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Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.

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Implement, review, or improve localization and internationalization in iOS/macOS apps — String Catalogs (.xcstrings), generated localizable symbols, stable key naming, LocalizedStringKey, LocalizedStringResource, pluralization, FormatStyle for numbers/dates/measurements, right-to-left layout, Dynamic Type, and locale-aware formatting. Use when adding multi-language support, setting up String Catalogs, enabling generated symbols for compile-time-safe localization keys, handling plural forms, formatting dates/numbers/currencies for different locales, testing localizations, or making UI work correctly in RTL languages like Arabic and Hebrew.

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Record a dated snapshot of the vault's health numbers and compare against previous snapshots so trends are visible. Use this skill for a monthly or quarterly check, when the user asks whether the vault is improving, or asks to track its numbers over time. Do NOT use for a one-off graph analysis, which is second-brain-graph, or for structural repairs.

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How to read experiment results without fooling yourself. Confidence intervals, p-values, multiple testing, sequential testing, CUPED, heterogeneous treatment effects, ratio metrics, network effects, dashboard reconciliation, and the interpretation failures that produce confidently wrong shipping decisions. Use this skill whenever the user is reading a finished experiment result panel and about to make a ship, kill, or iterate decision, or when an experiment number does not match the dashboard number. Triggers on read experiment results, result panel, ship or kill decision, p-value, confidence interval, statistical significance, multiple testing, peeking, sequential testing, CUPED, variance reduction, heterogeneous treatment effects, ratio metric, network effects, inconclusive test, experiment versus dashboard mismatch. Use `experiment-design` instead when the test has not run yet and the question is hypothesis, sample size, duration, or what to test.

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Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducin

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Implements the circular binary segmentation (CBS) algorithm to segment DNA copy number data and identify genomic regions with abnormal copy number.

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Use when a marketing BUDGET has to be planned or managed in USD — allocation by bucket, channel, and month, test versus scale split, scale-up and stop-loss thresholds, reserve, a plan-versus-actual tracker, and a review cadence. Trigger on 'budget planning', 'marketing budget', 'split the budget across channels', 'stop loss threshold', 'quarterly budget', 'we keep overspending and nobody notices'. Also use when a number has been approved and nobody has divided it up. Not for — the revenue-backward math that produces the number, see `10-reverse-kpi-global`; paid media allocation only, see `54-media-plan-global`; paying an external vendor, see `67-agency-vendor-brief-global`.

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Use when the user needs to WRITE a marketing report someone else will read — a one-page weekly for a CEO, a full monthly, or a quarterly strategy report with TL;DR, results versus target, insight, decisions needed, and next actions with owners. Trigger on 'marketing report', 'monthly report', 'weekly update for my boss', 'report for the client', 'quarterly summary', 'turn these numbers into a report'. Also use when the user says a stakeholder is asking how marketing is doing. Not for — diagnosing why the numbers are bad, see `03-performance-eval-global`; turning a raw export into insight, see `13-data-analysis-global`; a closed campaign retrospective, see `63-campaign-retrospective-global`.

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Use when marketing numbers look bad and the user needs to know WHY — layered root-cause diagnosis across tracking, delivery, creative, landing page, offer, and audience quality, 5-Whys, regional benchmarks for US, EU, SEA, and LATAM, and a 48-hour action plan. Covers dropshipping ROAS and BE-ROAS. Trigger on 'why is CPA so high', 'my ads are not converting', 'ROAS dropped', 'we are burning budget', 'performance is bad this month', 'diagnose the funnel'. Also use when the user pastes a screenshot of numbers with no question attached. Not for — auditing account configuration and scoring health, see `21-ads-audit-global`; writing a report someone else reads, see `07-marketing-report-global`; turning a raw export into insight, see `13-data-analysis-global`.

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Weekly, on a Friday, read only everywhere. Scores the week from the kit's own ledgers with a source path beside every number, cuts it by platform, framework, pillar, slot time, and post length, rewrites the drafting standards from that evidence and from nothing else, replays the browser flows the other routines depend on, and files exactly one thing to stop and one to do more of. It publishes only where you released the channel, never replies, spends only where you released it, never touches a credential, and never writes a number it did not measure.

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Weekly. Scores the week from the ledgers with a source path beside every number and never writes a number it did not count in a file this run. It names exactly two things and files both as cards, the one fix worth doing next week and the one thing to stop, and it replays every learned browser flow once, read only, so a drifted selector is found on a Friday rather than on a Tuesday morning a routine needed 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。

Weekly, on a Friday, read only everywhere. Scores the week from the ledgers with a source path beside every number, replays the browser flows the other routines depend on, names one thing to kill and one thing to scale, and files both as cards. It sends only where you released the channel, spends only where you released it, never touches a credential, and never writes a number it did not count out of a named file this run.

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。

Weekly, on a Friday, read only everywhere. Scores the week from the ledgers with a source beside every number, replays the browser flows the other routines depend on, names one thing to kill and one thing to scale, and files both as cards. It sends only where you released the channel, spends only where you released it, never touches a credential, and never writes a number it did not measure.

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。

Weekly, conditional browser lane, read only everywhere. Scores the fleet and the business for the week with a source beside every single number and no number anywhere without one, cites the Employee that owns a metric rather than recomputing it, refuses a rate below the floor, and writes one capped weekly page. It opens a browser only where the metric map names a live screen, never writes into another Employee's folder, sends only where you released the channel, spends only where you released it, and never touches a credential.

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无用数字字符清理工具。读取结构化文本数据，对指定或全部文本字段移除无语义的独立数字字符，输出清理后的结构化文件。 当用户提到无用数字字符清理、数字噪声删除、文本中的杂散数字清理等需求时使用此skill。 即使用户没有明确说出"number_noise_cleaner"，只要任务涉及从文本中删除无业务意义的数字字符，就应该使用此skill。 不负责数值规整、字段校验或通用正则替换。

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Use when the user wants to verify paper claims against code or data, audit numerical accuracy, check formula-code alignment, or validate citation accuracy. Triggers on phrases like "verify claims", "check numbers", "do the numbers match", "formula vs code", "audit the paper", or "cross-check results".

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Your CFO. Builds the unit economics of a business before money is spent: what one unit earns after its direct costs, the real profit margin at the planned volume, the break-even point in units a day, year 1 month by month, the cash needed before it pays for itself, how long the startup spend takes to earn back, and what happens if the price drops, sales come in low or costs rise. Every number traces to an input the user can check. Use when the user says "find the profit margins", "do the numbers", "is this profitable", "break-even", "unit economics", "how much do I need to start", or "run the CFO".

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This skill should be used when the user asks about the invoice system (インボイス制度), qualified invoices (適格請求書), registration numbers (登録番号), input tax credits (仕入税額控除), the 20% special measure (2割特例), the 30% special measure (3割特例), tax-exempt businesses (免税事業者), transitional measures (経過措置), small-amount exceptions (少額特例), corrected invoices (修正インボイス), or any related topics. Trigger phrases include: "インボイス", "適格請求書", "登録番号", "仕入税額控除", "2割特例", "3割特例", "免税事業者", "経過措置", "少額特例", "修正インボイス", "返還インボイス", "簡易インボイス", "インボイス登録", "T番号", "適格請求書発行事業者".

Answers business questions about the user's own spreadsheet or data export (CSV, TSV, XLSX from a CRM, Shopify, Stripe, QuickBooks, ad platforms, HR or payroll systems) correctly and auditably. Profiles every file first (grain, duplicate keys, embedded Grand Total rows, text-stored numbers, mixed currencies, UTC timestamps, Excel serial dates, hidden rows), states the metric definition used, computes every number in SQL or pandas instead of mental math, checks joins for fan-out, reconciles to a known total, and returns the query, filters, row counts, and rows behind the answer. Use this whenever the user says "analyze this spreadsheet", "how many...", "what's the total in this export", "which customers...", "pivot this", "revenue by month", "top 10", "what's our churn/MRR/AOV", or asks any question about their data, CSV, or Excel file, even a quick one. Also use when they ask to change values in a data file.

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Show Honey's benchmark scoreboard — the committed quality and token results per task tier (code, user-facing, agent-to-agent) from bench/. Reports only the reproducible committed figures, never invents per-repo numbers. Use when asked how much Honey saves, how it compares to Caveman / Ponytail / no-skill baseline, or for the headline numbers.

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Build AI phone agents with AgentPhone API. Use when the user wants to make phone calls, send/receive SMS, manage phone numbers, create voice agents, set up webhooks, or check usage — anything related to telephony, phone numbers, or voice AI.

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Use when implementing format and validate phone numbers.

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Corrects the gene-independent copy-number artifact in CRISPR-Cas9 screens (Aguirre 2016 / Munoz 2016 Cancer Discov) where amplified loci appear essential from DNA-damage burden of simultaneous cuts. Covers the p53-dependent G2-arrest mechanism, CRISPRcleanR (Iorio 2018) unsupervised pre-hoc correction, CERES (Meyers 2017) joint CN + gene-effect model, Chronos (Dempster 2021) DepMap-standard population-dynamics + CN model with lowest residual bias, the decision tree by data availability, the Spearman LFC-vs-CN diagnostic, focal-amplification examples (ERBB2 in HER2+, MYC in colorectal, FGFR1 in head and neck), and CRISPRi/a alternatives that bypass the artifact. Use when screening cancer cell lines, diagnosing essentiality at amplified loci, choosing CRISPRcleanR / CERES / Chronos, deciding whether CN correction is needed before MAGeCK / BAGEL2 / drugZ, or switching from Cas9 to CRISPRi.

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Normalize read-depth copy-ratio profiles and segment them into copy-number regions using circular binary segmentation (CBS, DNAcopy), hidden Markov models, HaarSeg, and fused-lasso methods. Covers GC-content, mappability, and replication-timing (wave-artifact) bias correction, panel-of-normals/PCA denoising, diploid-baseline centering, and algorithm selection by sequencing depth and event size. Use when choosing a segmentation algorithm, correcting depth bias, diagnosing oversegmentation or a mis-centered baseline, tuning CBS or HMM parameters, or understanding why a downstream CNV caller produced fragmented or shifted segments.

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。