「statistics」の検索結果

Display project statistics — phases, plans, requirements, git metrics, and timeline

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。

Calibrate Blender materials, lighting, camera crop, emission/glow, color management, and aura/HUD styling against supplied original/reference images using measurable color, brightness, saturation, bbox, and mask statistics. Use when a product must match the lighting/look of a source image or when audits say the product is too bright, desaturated, wrong hue, wrong glow, or wrong silhouette extent.

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。

GEO (Generative Engine Optimization) 引用追踪 + 优化（2026-06-24 标准）。每周对 4 大 AI（Claude/GPT/Perplexity/Gemini） 跑固定查询，检测回答里是否引用目标域名。对未被引用的页面补 Citable Statistics + AI 友好格式（一句话答+表格+FAQ）。 Bing IndexNow 推送确保大模型快速 discover/index。GA4 AI 来源流量监控。 当用户说"我有没有被 AI 引用"、"GEO 优化"、"llms.txt 更新"、"AI 引用追踪"时调用。 默认 B2B/开源；2C 产品（教育/应用）的查询选题与 Citable Stats 来源不同，见 gingiris-seo-geo/references/2c-adaptation.md。

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。

Act as an end-to-end data scientist: turn business questions into defensible analysis, validated models, and decision-ready reports. Use whenever the user asks to analyze, explore, or profile a dataset or CSV/Parquet/Excel file; asks what drives a metric or why a number changed ("why did churn go up?"); wants to test whether a difference is real (A/B tests, experiments, "is this significant?", "how many samples do I need?"); wants a predictive model (churn, forecast, scoring, segmentation, classification, regression); asks to review an existing analysis, notebook, or model for flaws; or needs results written up for decision-makers. Triggers in any language ("phân tích dữ liệu", "xây model dự đoán", "kiểm định A/B"), even when they never say "data science" or "statistics".

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 users ask about Nexus Mutual claims history, claim statistics, approval/denial rates, payout amounts, or want to analyze past claims for a product or time period.

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。

Add a viewer, configure a viewer, change viewer options, find viewer, close viewer, view a scatter plot, bar chart, histogram, line chart, box plot, pie chart, heat map, correlation plot, 3D scatter, trellis, density plot, statistics, on a Datagrok TableView via the datagrok_exec tool. Use whenever the user asks to plot, chart, visualize, show a graph, draw a distribution, color by a column, swap a viewer's axis, toggle a legend / regression line / log scale, replace one viewer with another, close every chart, reset the view to just the grid, or find an existing viewer by type. Plugin viewers like "Chem space", "sequence space", "activity cliffs" are NOT viewer types — they're registered functions — route those to `grok.functions.call`. Does NOT cover filtering (separate skill `datagrok-filtering`), selection (`datagrok-selection`), grid cell rendering (`datagrok-grid-customization`), layout save/restore, or custom-viewer authoring.

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 working with the non-metallic engineering materials — polymers, ceramics, or composites — and you need to reason about structure, processing, or properties. Covers thermoplastics versus thermosets, chain structure, glass transition, and viscoelasticity in polymers; ionic and covalent bonding, sintering, brittleness, and Weibull statistics in ceramics; and fiber-reinforced laminates, matrix and reinforcement roles, the rule of mixtures, and anisotropy in composites. Reach for it to choose a plastic, understand why a ceramic fails, or predict the stiffness of a laminate.

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。

Look up prior Claude Code sessions when context is lost or forgotten. Use when asked what was done before, what happened in the last session, or any request to recall past conversation history, prior decisions, experiments, or outcomes. Indexes and searches raw JSONL transcripts from ~/.claude/projects/ via DuckDB. Returns verbatim user messages, summarizes AI actions and sub-agent outcomes, detects tool errors and user frustration signals, and reports tool usage statistics. Summaries cached at ~/.claude/kaizen/session-summaries/.

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。

IOTA blockchain MCP server providing wallet management with human-in-the-loop signing, Move smart contract build/test/publish, and on-chain queries via JSON-RPC and GraphQL. Use when interacting with IOTA network from AI coding agents, managing IOTA wallets, building or publishing Move packages, querying on-chain objects or transactions, or checking epoch and network statistics.

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 several language models as independent coders on the same labeling or discovery task and reads their disagreement as data — panel assembly for model diversity, keeping votes independent, consensus rules, agreement statistics (Cohen's and Fleiss kappa, Krippendorff's alpha), the correlated-errors caveat that stops agreement being mistaken for validity, human validation beyond the panel, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, asks how to combine several models' labels, or asks what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.

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。

Manage Alibaba Cloud DNS (Alidns) using the @alicloud/alidns20150109 TypeScript SDK. Use when working with DNS resolution on Alibaba Cloud, including domain management, DNS record CRUD (A, AAAA, CNAME, MX, TXT, SRV, CAA, etc.), DNS load balancing (DNSSLB), custom resolution lines, DNSSEC, domain groups, batch operations, Cloud GTM (Global Traffic Manager), DNS GTM, GTM Classic, recursive DNS, DNS cache, Public DNS (PDNS), DNS over HTTPS (DoH), ISP cache flush, domain statistics, and resource tagging. Covers all 234 APIs of the Alidns 20150109 version.

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。

Get statistics for vector storage. Requires authentication. Use for Agentuity cloud platform operations

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。

Get statistics for keyvalue storage. Requires authentication. Use for Agentuity cloud platform operations

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 performance and manage engagement through Publora. Use when the user asks how a LinkedIn post or account performed (impressions, reach, reactions, comments, reshares, follower growth) or wants to react, comment, reshare or resolve an @mention. Statistics run over the REST API, engagement over MCP tools. Not for creating posts (use linkedin-post).

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。

Pure-Python knowledge base statistics dashboard. Reads shelf-index and log.md; emits Inventory, Layer distribution, Domain distribution, Recent Activity, and Staleness sections. No agent dispatch. Read-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。

Review a data analysis for quality, correctness, and reproducibility. Covers data quality assessment, assumption checking, model validation, data leakage detection, and reproducibility verification. Use when reviewing a colleague's analysis before publication, validating an ML pipeline before production deployment, auditing a report for regulatory or business decision-making, or performing a second-analyst review in a regulated environment.

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 a Quarto-based tour report with embedded maps, daily itineraries, logistics tables, and accommodation/transport details. Produces a self-contained HTML or PDF document suitable for offline use during travel. Use when compiling a planned tour into a shareable document, creating an offline-accessible travel guide, documenting a completed trip with photos and statistics, or producing a professional tour proposal for a group or client.

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 datasets and extract insights. Use when user needs to understand data patterns, statistics, or trends.

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。

Produce a complete narrated MYTHIC SHORT FILM end-to-end on Unsora MCP in the layered cut-paper diorama style — stacked matte cardstock worlds, a strict three-colour palette, exposure that swings, paper wipes hiding every seam, landing on a face. Animation-movie storytelling, not an explainer: gods, monsters, heroes, folklore, origin myths and transformations, told in ten-second story beats with a mythic narrator, native paper foley, and one assembled MP4. Use whenever the user wants a myth, legend, fable, folktale or fairy-tale short, a cut-paper or papercraft animated story, "tell the story of X" as a video, a stop-motion-look mythic film, or says "run the cardstock diorama myth animation" or "run the diorama myth pipeline" — even with no story given, since the skill proposes myths itself. NOT for fact-driven explainers with charts and statistics (that is vox-motion-graphics).

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 A/B test results with statistics. TRIGGERS - Use when user needs help with ab-test-analysis related tasks.

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。

MATLAB R2026a data analysis workflow for tables, timetables, statistics, fitting, optimization-assisted analysis, visualization, report artifacts, and reproducible paper figures. Use whenever the user asks MATLAB to analyze data, plot results, fit models, process CSV/Excel/MAT files, or reproduce figures.

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 expert academic paper summaries for social science research, particularly political science and applied statistics. Use when asked to summarize, review, or create a reading summary of an academic paper, PDF, or research article. Accepts a file (PDF or text format) or a directory of papers. Produces a structured markdown summary — approximately 400–600 words — covering primary contributions, major questions and answers with point estimates, methods and data, and limitations and robustness. Includes BibTeX citation retrieved from Google Scholar and keyword metadata.

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 a weekly changelog entry from git history, filtering operational noise and producing editorial summary, field notes, statistics, and a bounded commit manifest. Stops for review unless commit was explicitly requested.

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 whenever the user asks to run Stata commands, estimate econometric models, work with .dta files, run a .do file, generate Stata output, or do any statistical analysis where Stata is involved. Also trigger when the user mentions Stata variables, Stata syntax, or econometric tasks where Stata is the natural tool, including regressions, IV estimation, diff-in-diff, RDD, panel data, clustering, summary statistics, and margins. Stata runs through pystata on StataNow 19.5 BE; configure once with stata_setup, then drive everything with stata.run() and exchange data directly with pandas. Prefer this skill over subprocess calls or .do-file shelling for Stata work, including cases where the user does not say pystata.

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。