecated; use Dorado for all new analyses.

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。