「value」の検索結果

Compute and analyze gematria (Hebrew numerical values) using standard, ordinal, and reduced methods. Covers word-to-number conversion, isopsephy comparisons, and interpretive frameworks. Use when computing the numerical value of a Hebrew word or phrase, comparing two words for shared gematria values, studying a biblical verse or divine name for numerical correspondences, or connecting a numerical result to its position on the Tree of Life.

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。

Design value propositions for candidate customer segments and help the user choose the strongest one. Use when Codex needs to explain jobs, pains, and gains when needed, check niche-positioning prerequisites, ask one question at a time, present multiple value-proposition options, and write user-confirmed outputs into `opc-doc/`.

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。

"Apply the Fama-French three-factor model to decompose asset returns into market, size, and value factors. Use this skill when the user needs to explain cross-sectional return differences, evaluate fund performance beyond CAPM alpha, assess small-cap or value tilts in a portfolio, or when they ask 'why do small caps earn more', 'is value premium real', or 'what factors drive returns'.".

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。

"Apply real options analysis to value managerial flexibility embedded in investment decisions. Use this skill when the user needs to evaluate projects with significant uncertainty and flexibility, assess the value of deferring or expanding investments, compare traditional NPV with expanded NPV, or when they ask 'should we wait to invest', 'what is the option to abandon worth', or 'why does NPV undervalue this project'.".

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。

"Apply Porter's Value Chain Analysis to identify competitive advantage sources within an organization's activities. Use this skill when the user needs to find where value is created or lost in their operations, analyze cost structure by activity, optimize internal processes, or identify outsourcing candidates — even if they say 'where do we make money' or 'which activities should we keep in-house'.".

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。

Builds and audits a concept-ontology for a regelrecht corpus to decide and verify reference types — cross-law source-binding vs intra-law source-binding vs open-norm leaf vs external-fact leaf — and to catch concept conflation across laws. Core principle: a value's reference type is fixed by WHO derives it, and a binding is sound only when producer and consumer denote the SAME concept; the lexical surface (the word in the text) is not the concept. Detects false friends (one term, different concepts — e.g. a register-based vs a factual "naar de omstandigheden"-based residence/ingezetene concept), orphan plain-params (a value a regulation actually derives, modeled as a brute input), negation/complement re-entry (¬X modeled as an independent leaf next to X), and duplication (one concept re-entered as several independent leafs, losing the single-source-of-truth invariant). Produces a law-level glossary and a stelsel-level concept map with sound same-concept binding edges and flagged lexical-match-but-concept-mismatch edges. Use when deciding whether a value should be cross-law/intra-law/leaf, when the same term means different things across laws, or when a binding might silently conflate concepts.

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 visuals that sell a specific offer and value proposition. Translates an offer (price, bundle, guarantee, bonus, deadline) into hero visuals that make the value legible at a glance. Use when the user says "visualize the offer", "promo creative", "make the deal look good", "value prop hero", or has a concrete offer to merchandise. Part of the Creative Production set.

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。

Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.

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 should be used when the user asks to "scrub JSON values", "mask config fields", "add a Git clean filter", "remove volatile values from tracked config", or "stop config churn".

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 or change immutable business values with meaningful invariants, equality, or behavior, such as order numbers and money. Use when primitive values obscure domain rules; avoid wrapping every scalar.

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。

Value Metrics（価値概念・インパクト評価・スコア乖離検証）の観点を説明する

Register a custom Dynamic Visibility condition for JetEngine — extend \Jet_Engine\Modules\Dynamic_Visibility\Conditions\ Base, hook jet-engine/modules/dynamic-visibility/conditions/register, call $manager->register_condition( new MyCondition() ). The 3 abstract methods are get_id() / get_name() / check( $args = [] ); override get_group() to assign a UI group, is_for_fields() / need_value_detect() / need_type_detect() to control where the condition appears, get_custom_controls() to add per-condition UI controls. The check() $args includes type ('show' or 'hide'), field / field_raw, value, data_type ('chars' / 'numeric' / 'datetime' / 'date' / 'list'), and context ('default' or 'current_listing'). Important — $args['type'] is the user's show/hide intent; condition must invert its boolean accordingly. Use get_current_value() helper for context-aware meta resolution (handles WP_Post, WP_User, WP_Term, WP_Comment, listing macros). Use when scaffolding a JetEngine companion plugin's visib...

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 design, construct, or improve an offer — the thing they actually sell — including value framing, bonus stacking, guarantee design, scarcity/urgency, naming, and payment structure. Also use when the user mentions 'offer,' 'offer design,' 'build an offer,' 'grand slam offer,' 'irresistible offer,' 'value stack,' 'bonus stack,' 'guarantee,' 'risk reversal,' 'money-back guarantee,' 'scarcity,' 'urgency,' 'high-ticket offer,' 'productize a service,' 'naming an offer,' 'payment plan,' 'down-sell,' 'upsell offer,' or 'why isn't my offer converting.' Best for services, agencies, courses, coaching, info products, high-ticket B2B, and direct-response. If you run pure self-serve SaaS, read pricing first — tiers and packaging do more work there. For price level itself (tiers, freemium, value metric), see pricing. For the page that presents the offer, see copywriting. For the launch moment, see launch. For sales collateral, see sales-enablement.

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。

Analyze an optional company talent, values, culture, or recruitment page and turn it into cover letter positioning guidance. Use when the user provides a company values URL/text, asks to match a cover letter to company culture, or wants talent-profile keywords connected to resume.md evidence. 한국어 요청도 포함합니다 - 인재상 분석, 기업 가치관, 회사 문화, 채용 홈페이지 분석, 기업 분석, 인재상에 맞춰서, 회사가 원하는 인재.

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。

Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.

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。

Map a thesis's position in its value chain — who it buys from, sells to, and competes with; where the bottleneck and pricing power sit; and whether it owns a critical layer. Use when user says "value chain", "supply chain position", "where does [TICKER] sit", or "who are [TICKER]'s suppliers/customers".

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。

Estimate calcium-normalized Gapon selectivity coefficients from paired exchange and solution chemistry, or initialize depth-explicit EcoSIM Gapon inputs from the closest bundled ecosystem template when paired chemistry is unavailable. Use when deriving or checking EcoSIM GKC4, GKCH, GKCA, GKCM, GKCN, or GKCK values; matching a target ecosystem, climate, vegetation, and management regime to a starting profile; remapping template values to target soil layers; or documenting that template-based values require calibration or tuning.

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。

Pick the right business-model canvas (Lean Canvas, Business Model Canvas, or Value Proposition Canvas) for the stage and fill it with specifics — one segment, one primary canvas, top-3 assumptions, no fluff in the moat or channel boxes. Load when the user asks to fill a business model canvas, lean canvas, value proposition canvas, model this business, map the business model, says "fill the BMC", "make a Lean Canvas", "Value Proposition Canvas for this", "model this idea", "what's the business model", "design the business model". Sub-skill of `venture-exploration`. Hard-bans "everyone" segments, generic channels ("SEO/social/content/ads"), and "unfair advantage = AI/data/network effects" with no concrete asset. Does NOT score viability — for that use `idea-evaluation`.

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。

Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.

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。

Find and identify the CBaseEntity_SpawnRadius function in the CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the radius-aware spawn helper that resolves an entity's effect/trigger radius from either its float argument or the "radius" keyvalue, then applies it and reads the entity's "hammerUniqueId" keyvalue. Resolved via the two econ/ hammer keyvalue literals "radius" and "hammerUniqueId": the single function that references BOTH is the target. Trigger: CBaseEntity_SpawnRadius, SpawnRadius

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。

Improve test value and feedback cost when auditing slow, flaky, redundant or brittle tests; choosing tests during implementation; or reviewing test changes before a commit or PR. Keep ordinary implementation and pre-commit use scoped to the affected behavior, not a repository-wide audit.

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 this skill when building analytics dashboards with nuxt-ui-tools as a package consumer. Covers schema and view functions (defineDashboardSchema, defineDashboardView) that take their context as typed params, useDashboard with a getter that rebuilds on input change, typed injection (useDashboardView, injectDashboard, InferDashboard, InferDashboardView), filters declared inline with the f builder and synced with the URL, memory, or an external store (one value per key across views), headless filters, filter controls and the shipped UI (UiDashboardPage, UiDashboardFilters, UiDashboardFilter, UiDashboardViewTabs) with slot overrides, remote paginated pickers and remoteTableOptions, staged queries (essential / background / deferred) with select and dependent requires, lazy enabled conditions on views, queries, and filters (blocks of disabled queries hidden, grids closing up), derived values, views (tabs), query-scoped filters, number formats (presets, Intl options, useDashboardFormat), and the dashboard blocks (stats with trends, goals, and comparisons, stat groups, gauges, unovis charts with highlights, value labels, and totals, lists with progress rings, bars, funnel, alerts, activity feeds, sortable tables, custom widgets) with their automatic loading, error, empty, and refresh states, card menus, header and footer actions, row actions, drill-down and selected state, card tabs, split cards, comparison periods, auto-refresh, and data freshness.

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。

XとLinkedInのつながりから、会いたい相手への紹介経路を評価するスキル。経路の近さや関係の強さを重み付けし、紹介を頼む候補と接点の不足を整理します。

• 対象者を紹介できる知人探し
• 共通の知人を紹介価値で順位付け
• 対象企業への紹介経路を調べたいとき

複数のEVMチェーンでトークン残高や価格の桁がずれる問題を防ぐため、小数桁数の実行時取得、チェーン別キャッシュ、精度を保つ計算と単位統一を扱うスキル。

• トークン残高の桁ずれを調べたいとき
• 複数EVMチェーンの数量比較
• ブリッジ後の小数桁数の確認