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概要と使いどころ
人类图 (Human Design) 全盘解读技能。根据出生日期、准确时间和出生地点生成 BodyGraph，并以用户语言综合解读类型、策略、权威、人生角色、身体、天赋、财富、关系与使命；支持基于真实盘面的连续问答。触发词: 人类图, Human Design, BodyGraph, 人类图排盘, 人类图解读, 天赋, 使命, 职业, 关系, 类型, 策略, 权威, 人生角色, 通道, 闸门.
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。
Establish, author, restructure, or audit human-first processor Architecture, Design, Research, Review, and Verification documentation. Use for progressive documentation scaffolding, authority maps, reading paths, document-type content contracts, length-budgeted splitting, or maintainability reviews. Do not use as a substitute for cycle-accurate microarchitecture analysis or RTL implementation.
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。
Safely localize unknown Unity games, especially Japanese-to-Chinese projects. Use to discover Unity version/layout/backend, migrate translations across game versions, extract occurrence-mapped text from serialized assets, embedded CSV, bytecode, UI, Localization StringTables, Utage, or middleware, bridge rows through AiNiee-style translation, validate and transactionally write approved candidates, audit residual and runtime-only text or AutoTranslator diffs, diagnose TMP fonts and Addressables/IL2CPP failures, locate saves, or acceptance-test SHA-verified patches.
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。
Use when wrangler deploys silently fail or produce wrong artifacts, secrets upload as empty strings, custom domain DNS is not resolving, route assignment broke after rename, observability/tail logs are needed, D1/KV/R2 bindings are missing, OAuth scope errors block a command, cookies on a redirect are not attaching, or the worker exceeds CPU time. Triggers: "Tenant or user not found", "Authentication error" on wrangler d1 push, secret length is 0 after upload, route returns origin not worker, "compatibility_date too old", 1101 errors, custom_domain assignment lost on script rename. NOT for AWS Lambda / Vercel Edge / Deno Deploy (different runtimes), Cloudflare Zero Trust, or R2-specific tuning.
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。
Quality control for flow, spectral, and mass cytometry - time-based anomaly cleaning (flowAI, flowCut, PeacoQC, flowClean), margin/boundary event removal, signal-drift detection, dead-cell exclusion, CyTOF Gaussian/DNA/event-length checks, instrument calibration/standardization (MESF, CS&T, peak-2), and batch-level outlier flagging. Use when assessing acquisition quality, choosing a cleaning tool, ordering QC relative to compensation, deciding margin removal before density-based steps, or flagging problematic samples before clustering or differential 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。
Detects and removes doublets/aggregates from flow, spectral, and mass cytometry before clustering or quantification. Covers FSC-A vs FSC-H singlet discrimination (the Area-Height non-proportionality, not a 1D area gate), FSC-W/SSC width gating, CyTOF Gaussian discrimination parameters (Center/Offset/Width/Residual/Event_length) and DNA intercalator gating, and the residual heterotypic conjugates that survive scatter gating and masquerade as double-positive populations. Use when filtering aggregates before phenotyping, choosing a doublet method for flow vs CyTOF, or diagnosing a suspicious double-positive cluster.
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。
Assesses the quality and completeness of a genome annotation with BUSCO (conserved single-copy ortholog recovery), OMArk (proteome completeness, consistency, and contamination), CheckM2 (prokaryotic completeness/contamination), and a gene-set sanity panel (gene count, mono-exonic fraction, protein-length distribution, mRNA:gene ratio, coding density). Covers the assembly-BUSCO-vs-proteome-BUSCO diagnostic, what BUSCO-Duplicated really means, why gene count is a vanity metric, and the QC of transferred annotations. Use when judging whether an annotation is good enough to publish or submit, diagnosing a suspect annotation, or comparing annotation completeness across pipelines.
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。
Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile), within-sample (TPM, FPKM/RPKM), variance-stabilizing (VST, rlog, log-CPM), GC-content correction (cqn, EDASeq), and single-cell (scran deconvolution, scanpy normalize_total). Encodes the composition-bias rationale, the "most genes not DE" assumption and its catastrophic failure modes (MYC amplification, apoptosis, viral host shutoff, prokaryotic stress), the "lengthScaledTPM is not TPM" naming trap, the "TPM is not for DE" rule, the blind=TRUE vs FALSE decision, ERCC spike-in normalization (SBN), and the single-cell zero-inflation breakdown of TMM/RLE. Use when choosing or applying normalization, debugging shifted-MA-plot diagnostics, handling zero-heavy single-cell data, or correcting GC bias.
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。
Filter and select sequences by criteria (length, ID, GC content, N content, motifs, patterns, description) using Biopython, streaming so large files never load into RAM. Use when subsetting a FASTA/FASTQ file, removing unwanted or low-quality records, or selecting records by specific criteria. Use the paired-end-fastq skill instead whenever the input is paired R1/R2 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。
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.
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。
Assesses genetic health of populations for conservation with Ne estimation across time horizons (LDNe NeEstimator V2 option-file API + SNeP physical-linkage correction; recent trajectory via GONE/GONE2; deep history via Stairway Plot 2 / dadi / fastsimcoal2 / PSMC), F-statistics, runs of homozygosity binned by length class to date inbreeding, genetic-load decomposition (Bertorelle 2022 realized vs masked), the modern 100/1000 Ne rule (Frankham 2014), Ne/Nc 2-6 orders of magnitude in marine fish (Hauser & Carvalho 2008), tree-sequence forward simulations (SLiM 4 + pyslim + tskit), and the Sukumaran-Knowles caveat against MSC methods for management-unit definition. Use when estimating Ne by time horizon, detecting inbreeding via F_ROH, decomposing genetic load, justifying conservation thresholds, distinguishing ESU/MU/DPS, configuring NeEstimator V2, or correcting LDNe physical linkage.
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。
Comprehensive quality control for CLIP-seq libraries (eCLIP, iCLIP, iCLIP2, PAR-CLIP) covering library complexity (preseq), FRiP, IDR replicate reproducibility, read-distribution metagene, SMInput vs IgG control rationale, rRNA / snoRNA contamination, fragment-length distribution, and ENCODE-compliance thresholds. Use when assessing whether a CLIP library passed, deciding lenient vs stringent peak thresholds, comparing replicates with IDR rescue and self-consistency ratios, or distinguishing failed IP from over-amplified library.
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。
Queries PharmGKB / CPIC / DPWG for drug-gene interactions; calls CYP2D6/CYP2C9/CYP2C19/DPYD/TPMT/NUDT15/UGT1A1/SLCO1B1 star alleles and phenotype with PharmCAT, Cyrius (CYP2D6 structural variants), Aldy, Stargazer; applies Caudle 2020 activity-score translation. Use when implementing pharmacogenomic-guided prescribing, applying CPIC vs DPWG guidance, screening HLA risk alleles for ICI / antiepileptics / abacavir, or interpreting compound TPMT+NUDT15 thiopurine risk.
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。
Calls HLA class I and class II alleles at 2/4/6/8-field resolution from WGS/WES/RNA-seq/long-read data using OptiType, HLA-LA, T1K, Polysolver, HLA-HD, arcasHLA, StarPhase, or HIBAG imputation. Use when typing for HSCT, solid-organ transplant, neoantigen prediction, PGx screening (B*57:01, B*15:02, etc.), or disease-association studies, with reconciliation across tools and IPD-IMGT/HLA version mismatch handling.
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。
Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CA-CTCF/CA-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to target genes, classifying peaks against ENCODE cCRE registry, or running gene-set enrichment on peak-associated genes.
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。
Transition insulin pump to scheduled subcutaneous basal bolus insulin when anticipated hospital length of stay exceeds 1 to 2 days and pump expertise is unavailable. Triggers include: "Patient expected to stay >2 days, should we switch pump to scheduled insulin?
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。
Recommends continuing insulin pump therapy in hospitals with pump expertise; otherwise transitioning to scheduled subcutaneous basal bolus insulin if anticipated length of stay exceeds 1–2 days before pump discontinuation. Consider this when anticipating a hospital stay >2 days, lacking pump expertise, or needing to conserve supplies.
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。
Bring documentation prose down to a high-school reading level without losing precision. Runs after the content is written and before humanizer. Targets grade 9 on four measures — sentence length, vocabulary, clause load and jargon density — and carries the rewriting moves that actually shift them.
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。
A workflow skill that lets Codex keep coding for 60 hours on medium and large projects: Claude Code CLI plans through an interactive requirements questionnaire, PRD, specs, and roadmap; Codex implements verified vertical slices, with resumable Long-Run Execution for lengthy work; Trellis maintains project memory. Use when the user mentions 大项目工作流, Codex 连续开发 60 小时, Codex 长任务, long-running or resumable Codex implementation, large/medium project, new SaaS, multi-module system, requirements questionnaire, Claude Code CLI planning, Codex implementation handoff, Trellis bootstrap, non-system-drive project, or vertical slice. Skip for: single-file edits, casual Q&A, copy polish, throwaway prototypes, or tasks the user explicitly wants done fast without process.
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。
Auri: assistente de voz inteligente (Alexa + Claude claude-opus-4-20250805). Visao do produto, persona Vitoria Neural, stack AWS, modelo Free/Pro/Business/Enterprise, roadmap 4 fases, GTM, north star WAC e analise competitiva.
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。
Use for SWOT analysis, or when the user wants to assess where a team, product or company stands: "strengths and weaknesses", "should we enter this market?", "review our position", "competitor comparison". Turns findings into actions. Skip for detailed planning or pure market sizing.
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。
Play Clawing Trap - an AI social deduction game where 10 agents.
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。
Expert-level astrophysics covering stellar physics, galaxy formation, high-energy astrophysics, observational techniques, and the electromagnetic spectrum across wavelengths.
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。