「rtm」の検索結果

Detects A/B chromatin compartments from balanced Hi-C contact matrices via eigenvector decomposition of the distance-normalized, Pearson-correlated cis matrix with cooltools (eigs_cis), then orients (phases) the compartment eigenvector against a GC or gene-density track so the active (A) sign is not arbitrary. Covers the eigenvector-is-a-choice problem (per-arm view_df to remove the centromere gradient; picking the eigenvector by max correlation with activity, not by eigenvalue), GC phasing with bioframe.frac_gc, resolution choice (100kb-1Mb), saddle plots and saddle_strength for compartmentalization strength, the cohesin-loss-strengthens-compartments result, subcompartments (SNIPER/Calder/dcHiC), and cross-condition compartment switching. Use when calling A/B compartments, computing E1/eigenvectors, phasing the eigenvector, building saddle plots, choosing a compartment resolution, quantifying compartment strength, or comparing compartmentalization across conditions.

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Detects A/B chromatin compartments from balanced Hi-C contact matrices via eigenvector decomposition of the distance-normalized, Pearson-correlated cis matrix with cooltools (eigs_cis), then orients (phases) the compartment eigenvector against a GC or gene-density track so the active (A) sign is not arbitrary. Covers the eigenvector-is-a-choice problem (per-arm view_df to remove the centromere gradient; picking the eigenvector by max correlation with activity, not by eigenvalue), GC phasing with bioframe.frac_gc, resolution choice (100kb-1Mb), saddle plots and saddle_strength for compartmentalization strength, the cohesin-loss-strengthens-compartments result, subcompartments (SNIPER/Calder/dcHiC), and cross-condition compartment switching. Use when calling A/B compartments, computing E1/eigenvectors, phasing the eigenvector, building saddle plots, choosing a compartment resolution, quantifying compartment strength, or comparing compartmentalization across conditions.

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Detects A/B chromatin compartments from balanced Hi-C contact matrices via eigenvector decomposition of the distance-normalized, Pearson-correlated cis matrix with cooltools (eigs_cis), then orients (phases) the compartment eigenvector against a GC or gene-density track so the active (A) sign is not arbitrary. Covers the eigenvector-is-a-choice problem (per-arm view_df to remove the centromere gradient; picking the eigenvector by max correlation with activity, not by eigenvalue), GC phasing with bioframe.frac_gc, resolution choice (100kb-1Mb), saddle plots and saddle_strength for compartmentalization strength, the cohesin-loss-strengthens-compartments result, subcompartments (SNIPER/Calder/dcHiC), and cross-condition compartment switching. Use when calling A/B compartments, computing E1/eigenvectors, phasing the eigenvector, building saddle plots, choosing a compartment resolution, quantifying compartment strength, or comparing compartmentalization across conditions.

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[omh] Recurring market or topic research: research operations department - coordinate Scout, Analyst, and Briefer work with source-inbox and status boundaries; for one decision brief use research-brief, and for typed candidates before research starts use source-finder. Use when the user says: research-department, research department, research ops department, research operations department, scout analyst briefer, scout analyst brief, daily research department, competitor research department.

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Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".

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Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C data.

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Search Sutochno.ru (СУТОЧНО.РУ), a Russian short-term apartment-rental platform where you book directly from owners and pay in rubles (Mir card / bank transfer). Best for Russian-speaking travellers booking stays in Georgia / the CIS, where Airbnb and Booking have withdrawn or do not accept Russian cards. Sutochno is NOT behind a bot wall — it ships on the toolkit standard patchright-docker base but runs the bundled chromium headless with no Akamai sensor to defeat. Trigger phrases include search Sutochno, суточно, Russian apartment rental, ruble payment, Mir card, Tbilisi apartment, Batumi apartment, Georgia CIS rental.

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Detect A/B compartments from Hi-C data using cooltools and eigenvector decomposition. Identify active (A) and inactive (B) chromatin compartments from contact matrices. Use when identifying A/B compartments from Hi-C data.

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Use this skill when building or maintaining a Requirements Traceability Matrix (RTM) on a Salesforce project: one row per requirement, columns for source, user-story id(s), test-case id(s), defect id(s), sprint, release, and status. Covers forward traceability (req → story → code → test) and backward traceability (test → req). Trigger keywords: RTM, requirements traceability matrix, audit trail for salesforce delivery, traceability for steerco, deferred requirement tracking, regulatory traceability. NOT for eliciting the requirements in the first place — use admin/requirements-gathering-for-sf. NOT for user-story authoring — use admin/user-story-writing-for-salesforce. NOT for UAT test design — use admin/uat-test-case-design. NOT for Apex test design — use apex/test-class-standards. NOT for backlog prioritization — use admin/moscow-prioritization-for-sf-backlog. More triggers: traceability.md, build-layer traceability, REQ-XXX and FG-XXX id mapping, artefact-to-requirement orphan report, coverage-gap report, check_rtm.py --manifest-dir, owning run-time agent column, design decision ref column, metadata API name in a traceability row.

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Diagnostic-only test suite auditor. Classifies repo type, maps against 7-layer testing taxonomy (git hooks → static → unit → integration → system → E2E → acceptance), runs deterministic quality gates (coverage, mutation, CRAP, architecture, escape-scan), builds RTM / personas / journeys traceability, produces TEST_AUDIT.md, updates tests/TESTING.md, and mandatorily hands off to implement-tests when gaps are found. Use when auditing test quality, finding test gaps, or running the full 7-layer sweep. Trigger with "audit tests", "find gaps", "test audit", "check test quality", "full sweep", "7-layer audit", "rtm check".

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AI 短剧 (AI 微短剧) (AI 短剧 (AI 微短剧) (从业者视角) — 用 AIGC 工具（AI 视频生成 / AI 脚本 / AI 生图 / AI 配音 / 对口型 / 角色一致性）制作竖屏微短剧并变现的新兴行业。覆盖: (a) 创作工作流 — 选题→剧本/分镜→AI 生图→图生视频(首尾帧/运镜/参考)→配音/对口型→剪辑/调色→成片，其中角色/场景一致性是第一性难题; (b) 工具栈 — 视频生成(可灵 Kling / 即梦 Seedance / 海螺 Hailuo / Vidu / Runway Gen / OpenAI Sora / Pika / Luma / Pixverse)、脚本(LLM)、生图(Midjourney/SD/即梦)、配音(TTS)、对口型、剪辑(剪映/CapCut); (c) 商业/变现 — 国内付费投流(IAP + ROI + 平台分账, 抖音/快手/红果/微信小程序短剧)与海外订阅(ReelShort/DramaBox/ShortMax/GoodShort)两套打法、品牌定制、成本结构; (d) 合规 — 中国《人工智能生成合成内容标识办法》(2025-09 强制 AI 标识)、广电微短剧备案与分类分层审核、版权与肖像权。主战场 = 抖音/快手/视频号/B站 + 海外短剧 App。学派分歧: 纯 AI vs AI+实拍混合、国内投流 vs 海外订阅、视频工具派之争、「AI 短剧是真需求还是伪风口」。不含: 传统实拍短剧制作、通用影视编剧(已有 scriptwriting skill)、短视频信息流投放(已有 short-video-ads skill)、纯 AI 视频底层技术研发。) Master OS — automated mastery of AI 短剧 (AI 微短剧) (从业者视角) — 用 AIGC 工具（AI 视频生成 / AI 脚本 / AI 生图 / AI 配音 / 对口型 / 角色一致性）制作竖屏微短剧并变现的新兴行业。覆盖: (a) 创作工作流 — 选题→剧本/分镜→AI 生图→图生视频(首尾帧/运镜/参考)→配音/对口型→剪辑/调色→成片，其中角色/场景一致性是第一性难题; (b) 工具栈 — 视频生成(可灵 Kling / 即梦 Seedance / 海螺 Hailuo / Vidu / Runway Gen / OpenAI Sora / Pika / Luma / Pixverse)、脚本(LLM)、生图(Midjourney/SD/即梦)、配音(TTS)、对口型、剪辑(剪映/CapCut); (c) 商业/变现 — 国内付费投流(IAP + ROI + 平台分账, 抖音/快手/红果/微信小程序短剧)与海外订阅(ReelShort/DramaBox/ShortMax/GoodShort)两套打法、品牌定制、成本结构; (d) 合规 — 中国《人工智能生成合成内容标识办法》(2025-09 强制 AI 标识)、广电微短剧备案与分类分层审核、版权与肖像权。主战场 = 抖音/快手/视频号/B站 + 海外短剧 App。学派分歧: 纯 AI vs AI+实拍混合、国内投流 vs 海外订阅、视频工具派之争、「AI 短剧是真需求还是伪风口」。不含: 传统实拍短剧制作、通用影视编剧(已有 scriptwriting skill)、短视频信息流投放(已有 short-video-ads skill)、纯 AI 视频底层技术研发。: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on AI 短剧 (AI 微短剧) (从业者视角) — 用 AIGC 工具（AI 视频生成 / AI 脚本 / AI 生图 / AI 配音 / 对口型 / 角色一致性）制作竖屏微短剧并变现的新兴行业。覆盖: (a) 创作工作流 — 选题→剧本/分镜→AI 生图→图生视频(首尾帧/运镜/参考)→配音/对口型→剪辑/调色→成片，其中角色/场景一致性是第一性难题; (b) 工具栈 — 视频生成(可灵 Kling / 即梦 Seedance / 海螺 Hailuo / Vidu / Runway Gen / OpenAI Sora / Pika / Luma / Pixverse)、脚本(LLM)、生图(Midjourney/SD/即梦)、配音(TTS)、对口型、剪辑(剪映/CapCut); (c) 商业/变现 — 国内付费投流(IAP + ROI + 平台分账, 抖音/快手/红果/微信小程序短剧)与海外订阅(ReelShort/DramaBox/ShortMax/GoodShort)两套打法、品牌定制、成本结构; (d) 合规 — 中国《人工智能生成合成内容标识办法》(2025-09 强制 AI 标识)、广电微短剧备案与分类分层审核、版权与肖像权。主战场 = 抖音/快手/视频号/B站 + 海外短剧 App。学派分歧: 纯 AI vs AI+实拍混合、国内投流 vs 海外订阅、视频工具派之争、「AI 短剧是真需求还是伪风口」。不含: 传统实拍短剧制作、通用影视编剧(已有 scriptwriting skill)、短视频信息流投放(已有 short-video-ads skill)、纯 AI 视频底层技术研发。 problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「ai 短剧」「ai 微短剧」「ai short drama」「ai 短剧制作」「ai 短剧工作流」

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Turn in vitro potency and animal pharmacokinetics into a defensible human dose projection — the arithmetic that decides whether a compound can reach its target concentration safely. Use this skill for non-compartmental analysis of a concentration-time profile (AUC, Cmax, terminal half-life, clearance, volume of distribution), one- and two-compartment simulation of a dosing regimen, interspecies allometric scaling, human-equivalent dose conversion by body surface area, and the exposure margin between a projected therapeutic concentration and a toxicology no-effect level. Also trigger on non-compartmental analysis, AUC, clearance, volume of distribution, allometric scaling, human equivalent dose, first-in-human, NOAEL, therapeutic index, or exposure margin.

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HeartMuLa: Suno-like song generation from lyrics + tags.

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HeartMuLa: Suno-like song generation from lyrics + tags.

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。

Reference skill for Zoom RTMS. Use after routing to a live-media workflow when processing real-time audio, video, chat, transcripts, screen share, or contact-center voice streams.

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Walmart category page scraper: input a walmart.com browse or category URL with optional page number, extract paginated product listings with itemId, url, title, brand, image, price, wasPrice, rating, reviewCount, availability, seller info, fulfillmentBadge, and classType. Use when user mentions walmart category, walmart browse page, walmart category listing, scrape walmart category, walmart department scrape, walmart category URL, browse walmart categories, walmart category products, walmart category page scraper, walmart browse scraper, extract walmart category items, walmart filtered category, walmart subcategory products, walmart browse items, walmart department listing, walmart catalog browse, walmart aisle scraper. Also applies to collecting products from a specific walmart category URL with filters applied (e.g. filtered category URLs copied from the browser), scraping all items from a walmart browse section, category-scoped price monitoring on walmart, and parent category crawling where subcategory URLs are enumerated first.

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Find LinkedIn profiles of a specific team or department at a company. Use when asked to get LinkedIn profiles, find team members, or look up people in a particular team/department/group at a company.

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Detects TAD boundaries from balanced Hi-C contact matrices via the diamond-window insulation score (cooltools insulation) and HiCExplorer hicFindTADs, returning a continuous log2 insulation track, valley-prominence boundary_strength, and Li/Otsu-thresholded is_boundary flags across a list of window sizes. Covers the multi-scale window sweep (sub-TAD to compartment-domain), why the boundary is reproducible but the domain partition is not, cross-condition comparison via differential SCORE not differential partition, and the insulation-vs-compartment orthogonality. Use when calling TADs or domain boundaries, computing insulation scores, choosing a window size, ranking boundary strength, comparing boundaries across conditions, or annotating CTCF-backed boundaries; route domain rendering to hic-visualization and boundary-feature overlap to genome-intervals.

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Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries (delta insulation), and differential loops (diffloop, DiffHiChIP) -- with distance-stratified between-sample normalization, replicate-aware NB-GLM FDR, HiCRep SCC reproducibility gating, and CNV correction for cancer/aneuploid samples. Use when comparing Hi-C between treatment and control, finding differential contacts/compartments/boundaries/loops, normalizing two maps of unequal depth, choosing a replicate-aware test, gating replicates with SCC, or correcting copy-number artifacts before a tumor-vs-normal comparison.

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Generate C/C++ or CUDA code from an AI model (PyTorch, LiteRT) using MATLAB Coder or GPU Coder. Use when the user wants to integrate an AI model into an application with code generation as the end goal — generating MEX, CUDA MEX, static library, dynamic library, or executable — or using the model in Simulink for simulation and code generation. Covers PyTorch ExportedProgram (.pt2) via loadPyTorchExportedProgram and LiteRT (.tflite) via loadLiteRTModel (R2026a+). Keywords: PyTorch, torch, .pt2, ExportedProgram, loadPyTorchExportedProgram, invoke, codegen, MEX, CUDA, GPU, C, C++, deploy, AI model, deep learning model, LiteRT, TFLite, TensorFlow Lite, Simulink, slbuild, PyTorch ExportedProgram block, MATLAB Function block, dlosslib, loadLiteRTModel.

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Produces a copy-ready clause about a company adding people to one specific department in the last 6 months, plus the department-level headcount counts that drive the segment gate. Triggers on "they're hiring", "hiring surge", "growing their sales team", "scaling the team", "headcount growth", "who added SDRs", "companies that just built a marketing team". Outputs hiring_surge_line, a lowercase second-person clause that completes "Noticed <line>."

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Use when a Personal Corp operating loop needs setup, repair, a new department, or task routing: HQ files and agent rules, GitHub issue workflow, corp-* owner map, department repositories, or deciding which repo an issue belongs to. Triggers: "corp doctor", "почини контур", "заведи отдел", "куда положить задачу", "настрой штаб", "проверь операционку". Replaces corp-init, corp-new and task-routing.

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The commit-R protocol — test-driven rewrite of one compartment. Commit, remove the compartment's tests ("R:" commit), rewrite them from a stated hypothesis so production fails on purpose, remove the production files ("R:" commit), then rewrite production and patch or delete the outdated adjacent functions. Use when the operator says "commit R", "commit-R protocol", "remove and rewrite the tests", or asks for a TDD pass that looks for a faster, simpler path to the same outcome.

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Configure Prometheus Alertmanager with routing trees, receivers (Slack, PagerDuty, email), inhibition rules, silences, and notification templates for actionable incident alerting. Use when implementing proactive monitoring with automated incident detection, routing alerts to the appropriate team by severity, reducing alert fatigue through grouping and deduplication, integrating with on-call systems like PagerDuty, or migrating from legacy alerting to Prometheus-based alerting.

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