「scale」の検索結果

当用户需要评估某项投资、收购标的、商业机会或重大资源投入是否"值得"时调用。典型触发信号:涉及"内在价值""安全边际""护城河""定价权""买还是不买"等决策。不适用于纯心理学偏差分析(用 misjudgment-checklist)或规模效应判断(用 scale-advantage-analysis)。

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。

当用户需要分析企业/组织/产品的竞争格局、评估"做大"是否真的更好、判断某公司的护城河来源是否可持续时调用。典型触发信号：涉及"规模经济""市场占有率""大企业的困境""先发优势""网络效应""赢家通吃"等话题。不适用于纯财务分析(用 value-assessment)或纯心理偏差检查(用 misjudgment-checklist)。

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。

Ultra-granular code analysis for deep architectural context building. Line-by-line and block-by-block analysis using First Principles, 5 Whys, 5 Hows methodology at micro scale. Builds mental models, tracks invariants and assumptions, and maps cross-function call flows for security audit preparation.

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。

Clarify priority and emphasis by fixing unclear primary actions, competing visual weight, loud section titles, and weak label/value treatment. Use when the user mentions hierarchy, prioritization, too much competition, grayscale confusion, loud headings, or unclear primary actions.

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。

Web terminal server: manage the wterm-server daemon for browser-based shell access (local or remote via Tailscale). This skill should be used when checking wterm status, listing or creating terminal sessions, killing sessions, or managing the wterm LaunchAgent. Trigger on: wterm, web terminal, remote terminal, remote shell, browser terminal, terminal sessions.

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。

Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski rule of five, Veber, Oprea, CNS, lead-like, rule of three), structural alert catalogs (PAINS a/b/c, NIBR screening-deck severity, Brenk, BMS, Glaxo, Dundee, ChEMBL common alerts), ZINC-15 percentile complexity metrics (Bertz, SAscore, QED, Whitlock, Barone), chemical-group detection, Lilly demerits, and the medchem query language (MATCHRULE, HASALERT, HASPROP, HASGROUP) for filtering a library at scale. Also trigger on medchem, `import medchem as mc`, RuleFilters, NIBRFilters, CommonAlertsFilters, NamedCatalogs, QueryFilter, PAINS filtering, or structural alerts.

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。

Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological relationships across genes and proteins, drugs, diseases, phenotypes, pathways, biological processes, exposures and anatomy. Use this skill to search entities by name, pull direct neighbours and their evidence types, summarise the local network around a disease, and find direct or two-hop drug-disease connections for repurposing hypotheses. Also trigger on PrimeKG, kg.csv, Harvard Dataverse knowledge graph, disease_protein, drug_protein, indication and contraindication edges, or network pharmacology over a biomedical knowledge graph.

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。

Navigate make-on-demand catalogues — ZINC-22 through CartBlanche and Enamine REAL Space — to find compounds that can actually be ordered. Use this skill to look substances up by ZINC identifier or structure, understand tranche partitioning by heavy-atom count and logP, and choose between screening an enumerated subset and searching a combinatorial synthon space with a fragment-growing method such as V-SYNTHES. Also trigger on ZINC22, CartBlanche, Enamine REAL, make-on-demand, tangible library, synthon, tranche, giga-scale enumeration, or ultra-large virtual screening.

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 the user is deciding, reviewing, or second-guessing a software architecture or tech-stack choice — monolith vs microservices vs serverless vs event-driven, backend language, database type, caching, CQRS/event sourcing, polyglot, or a migration like Strangler Fig. Triggers on "should I use microservices", "which database", "tech stack for", "system design", or "architecture review". For how to deploy, operate, and scale that design (CI/CD, cloud, Kubernetes, IaC), use devops.

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 the user needs to deploy, operate, secure, or scale running infrastructure — cloud architecture (multi-region, VPC, FinOps), CI/CD and deployment strategies, secrets/IAM/supply-chain security, observability and SLO alerting, SRE and incident response, Kubernetes vs ECS and autoscaling, Terraform/Pulumi/CDK, or platform engineering and DORA metrics. Also for generating runbooks, pipeline configs, Terraform modules, or Kubernetes manifests. For choosing the system's architecture or stack before it runs (monolith vs microservices, which database), use software-architect.

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 a non-designer needs to audit a UI, generate a design spec (spacing, type scale, color tokens, grids), or build brand foundations (logo systems, palette and type pairing, brand guidelines). Covers the visual layer, UX/perceptual critique, and brand identity. For implementing the design in code (React/HTML/CSS), use frontend-design.

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。

Review software architecture for coupling, cohesion, SOLID principles, API design, scalability, and technical debt. Covers system-level evaluation, architecture decision record review, and improvement recommendations. Use when evaluating a proposed architecture before implementation, assessing an existing system for scalability or security, reviewing ADRs, performing a technical debt assessment, or evaluating readiness for significant scale-up.

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。

Restore legibility to an auto-generated graph diagram that has outgrown its canvas - rendering at single-digit percent scale with sub-pixel labels. Covers the levers that measurably reduce layout units (source-level label wrapping, invisible chain links so unconnected nodes stop spreading into one row, per-cluster splitting, layout direction picked by rendering both and measuring) and the rejected ones (raising the render font is a no-op because layout engines measure in text units; a topology heuristic for direction regressed 13 of 38 diagrams). Use when a generated Mermaid/Graphviz/DOT diagram is too small to read; not for hand-authoring a small diagram.

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。

Field identification of minerals and ores using hardness, streak, luster, cleavage, crystal habit, and simple chemical tests. Covers the systematic elimination methodology, Mohs scale application, and common ore indicators for precious metals, gemstones, and industrial minerals. Use when encountering an unknown rock or mineral specimen, when prospecting and assessing whether a site shows valuable mineral indicators, when distinguishing ore-bearing rock from barren rock in the field, or when building geological literacy through systematic observation.

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。

Implement layered collective defense using alarm signaling, role mobilization, and proportional response. Covers threat detection, alert propagation, immune response patterns, escalation tiers, and post-incident recovery for distributed systems and organizations. Use when designing defense-in-depth where no single guardian covers all threats, building incident response that scales with severity, or when current defense is over-reactive to every alert or under-reactive to genuine threats.

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 machine learning models to production serving infrastructure using MLflow, BentoML, or Seldon Core with REST/gRPC endpoints, implement autoscaling, monitoring, and A/B testing capabilities for high-performance model inference at scale. Use when deploying trained models for real-time inference, setting up REST or gRPC prediction APIs, implementing autoscaling for variable load, running A/B tests between model versions, or migrating from batch to real-time inference.

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 asked to audit typography across a codebase. Produces a file:line report with concrete fixes ordered by impact and flags unverifiable rules. Not for building a type system or token scale.

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 a human invokes this skill to build a webhook UI that wakes a bot. Not for unpreviewed or unapproved credential, host, Tailscale, deployment, remote, paid, or irreversible changes.

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 for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.

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。

When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.

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。

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

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。

Score a PhD applicant's profile and rank candidate advisors using a connection-first 4.0-scale scoring system. Best-supported for physics / HEP and materials science (MSE), with the scoring engine extensible to chemistry, biology, CS, math, EE, ChemE, earth science (each with field-specific caveats — see references/journal_tiers.md). Use when the user wants to evaluate their PhD application chances, find matching advisors at top US programs, score a CV for graduate school, or compare candidate professors. Also triggers when the user mentions phdtaketaketake or its connection-first philosophy of valuing advisor network over h-index.

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。

Initialize a local custom Elementor Widget plugin, design handoff workspace, and pending site-style context, choosing a Flat or Grouped plugin structure from expected Widget scale. Use once before the first custom Widget when no plugin scaffold exists; theme context is optional and read-only. Do not map Elementor Site Settings, design visuals, implement Widgets, deploy, or inspect a live WordPress installation.

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 an organic-traffic operating system for any site or app: a multi-phase, resumable engine that plans and ships a BATCH ROADMAP of landing pages (use-cases, playbooks, /for/ pages, roundups) on top of real keyword research, with a persistent phase tracker. Use when the user says 'SEO machine', 'build organic traffic', 'rank on Google', 'we need traffic', 'SEO roadmap', 'batch of pages', 'pages roadmap', or 'build an SEO engine'. Distinct from `seo-audit` (one-off diagnostic) and `seo-content` (single-article writer): this skill owns the multi-page roadmap, run sequencing, page generation, internal linking, and the persistent phase tracker across the whole run. For a single alternatives or vs/comparison page, see /competitor-alternatives; for programmatic SEO templates and content at scale, see /seo-content; for off-page link building, see /off-page-seo. Resumable — every invocation continues the last 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。