3,925 件 ・ 関連度順
概要と使いどころ
Predict construction project costs using Machine Learning. Use Linear Regression, K-Nearest Neighbors, and Random Forest models on historical project data. Train, evaluate, and deploy cost prediction 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。
Assess organization's digital transformation readiness. Evaluate data culture, technology adoption, and process maturity.
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 ML models for construction predictions. Train and evaluate custom models for cost, duration, and risk prediction.
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 contractor bids against CWICR benchmarks. Identify pricing anomalies, compare bid components, and support bid evaluation decisions.
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 and compare subcontractor bids against CWICR benchmarks. Evaluate pricing, identify outliers, and support negotiation.
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。
Building energy simulation and analysis for construction. Calculate heating/cooling loads, evaluate envelope performance, optimize HVAC sizing, and ensure energy code compliance.
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 roster fit and personality dynamics. Leadership assessment, role clarity, locker room culture, trade/signing impact.
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 spreads, over/unders, prop bets. Historical trends, situational stats, value bet identification. For entertainment/education only.
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。
Pulls financial statement numbers for US public companies straight from SEC EDGAR's free official XBRL APIs (companyfacts, companyconcept, frames, submissions) into a cited table. Every value carries its accession number, form, fiscal period, filed date, XBRL tag and a link to the filing, and the tool handles fiscal-year ends, quarterly vs YTD vs TTM, derived Q4, restatements and units. Use this whenever the user wants 10-K numbers or 10-Q numbers, says "pull financials for", asks for public company revenue, net income, EPS, cash, debt or capex, wants comps or a competitor side-by-side, a credit check, prospect research, or model inputs, or mentions SEC filings or EDGAR, even if they never say XBRL. Free and primary-source, no paid data terminal needed. Do not use it for private companies, stock prices or valuation multiples.
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。
Multi-dimensional rep evaluation: activity, conversion, velocity, deal size. Peer benchmarking and coaching priority identification.
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。
Calculate comprehensive ROI for AI implementation projects. Takes current costs, manual process time, team size, and hourly rates. Generates detailed roi-analysis.md with executive summary, cost-benefit tables, sensitivity analysis, break-even timeline, and comparison scenarios. Use when evaluating AI investments, building business cases, or justifying automation spend.
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。
Evaluates which SaaS tools can be replaced with AI agents. Takes a list of current SaaS subscriptions with costs, assesses replacement feasibility, estimates build vs buy economics, identifies Claude+MCP alternatives, and generates a comprehensive replacement plan with priority matrix, ROI analysis, implementation timeline, and risk assessment.
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 pitch decks and investor presentations. Reads slide content, evaluates narrative flow, problem/solution clarity, market sizing, competitive positioning, financial projections, team credibility, and ask clarity. Generates a scored pitch-review.md with slide-by-slide feedback, overall score, top improvements, investor objection predictions, and comparisons to successful decks. Use when reviewing fundraising materials, investor decks, or pitch presentations.
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 structured hiring scorecards for any role. Takes job title, requirements, and team context. Generates comprehensive scorecard with weighted scoring rubric, interview questions per competency, evaluation matrix, red/green flags, and reference check questions.
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。
Writes, explains, debugs, and optimizes BI calculations - Power BI / Fabric DAX measures and calculated columns, Tableau calculated fields (FIXED/INCLUDE/EXCLUDE LOD expressions, table calculations), and Looker LookML measures, dimensions, and derived tables. Use it whenever the request involves DAX, CALCULATE, a Power BI measure, a Tableau calc or LOD, LookML, or a business metric such as YoY, YTD, rolling 12 months, running total, percent of total, distinct customers, ranking, new vs returning customers, closing balances, or basket analysis. Use it especially when someone says a measure "shows the wrong total", "is blank", "ignores my slicer/filter", "repeats the same value on every row", or "is slow" - those are filter context, context transition, LOD order-of-operations, or fanout bugs this skill is built to diagnose. Produces the formula, the context it evaluates in, and a hand-checkable test with expected numbers.
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。
Assesses how ready a business is for AI adoption across six dimensions. Evaluates data maturity, tech stack, team skills, process documentation, budget, and culture. Generates a comprehensive ai-readiness-report.md with scores, gap analysis, and recommended starting points. Aligned with OneWave AI's audit methodology.
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 contracts for concerning clauses, extract key terms, compare to standard terms, and flag unusual provisions. Use when user needs contract review, legal document analysis, or agreement 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。
Analyze LinkedIn profiles in target accounts to identify potential internal champions. Evaluates role, career path, mutual connections, interests, and suggests personalization approach. Use when you need to find who will champion your solution internally.
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。
Continue the current local Codex conversation and coding task in an AgentKit Studio cloud Codex Sandbox using a Studio URL and short one-time pairing code. Use when the user asks to hand off, migrate, or continue a local repository in Studio, especially when a prompt contains a Studio address and pairing code. Export the complete user-visible user and assistant message history from every prior turn, including interrupted turns and progress commentary, create a temporary Studio Sandbox, restore tracked and non-ignored working-tree files plus Git metadata, inject that visible history into the cloud Thread, transfer GitHub CLI authentication separately when needed, and send one final continuation message; never copy system or developer prompts, reasoning, tool logs, SQLite state, global configuration, local skills, or SSH private keys.
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。
Drive the agentkit CLI (aliases agentkit / ak) to scaffold, build, deploy, and manage agents on Volcengine AgentKit from the terminal — runtimes, knowledge bases, memory collections, tools, harnesses, invocation, SSO auth, sandboxes, and evaluation datasets. Use when a user wants to create/deploy an agent project, call or inspect a deployed runtime, manage AgentKit resources, or resolve a CLI/auth/deploy error. Does NOT handle non-AgentKit deployment, general Docker/k8s operations, Volcengine IAM management, or writing agent application code (use veadk-agent-development for that).
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。
Evaluate technical options with scoring matrix, trigger Gate 4 for significant decisions
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。
API reference: Swift Concurrency. async/await, Task, TaskGroup, actors, AsyncSequence, AsyncStream, continuations.
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。
Provisions the oracle ML inference daemon with onnxruntime via uv. Use when setting up local ONNX model inference for skill quality 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。
Evaluates and improves skills, agents, commands, and hooks after a workflow slice. Use when execution felt slow, confusing, repetitive, or fragile.
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。