321 skills · sorted by relevance
AI CRO Expert — landing page audit, A/B test plan, funnel analysis, heatmap interpretation, form optimization สำหรับเว็บไซต์และ e-commerce ไทย
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Comprehensive astrology expert covering natal charts, transits, houses, aspects, and astrological traditions from Western to Vedic
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Palm reading expert covering line interpretations, hand shapes, mounts, and traditional chiromancy practices
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Numerology expert covering life path numbers, name numbers, and Pythagorean to Chaldean systems
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I Ching (易經) expert covering hexagram interpretation, traditional wisdom, and consultation methods
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Scholar of biblical interpretation covering Hebrew Bible and New Testament with historical-critical and literary methods
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Deep analysis of competitor patent claims: element decomposition, scope interpretation, equivalents prediction, prosecution history estoppel analysis. Automatically converts PDF/DOCX/DOC patent files to structured Markdown via patent-pdf-to-md skill before analysis. Invoke when user asks to analyze/parse competitor patent claims, decompose claim elements, assess claim scope, or perform 权利要求解析/要素分解/保护范围解读. 竞品专利权利要求深度解析：要素分解、保护范围解读、等同范围预判、审查历史限制分析。自动调用patent-pdf-to-md技能将PDF/DOCX/DOC专利文件转换为结构化Markdown后再进行分析。当用户要求解析竞品专利权利要求、要素分解、保护范围时触发。
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Abductive reasoning about causes. Takes a phenomenon, separates observations from interpretations, then spawns diagnosticians applying different reasoning lenses (technical, human-factors, process, incentive-structure, environmental, temporal, measurement-artifact, statistical) in isolation. Orchestrator evaluates candidate causes for fit-against-evidence, calibrates confidence honestly, and reports leading candidate(s) with distinguishing evidence needed. Produces feedback only — no code, no tickets, no artifacts.
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占事吉凶 · 测吉凶：针对**某一件具体事、某一天、某一刻**的吉凶研判与择吉建议。 运用「黄历择日 + 四柱命理本命喜忌 + 阴阳五行天时地利 + 天人感应/梅花心易」四层独立推演， 再交叉汇聚成【吉 / 平·宜谨慎 / 凶·宜改期】的整体倾向与可执行建议。 当用户问：测吉凶、占吉凶、这事能不能做、今天适不适合出门/旅行/搬家/开业/签约/求医、 出行吉凶、看日子、择日、挑个好日子、黄历、老黄历、今天宜不宜、宜忌、冲煞、起一卦、 算算这件事顺不顺、"临出发前忽然心悸/心慌，是不是预兆"、"我有种不好的预感" 时使用。 English triggers: "is today auspicious", "is it a good day to travel/move/sign", "should I go today", "pick an auspicious day", "Chinese almanac / huangli", "divination for a decision", "I have a bad feeling about going out today". 内置离线脚本：公历→农历+完整四柱+十神（bazi.py）、黄历宜忌/建除/值神/廿八宿/彭祖百忌/ 冲煞/吉神凶煞/逐时辰吉凶+梅花时间起卦（almanac.py）、经纬度定位+当天当地天气（geoweather.py）。 边界：要**批一生八字/大运流年**请用 `bazi` 技能；要**解梦**请用 `zhougong-dream-interpretation`。 即使用户只是随口问「今天出门好不好」「这事顺不顺」，也应主动使用本技能。
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塔罗牌占星：把「抽三张塔罗牌」与「西方占星本命盘」合为一次解读。 用户带着一个具体问题来 → 抽三张牌（可复现的 seed）→ 若愿意提供生日，则用脚本 确定性地排出星座与星盘 → 用黄金黎明的塔罗↔占星对应把两者接起来（牌落在黄道哪一旬， 你的哪颗行星正站在那里）→ 给出一张交叉对照表、对所问之事的审慎取向与可执行建议。 塔罗层：牌阵位置语义、牌与牌的组合叙事、元素尊贵、正逆位、直觉对话、治疗性解读。 占星层：本命盘、相位与宫位、必然尊贵、行运盘推运、比较盘/组合盘（合盘）、太阳弧推运。 当用户说：塔罗、塔罗牌、抽牌、抽三张牌、占卜、算一卦（西洋）、牌阵、正逆位、 星盘、本命盘、星座、上升星座、月亮星座、占星、行运、流年、合盘、比较盘、 太阳弧、推运、我该不该……、这段关系会怎样、我适不适合换工作 时使用。 English triggers: "tarot", "tarot reading", "draw three cards", "what do the cards say", "spread", "reversed card", "natal chart", "birth chart", "astrology", "rising sign", "transits", "synastry", "composite chart", "solar arc", "progressions", "should I take this job", "what does my chart say". 内置离线脚本：抽牌洗牌（可复现 seed）、本命盘（行星/四轴/宫位/相位/元素统计）、 必然尊贵、牌↔盘共鸣、元素数字统计、行运盘、比较盘+组合盘、太阳弧+次限推运。 边界：要**周公解梦**请用 `zhougong-dream-interpretation`；要**四柱八字**请用 `bazi`； 要**中式黄历择日/测吉凶**请用 `zhanshi-jixiong`。本技能只做西洋塔罗与西洋占星。 即使用户只是随口说「帮我抽张牌看看」「我最近水逆吗」，也应主动使用本技能。
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Pedagogical patterns for enriching notebooks (GameTheory model). Use when adding interpretations, structuring notebooks, or creating educational content in Jupyter notebooks.
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Preventive hygiene audit of your own Claude Code configuration — memory files, project context (CLAUDE.md), rules, permissions, skills — a deterministic scan of sizes / broken links / stale entries / excessive permissions / junk + interpretation + targeted fixes by agreement. Keeps the setup from rotting before it breaks. Triggers — "check the system", "system health", "workflow hygiene", "what to clean up", "audit memory", "optimize the system".
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Runs JACKS (Joint Analysis of CRISPR/Cas9 Knockout Screens; Allen et al 2019 Genome Research) which models per-sgRNA log-fold-change as the product of a treatment-dependent gene-essentiality term and a treatment-independent guide-efficacy term. Covers the Bayesian decomposition math, the hierarchical efficacy prior shared across screens performed with the same library, when JACKS outperforms MAGeCK (multi-screen joint analysis, libraries with broad efficacy variance) and when it does not (single screen, novel libraries with no prior efficacy), library-reuse efficacy transfer, downstream essentiality interpretation, and the 2.5x sample-size reduction enabled by efficacy-aware testing. Use when running multiple screens with the same library, when guide-level noise is suspected to dominate per-gene signal, when reusing published essentiality reference screens for efficacy priors, or when comparing screens performed across cell lines that share library but differ biologically.
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Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.
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Analyzes base-editing screens for variant function. Covers library design (Hanna 2021 ClinVar-scale CBE screen benchmarked on BRCA1/2, Cuella-Martin 2021 DDR saturation), CBE vs ABE chemistry choice (BE3/BE4 vs ABE7.10/ABE8.20/ABE8e), editing-window math (positions 4-8 from PAM-distal end; 4-7 for ABE7.10), bystander-edit quantification and the variant-call ambiguity it creates, sgRNA-efficiency filtering before hit calling, indel byproduct interpretation, the substitution-vs-indel diagnostic, variant annotation against ClinVar / COSMIC, and the Broad be-validation-pipeline. Use when designing a BE variant screen, choosing CBE vs ABE for a specific edit, interpreting bystander-confounded hits, distinguishing functional signal from indel artifact, integrating CRISPResso2 output with screen scoring, or deciding BE vs PE for SNV installation.
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Designs and analyzes combinatorial CRISPR screens covering paired-Cas9 (Big Papi, Najm 2018), enhanced AsCas12a multiplex (enCas12a, DeWeirdt 2021), in4mer 4-guide-array Cas12a (Esmaeili Anvar N et al 2024 Nat Commun 15:3577) and the Inzolia paralog-pair library, paralog-buffering detection (Dede 2020 Genome Biol; Thompson 2021 Nat Commun 12:1302), genetic-interaction (GI) scoring as observed_double_LFC minus expected_additive_double_LFC, synthetic-lethal and synthetic-rescue interaction interpretation, the half-of-essentiality buffered by paralogs phenomenon, multiplex screen statistical analysis with MAGeCK MLE interaction terms, and the relationship to single-cell combinatorial Perturb-seq. Use when designing a paralog or pathway-pair screen, choosing between paired-Cas9 (Big Papi) and Cas12a multiplex (Inzolia), interpreting genetic interaction scores, identifying synthetic-lethal targets for drug development, or scaling beyond single-gene CRISPR screens.
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Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor (pegRNA-templated) modes. Covers single-amplicon (CRISPResso), multi-sample batch (CRISPRessoBatch), pooled-amplicon (CRISPRessoPooled), WGS off-target (CRISPRessoWGS), and sample-comparison (CRISPRessoCompare) workflows; quantification-window math that controls what is called edited; substitution-vs-indel diagnostic to distinguish BE from Cas9 contamination; MMEJ deletion pattern interpretation; allele-frequency tables; and failure modes from amplicon misalignment or contamination. Use when quantifying editing from amplicon sequencing, choosing CRISPResso mode by design, distinguishing intended edits from bystanders and indel byproducts, debugging low-alignment runs, or generating publication-grade editing reports.
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Predict RBP binding from RNA sequence using deep learning models (RBPNet sequence-to-signal, RNAProt RNN, GraphProt2 GCN with structure, DeepCLIP, DeepRiPe multi-modal CNN) for variant-effect prediction, in silico binding-site discovery, model interpretation, and transfer learning from CLIP and RBNS datasets. Use when computational prediction of RBP binding from sequence is needed, evaluating variant effects on binding without further wet-lab experiments, comparing model performance, or training a custom model on ENCODE eCLIP data.
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Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, or distinguishing the automatable evidence from the case-specific evidence requiring manual input.
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Queries gnomAD v4 (807k samples), v3, v2.1.1, and constraint metrics with grpmax FAF95, bottleneck-group exclusion, LOEUF interpretation, SV/CNV/mtDNA catalogs, and Whiffin max-credible-AF framework. Use when filtering rare variants, applying ACMG BS1/BA1, ranking genes by LoF intolerance, or selecting between v2 (GRCh37 + chrX/Y constraint) and v4 (GRCh38 + 807k samples).
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Determines unilateral vs bilateral aldosterone excess based on cortisol-corrected aldosterone ratios from adrenal venous sampling, with ratio >4:1 indicating unilateral excess, ratio 3:1 suggestive of bilateral hypersecretion, and interpretation dependent on cosyntropin stimulation protocol used during sampling. Use when analyzing AVS results to guide surgical vs medical treatment decisions; triggers include 'AVS lateralization ratio', 'cosyntropin-stimulated AVS', 'aldosterone-to-cortisol ratio >4:1', and 'ratio 3:1 suggestive of bilateral disease'.
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Order and interpret lipoprotein(a) [Lp(a)] measurement at least once in a lifetime, apply the risk-enhancer threshold (≥125 nmol/L or ≥50 mg/dL), and run cascade screening of first-degree relatives for premature ASCVD, familial hypercholesterolaemia, or elevated Lp(a) per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers the Class 1 lifetime measurement, how elevated Lp(a) affects LLT initiation and intensification, the cascade screening indications, the interaction of Lp(a) with ASCVD risk estimation, and current therapeutic limitations. Use when a clinician asks when to check Lp(a), how often to repeat Lp(a), elevated Lp(a) what next, treatment for high Lp(a), should I screen my patient's family, Lp(a) and statins, cascade screening indications. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.
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Calculate and interpret the PREVENT-ASCVD risk score (10-year and 30-year) for primary prevention of atherosclerotic cardiovascular disease per the 2026 ACC/AHA multisociety dyslipidaemia guideline. Covers inputs required, risk-category thresholds (low <3%, borderline 3–<5%, intermediate 5–<10%, high ≥10%), when to use the 30-year calculation (adults 30–59), and how PREVENT differs from the older Pooled Cohort Equations (lower risk estimates by 40–50%, race-agnostic). Use when a clinician asks what the 10-year ASCVD risk is, how to calculate PREVENT, PCE vs PREVENT, risk category for this patient, does my patient need a statin, 30-year risk calculation, primary prevention risk assessment. Grounded in the 2026 ACC/AHA multisociety dyslipidaemia guideline.
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Performs corticotropin stimulation test to diagnose adrenal insufficiency when morning cortisol is indeterminate (3-15 µg/dL). Triggers include morning cortisol 3-15 µg/dL requiring further AI testing.
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