「rtm」の検索結果

[omh] Business question on market, competitors, pricing: business research brief - turns a market, competitor, pricing, or customer question into a structured evidence-vs-inference brief; for raw link gathering use ulw-research, and for ongoing multi-role research use research-department. Use when the user says: research-brief, business-research, business research, research brief, decision brief, pricing decision brief, decision-ready brief, source-backed business research.

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。

Runs the planning cycle — annual budget, rolling forecast, consolidation of business unit inputs, and the variance analysis that explains actuals against plan. Use this to build or challenge a budget, run a forecast cycle, consolidate departmental submissions, explain why results diverged from plan, or improve forecast accuracy.

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 medical referral letters with patient summary, reason for referral, key findings, and requested next steps; use when transferring care or communicating with another clinician or department.

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。

Gregor Mendel — genetics mentor, patient experimenter, and gardener-monk. Trigger this skill when users ask about genetics, heredity, inheritance patterns, Mendelian laws, dominant/recessive traits, gene segregation, independent assortment, Punnett squares, classical genetics, or evolution-genetics connections. Also trigger when discussing the philosophy of science, how great ideas get ignored, the relationship between faith and science, or the virtue of patient long-term observation. Even if the user doesn't say "Mendel" explicitly, trigger this skill for questions touching genetics, breeding, trait inheritance, or genomics history. Part of the AIPOCH Science Mentor Skill Hub.

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。

Read-only Ramp corporate spend: transactions, cards and card limits, users, departments. No spend actions by design. Trigger phrases: ramp, corporate spend, expense transactions, card spend limits.

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。

Balances Hi-C contact matrices (ICE via cooler.balance_cooler, KR/SCALE/VC context), computes distance-decay expected with cooltools (expected_cis per-diagonal P(s), expected_trans scalar), builds observed/expected (O/E) matrices, and diagnoses polymer state from the P(s) log-derivative. Covers the within-matrix-vs-cross-sample distinction (balancing is NOT a normalizer), the equal-visibility assumption that CNV/aneuploidy violates (use raw counts for copy-number), cis-only balancing, mad_max/blacklist masking before balancing, multiplicative cooler weights vs divisive juicer weights, and the resolution-vs-depth budget. Use when balancing a .cool/.mcool, computing expected or P(s), making O/E matrices for compartments/loops, deciding ICE vs KR vs SCALE, choosing a resolution for a given depth, or troubleshooting NaN/all-NaN balanced matrices; route cross-sample comparison to hic-differential.

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。

Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two 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。

Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

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 comparing process cohorts, departments, periods or before-and-after results under matched definitions.

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 real estate, architecture, and interior design showcase video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants property tours, real estate listings, architecture showcases, interior design videos, home staging content, property marketing, virtual tours, construction reveals, or any real estate/architecture video. Triggers on: real estate, property, house, apartment, architecture, interior design, home tour, listing video, property marketing, virtual tour, building, construction, renovation, home staging, or any real estate/architecture video request. Use even for "make a video for my listing" or "showcase this property.

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。

Build customer journey maps and service blueprints that visualize the end-to-end user experience including touchpoints, emotions, friction, and underlying systems. Use this skill whenever the user wants to map a customer journey, build a service blueprint, identify friction across an experience, align teams on the user experience, or visualize touchpoints and pain points. Triggers on customer journey, journey map, service blueprint, user journey, experience map, touchpoint analysis, friction map, journey audit, end-to-end experience, customer experience map. Also triggers when the team has departmental views of users but no shared map of what the experience actually feels like.

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。

Release coordination across departments

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。

Create agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Paperclip.

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。

Cascades strategy from boardroom to individual contributor and detects misalignment. Use when teams pull in different directions, OKRs don't connect, departments optimize locally at company expense, or strategy doesn't translate to execution.

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。

C-suite orchestration that routes founder questions to the right advisor role(s) and runs multi-role board meetings. Use when coordinating executive decisions, routing strategic questions, or resolving cross-department conflicts.

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。

Reviews outside counsel invoices and related billing data for an in-house legal department, including LEDES or e-billing exports, OCGs, approved rates, discounts, budgets, AFAs, and staffing rules. Starts with internal comparisons before bringing in external data. Produces invoice review findings, MBR/QBR scorecards, dispute logs, and management reports. For demonstration purposes only and not professional advice.

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 complete marketing department in one skill. Website and landing-page audits with weighted 0-100 scores, copywriting with panel scoring and AI-slop removal, an 18-tactic ad hook engine, GEO/AEO for getting cited by ChatGPT/Perplexity/AI Overviews, paid-ads creative diagnosis and production briefs, email sequences, LinkedIn/X writing, launch playbooks, positioning and offer design, competitor teardowns, app store optimization, honest analytics and test design. Use for ANY marketing task — audit, write, rewrite, diagnose, score, plan, launch, position, price, analyze — whenever the user mentions marketing, growth, conversion, copy, ads, hooks, CPM, ROAS, SEO, GEO, email, social, landing pages, funnels, launches, competitors, brand, positioning, pricing, or app stores, or says "my landing page sucks", "nobody's converting", "why are my CPMs up", "AI doesn't recommend us", "write me 20 hooks". Route via the table inside; fan out subagents for multi-dimensional work. Not for pure engineering, legal, or finance.

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 guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.

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。

Build or modernize an employee handbook for a small business with no HR department -- interviews the owner for actual practices, drafts every core policy in plain English, flags the state-specific requirements that need local verification, and outputs a document employees might actually read.

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。

Announcement board: author, category, department, priority, audience, publish and expiry dates, status and acknowledgements, as CSV, SQL, JSON Schema or Notion on request. Use for internal notices.

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。

Guides assessment and use of the EU-US Data Privacy Framework adequacy decision for transatlantic data transfers. Covers DPF self-certification with the Department of Commerce, DPF principles compliance, Data Protection Review Court, and annual EC review. Keywords: DPF, EU-US, adequacy, Privacy Shield, transatlantic transfers.

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。

Athenahealth integration. Manage Patients, Appointments, Providers, Practices, Departments, Claims. Use when the user wants to interact with Athenahealth data.

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。

Fix cert-manager DNS01 ACME challenges stuck in "pending" state with "DNS record not yet propagated" inside GKE private clusters, even when TXT records exist in Cloudflare DNS. Use when: (1) cert-manager challenges show "pending" for hours with propagation check failures, (2) dig from outside cluster shows correct TXT records but cert-manager can't verify them, (3) Using Cloudflare DNS01 solver in a GKE private cluster with Cloud NAT, (4) Google Cloud intercepts 8.8.8.8 DNS queries returning NXDOMAIN for Cloudflare-managed records, (5) Even --dns01-recursive-nameservers with 1.1.1.1 doesn't fix the propagation check despite TXT records being verifiable from busybox pods in the same namespace. Covers the full debugging flow and certbot manual workaround.

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。

JeecgBoot 系统主数据查询与管理。Use when user asks to query/create/manage system master data, or says "查询角色", "查询用户", "查询部门", "查询字典", "创建字典", "创建角色", "查岗位", "查职务", "查租户", "查数据源", "查定时任务", "系统主数据", "query roles", "query users", "query depts", "create dict", "create role", "master data". Also triggers when other skills (desform, bpmn, codegen) need to look up or create roles, users, departments, dictionaries, or positions as dependencies — follows "先查后建" (query-first-create-later) principle.

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。