「terms」の検索結果

Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue/cell-type ontologies (UBERON/CL) or analyzing variants in chr:pos:ref>alt format.

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Expert en négociation de contrats (terms, SLAs, renewal, upsell, legal review, redlines)

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 en négociation de contrats v2 (terms, SLAs, renouvellement, PI, responsabilité, contexte juridique DZ)

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 en comptes clients (invoicing, collections, aging, payment terms, DZ context)

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Draft privacy policies, terms of service, disclaimers, and legal notices. Creates GDPR-compliant texts, cookie policies, and data processing agreements.

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。

Product-research (选品) desk (Busabase App-in-Skill) for a cross-border e-commerce seller. The agent sweeps trend sources — Amazon BSR movers, TikTok viral product videos, Temu/AliExpress rising items, Google Trends terms, competitor new launches — and files product candidates with margin cards (landed cost, fees, breakeven ACOS) and competition reads; Kelly verdicts them develop / watch / drop, and develop items become sourcing and listing briefs handed to kelly-listing. Use when the user invokes $kelly-picks or /kelly-picks, or asks for 选品, product research, a product sourcing radar, BSR movers, TikTok viral products, a margin calculator, breakeven ACOS, competition reads, or product candidate triage.

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Busabase-backed App-in-Skill dashboard for a revenue-based-financing (RBF) fund or private-credit book of many small SME contracts. Use when the user invokes $kelly-portfolio-health or /kelly-portfolio-health, wants to check portfolio health, AUM, repayment progress, concentration risk, or a watchlist of contracts with declining revenue. Human actions (flag a contract for review, clear a flag, leave a note) write directly onto the contract's own Busabase record — this skill never moves money or changes contract terms. Generic and brand-free — not tied to any specific company or fund.

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。

Ad-campaign command desk (投放指挥台, Busabase App-in-Skill) for a cross-border e-commerce seller running Amazon Ads, Meta (FB/IG), TikTok Ads, and Google Ads. Use when the user invokes $kelly-ads or /kelly-ads, or asks about 投放, ad campaigns, ad spend, ACOS, ROAS, Amazon Ads, TikTok ads, Meta ads, Google Ads, search terms, negative keywords, bid adjustment, budget pacing, CPC spikes, rejected ads, ad anomaly detection, 广告优化, or reviewing agent-proposed adjustment cards (negative keyword, bid down/up, pause target, budget shift, creative refresh).

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Use when asked to map, crosswalk, align, compare, or gap-analyze any two cybersecurity frameworks, control catalogs, or regulatory requirements using NIST IR 8477 Set-Theory Relationship Mapping (STRM). Triggers on terms like "map controls", "crosswalk", "framework alignment", "gap analysis", or producing a STRM CSV output file.

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Orchestrates the full path from differential expression results to redundancy-collapsed functional enrichment: choose ORA vs GSEA, convert gene IDs per method, run enrichGO/enrichKEGG/enrichPathway/enrichWP or gseGO/gseKEGG (clusterProfiler, ReactomePA, rWikiPathways), and visualize. Use when a DESeq2/edgeR/limma result must become enriched GO terms, KEGG/Reactome/WikiPathways pathways, or a GSEA leading edge; when the input is a full ranking for all genes (GSEA, named decreasing vector) or only a pre-selected list (ORA plus a defensible background universe); or when assembling DE-to-pathway end to end. The DE list and ranking statistic come from differential-expression/de-results; per-method nuance lives in the pathway-analysis skills.

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 an editable DOCX service agreement with parties, terms, and payment schedule.

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Generate a non-disclosure agreement PDF with party names, effective date, and standard confidentiality terms.

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Extract landlord, tenant, property, lease dates, rent, deposit, utilities, occupants, and pet terms from residential leases.

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Extract key terms from a non-disclosure agreement, then generate a compliance checklist spreadsheet tracking obligations and deadlines.

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Extract parties, obligations, restrictions, permitted disclosures, and expiry dates from non-disclosure agreements.

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。

This skill enables Claude to perform comprehensive accessibility audits. It uses the accessibility-test-scanner plugin to identify WCAG 2.1/2.2 compliance issues, validate ARIA attributes, check keyboard navigation, and assess screen reader compatibility. Use this skill when the user requests an accessibility scan, audit, or compliance check, or when terms like "WCAG", "ARIA", "screen reader", "accessibility testing", or "a11y" are mentioned. It provides actionable insights for improving web application accessibility.

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Help a user talk through whether to change jobs, stay, or change something in their current work, starting from uncertainty, distress, a vague sense of stagnation, an offer in hand, a counter-offer from the current employer, or pressure from family or colleagues. Clarify what matters, separate deadlines that order the next steps from the decision itself, compare conditional options, and agree on a small next step and a time to revisit it. Use when someone asks whether they should quit, wonders whether leaving is just running away, has second thoughts after receiving an offer or being asked to stay, feels stuck because others say it would be a waste, wants to leave soon after joining, or wants advice before deciding to start a job search; do not make the final stay-or-leave decision, evaluate offer terms, plan the resignation, or predict hiring outcomes.

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Help job seekers use Otameshi Tenshoku to prepare profiles and applications, clarify trial conditions, plan learning visits or paid trial work, and reflect on the experience. Use when a candidate wants to apply for, prepare for, negotiate the scope of, or review an otameshi work experience; do not use to predict whether they will be hired or to judge their aptitude, to state fees, contract terms, or service conditions from memory, or to submit an application, update a profile, or send a message on their behalf. Employer-side requests belong to the employer skills (trial-work-design, trial-listing-draft, applicant-reply and others).

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Read a Japanese job posting closely and report what it actually states: base pay separated from fixed overtime allowance, the range converted to an hourly basis, required versus preferred requirements, and the terms left ambiguous. Use when a user wants a 求人票 or job description examined before applying, wants two postings compared on the same basis, or wants questions prepared about pay and working conditions; do not use to judge whether the user will be hired, to infer duties the posting does not state, or to evaluate the employer's reputation.

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Plan the first months at a new Japanese employer after an offer is accepted, listing every expectation and promise made in interviews, the offer, or negotiation with its source, separating what is in writing from what was only said and what has no agreed measure, working out when the probation period ends and whether its criteria and conditions are known, and scheduling who to confirm what with before and after the start date. Use when a user has accepted an offer and wants to prepare for joining, make sure verbal promises such as remote days or a future role are confirmed, or understand what the probation period means for them; do not use to predict whether they will fit in or pass probation, to judge their manager or colleagues, to rule on the legality of probation terms, or to contact the new employer.

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Put two or more Japanese job offers on one basis so they can be read side by side, separating fixed overtime allowance and unguaranteed bonus from the stated annual figure, converting each offer to guaranteed annual pay and to an hourly rate that includes deemed overtime hours, and listing non-monetary terms without scoring them. Use when a user holds more than one offer, wants to know what a stated 年収 actually contains, or wants to see where the ranking changes once the components are separated; do not use to recommend which offer to accept, to score or rank offers, to estimate take-home pay as fact, or to reply to an employer.

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 domain terms drifting between code identifiers and the established ubiquitous language (same concept under different names, or different concepts sharing a name).

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Assigns GO terms, Pfam/InterPro domains, KEGG orthologs, EC numbers, and product names to predicted proteins using eggNOG-mapper (orthology), InterProScan (domain signatures), and KofamScan (KEGG), routing specialized functions to dbCAN/antiSMASH/AMRFinderPlus/SignalP. Covers the orthology-vs-domain-vs-homology paradigms, the annotation-error percolation cascade, domain-presence-is-not-function, GO IEA circularity in enrichment, evidence tiering, and bit-score/coverage thresholds. Use when adding functional annotation to predicted genes, choosing between eggNOG-mapper and InterProScan, or judging how much to trust a functional label.

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Performs differential expression on bulk RNA-seq count data with DESeq2's negative-binomial GLM, Wald and LRT testing, apeglm/ashr/normal LFC shrinkage, independent filtering, Cook's outlier handling, VST/rlog transforms, and design formulas including paired, batch, and interaction terms. Use when running bulk DE, choosing DESeq2 over edgeR or limma-voom, building a paired or interaction design, applying LFC shrinkage for ranking or GSEA, choosing Wald vs LRT, troubleshooting padj=NA, picking VST vs rlog, importing salmon/kallisto via tximport, or analyzing prokaryotic RNA-seq.

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。