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cccskills

「forecast」の検索結果

316 件 ・ 関連度順

概要と使いどころ

Comprehensive data science workflow skill for analyzing tabular and time series data. Use when conducting exploratory data analysis, building predictive models, performing feature engineering, or generating data-driven insights. Supports end-to-end analysis from data understanding through model deployment, following industry best practices for regression, classification, time series forecasting, and statistical 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。

takusaotome/claude-skills-library92026年10月5日 更新

Econometrics skill for time series analysis. Activates when the user asks about: "time series", "stationarity", "unit root test", "ADF test", "KPSS test", "ARIMA", "ARMA", "autocorrelation", "ACF", "PACF", "VAR model", "VECM", "Granger causality", "cointegration", "impulse response function", "forecast", "seasonal decomposition", "ARCH", "GARCH", "时间序列", "平稳性检验", "单位根", "自回归", "格兰杰因果", "协整", "脉冲响应", "预测", "向量自回归"

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。

zhouziyue233/great-econometrics82026年4月17日 更新

Knowledge base from the NIST/SEMATECH e-Handbook of Statistical Methods (NIST HB 151) — the practical statistics reference for engineering, metrology, and quality. Use for: exploratory data analysis and the four univariate assumptions (4-plot); measurement process characterization including bias/precision, calibration designs, gauge R&R, and ISO/GUM uncertainty budgets; production process characterization (stability vs. capability); process modeling and regression (LS/WLS/NLS/LOESS); design of experiments (screening, fractional/factorial, response-surface, Taguchi); statistical process control (Shewhart/CUSUM/EWMA charts, capability indices, acceptance sampling); product/process comparisons (hypothesis tests and confidence intervals for 1/2/3+ groups, ANOVA, multiple comparisons); and reliability (lifetime & repair-rate models, accelerated testing, reliability growth). Scope limits: this is applied frequentist statistics for measurement and quality — it does NOT reproduce the per-distribution formula galleries, worked case studies, datasets, plot images, or Dataplot/R code of the original web Handbook (those are described, not copied); it is thin on modern machine learning, Bayesian methods beyond conjugate reliability priors, time-series/forecasting, and Bayesian experimental 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。

jgsystemsconsulting/jgs-se-knowledge-packs82026年10月9日 更新

Knowledge base from the NASA Schedule Management Handbook (2024 edition, Revision 2). Use for program/project schedule management of aerospace and large engineering efforts: the five sub-functions (Planning, Development, Assessment & Analysis, Maintenance & Control, Documentation & Communication); the Integrated Master Schedule (IMS) and the WBS/OBS/CBS breakdown structures; the Schedule Management Plan (SMP) and Basis of Estimate (BoE); Critical Path Method, logic, durations, float and margin; tiered schedule assessment (Requirements/Health/Basis checks, the Shock Test) and the Dimensions of Schedule Reliability; Schedule Risk Analysis (SRA), Integrated Cost-Schedule Risk Analysis (ICSRA), Monte Carlo, correlation, merge bias, and the Joint Confidence Level (JCL); baselining, replan vs. rebaseline, EVM schedule metrics (SPI, BEI, CEI, HMI, Earned Schedule, CPLI), and status/progress/forecast reporting. This is NASA's scheduling doctrine grounded in NPR 7120.5 and the GAO Schedule Assessment Guide. Thin on the underlying mechanics of CPM, statistics, and EVM (it points to companion handbooks); aerospace/space-flight-centric; anchored to the 2024 second edition.

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。

jgsystemsconsulting/jgs-se-knowledge-packs82026年10月9日 更新

wetter

無料

Answers weather questions for a location or coordinates via wttr.in (free, no API key). Current weather + 3-day forecast. Location comes from the user request or preferences; optional short cache.

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。

ellmos-ai/skills82026年10月12日 更新

Reviews a proposal, business case, deck or plan in character as a Chief Business Officer archetype, covering commercial model, partnerships, deal structure, market positioning, strategic fit and opportunity cost, and returns a DRAFT review with a verdict, findings that cite the exact passage, commercial risks and five interrogation questions. Use when the user asks to "run a CBO review", "pressure-test this partnership", "check the deal structure" or "what would a commercial executive say about this". Do not use for pipeline, quota, sales-motion or forecast reviews, use cro-reviewer instead. Drafts for human review; never approves, authorises or signs off.

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。

kesslernity/awesome-copilot-agent-skills82026年9月19日 更新

Reviews a proposal, business case, deck or plan in character as an Investor archetype and returns a DRAFT review in the chat with a verdict whose conditions read as terms, findings that cite the exact passage, capital-allocation risks, what would change the verdict and five interrogation questions. Use when the user asks to "run an investor review", "what would an investor say about this", "pressure-test the capital case" or "prepare me for the investment committee". Do not use for internal budget, cost or finance-function review, use cfo-reviewer instead; for revenue forecast and pipeline, use cro-reviewer. Drafts for human review; never approves, authorises or signs off.

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。

kesslernity/awesome-copilot-agent-skills82026年9月19日 更新

Use when working with Apptio — apptio and Cloudability IT financial management and cloud cost optimization. Covers IT cost allocation, cloud cost analysis, benchmarking, budget forecasting, showback/chargeback reports, and technology business management. Use when managing IT financial planning, benchmarking cloud spend, or creating chargeback 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。

cloudthinker-ai/CloudSkills62026年4月5日 更新

Use when working with Aws Billing — analyze, break down, and report AWS costs and bills. Covers cost breakdown by service, account, or usage type; monthly/daily billing trends; cost anomaly detection; RI/SP utilization; cost forecasting; credit/discount analysis; and multi-account cost comparison. Uses anti-hallucination rules, mandatory currency/credit detection workflow, and reusable Cost Explorer functions.

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。

cloudthinker-ai/CloudSkills62026年4月5日 更新

Use for health trend, anomaly, disk forecast

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。

openamer/openamer62026年10月13日 更新

FutureSearch: Search the Future — AI forecasting with a public track record. First in Metaculus's Summer 2026 FutureEval tournament, above the superfo

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。

openamer/openamer62026年10月13日 更新

energykit

無料

Query grid electricity forecasts and submit load events using EnergyKit to help users optimize home electricity usage. Use when building smart home apps, EV charger controls, HVAC scheduling, or energy management dashboards that guide users to use power during cleaner or cheaper grid periods.

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。

JordanCoin/ios-skills-collection62026年9月10日 更新

Financial analyst agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Ratio analysis, DCF valuation, budget variance, rolling forecasts. 4 Python tools (stdlib-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。

micsapp/micstec-skills42026年3月20日 更新

aeon

無料

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

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。

huang-sh/DeepScience42026年7月15日 更新

Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate skills.

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。

peacezha/TRACE32026年10月11日 更新

Comprehensive dimension analysis and reporting for CJA. Use this skill whenever the user wants to analyze one or more dimensions — including cardinality, distribution/skew, trends, anomalies, data quality errors, comparisons, and forecasting. Also trigger when someone asks "what are the top values for...", "dimension health", "explore this dimension", "dimension dashboard", "dimension statistics", "data quality check on a dimension", "dimension cardinality", "dimension trends", "dimension skew", "dimension anomalies", "compare dimensions", or any similar request to understand what's inside a CJA dimension. Produces an interactive HTML dashboard or a markdown report. Works with the CJA MCP server.

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。

OCIOStateOfNebraska/stateofnebraska-aem32026年10月9日 更新

Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors are separate skills.

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。

peacezha/HPClaw32026年10月11日 更新

Use when a carrier owner, CFO, or controller asks how to build an annual budget, monthly P&L model, cash flow forecast, scenario plan, or break-even analysis for a trucking operation. Covers revenue modeling, cost structures, capital planning, and the discipline of tracking actuals vs budget.

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。

x3allamerican/skills32026年5月17日 更新

weather

無料

Get current weather and forecasts (no API key required).

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。

ibragimov-oasis/vibe-coder22026年6月24日 更新

Expert sales execution covering pipeline management, discovery, demos, negotiation, and deal closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.

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。

aAAaqwq/openclaw-team22026年6月18日 更新

Track deals through every stage from lead to close. Manage pipeline stages, update deal status, forecast revenue, and identify bottlenecks in your sales process.

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。

aAAaqwq/openclaw-team22026年6月18日 更新

World-class autonomous sales and revenue skill system. Use ANY time the user asks to sell, pitch, prospect, close, negotiate, launch, monetize, build funnels, write outreach, craft proposals, develop pricing, design offers, write sales copy, create email sequences, plan campaigns, position products, handle objections, create playbooks, build pipeline, forecast revenue, develop GTM strategy, optimize conversions, write ad copy, create sales decks, score leads, nurture prospects, upsell, cross-sell, retain customers, write case studies, price products, structure enterprise deals, create battle cards, script discovery calls, build affiliate programs, plan product launches, create webinar funnels, design pricing pages, A/B test offers, analyze unit economics, calculate LTV/CAC, or ANY other sales, revenue, monetization, go-to-market, or commercial growth task. If it involves selling, revenue, deals, pipeline, or commercial strategy — USE THIS SKILL. Trigger aggressively.

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。

aAAaqwq/openclaw-team22026年6月18日 更新

Comprehensive dimension analysis and reporting for CJA. Use this skill whenever the user wants to analyze one or more dimensions — including cardinality, distribution/skew, trends, anomalies, data quality errors, comparisons, and forecasting. Also trigger when someone asks "what are the top values for...", "dimension health", "explore this dimension", "dimension dashboard", "dimension statistics", "data quality check on a dimension", "dimension cardinality", "dimension trends", "dimension skew", "dimension anomalies", "compare dimensions", or any similar request to understand what's inside a CJA dimension. Produces an interactive HTML dashboard or a markdown report. Works with the CJA MCP server.

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。

aemgdc/aemdev22026年10月13日 更新

Estimates infrastructure needs based on traffic forecasts, workload analysis, and performance requirements with sizing recommendations and cost trade-offs. Use for "capacity planning", "infrastructure sizing", "resource estimation", or "scalability planning".

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。

sathishssj3/Stereix-Engine22026年10月4日 更新