「distribution」の検索結果

Implement comprehensive model drift monitoring using Evidently AI, statistical tests (PSI, KS), and custom metrics to detect data drift and concept drift in production ML systems. Set up automated alerting and reporting workflows to catch degradation before it impacts business metrics. Use when production models show unexplained performance degradation, when new data distributions differ from training data, when seasonal shifts affect input features, or when regulatory requirements mandate model monitoring.

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Generate and verify a hiking gear checklist optimized for season, duration, difficulty, and group size with weight management. Covers the ten essentials, layering systems, navigation tools, emergency kit, and group gear distribution. Use when preparing for a day hike or multi-day trekking tour, packing for a group and distributing shared gear, adapting a standard gear list to specific conditions, reviewing gear before departure, or managing pack weight for long or technical routes.

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 a GitHub release with proper tagging, release notes, and optional build artifacts. Covers semantic versioning, changelog generation, and GitHub CLI usage. Use when marking a stable version of software for distribution, publishing a new library or application version, creating release notes for stakeholders, or distributing build artifacts (binaries, tarballs).

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 and visualize magnetic fields produced by current distributions using the Biot-Savart law, Ampere's law, and magnetic dipole approximations. Use when computing B-fields from arbitrary current geometries, exploiting symmetry with Ampere's law, analyzing superposition of multiple sources, or characterizing magnetic materials through permeability, B-H curves, and hysteresis behavior.

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Analyze prime numbers using primality tests, factorization algorithms, prime distribution analysis, and sieve methods. Covers trial division, Miller-Rabin, Sieve of Eratosthenes, and the Prime Number Theorem. Use when determining whether an integer is prime or composite, finding prime factorizations, counting or listing primes up to a bound, or investigating prime properties within a number-theoretic proof or computation.

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 pre-trained generative diffusion models (Stable Diffusion, DALL-E, Flux) by computing quality metrics (FID, IS, CLIP score, precision/recall), inspecting noise schedules, extracting and visualizing attention maps, and probing latent spaces. Use when evaluating a pre-trained generative diffusion model's output quality, comparing noise schedule variants, analyzing cross-attention patterns for text-conditioned generation, interpolating between latent codes, or detecting out-of-distribution inputs.

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 the dynamics of diffusion processes using stochastic differential equations, Fokker-Planck equations, first-passage time distributions, and parameter sensitivity analysis. Use when deriving probability density evolution for a continuous-time diffusion process, computing mean first-passage times for bounded diffusion, analyzing how drift and diffusion parameters affect process behavior, or validating closed-form solutions against stochastic simulation.

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Turn a set of structures into absorption, distribution, metabolism, excretion, and toxicity estimates with ADMET-AI, and read them as a developability verdict rather than a table of numbers. Use this skill to run batch prediction over a library, interpret each endpoint against its DrugBank-approved percentile, and flag the liabilities that stop a series — hERG blockade, CYP inhibition, poor Caco-2 permeability, high clearance, and plasma protein binding. Also trigger on ADMET-AI, admet_ai, Chemprop-RDKit, hERG liability, CYP3A4 inhibition, Caco-2, bioavailability prediction, or developability triage.

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 researching Claude Code or Codex upstream releases, selecting adaptations, or preparing Harness upgrades. Local-only; not for distribution.

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 standardized charts and visual assets from analytics query results. Prefer dependency-free plain HTML/CSS/JavaScript/SVG for interactive exploratory charts; use local plotting tools such as matplotlib, seaborn, or Plotly when static/report-ready exports or specialized charting libraries are more appropriate. Use for trends, comparisons, distributions, report assets, CSV-to-chart work, and presentation-ready data visuals.

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Analyze queried data for trends, week-over-week comparisons, distributions, funnels, cohorts, top-N lists, anomalies, sanity checks, and report-ready findings. Use after or alongside ClickHouse queries when the user wants insight rather than raw rows.

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 interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).

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 standardized charts and visual assets from analytics query results. Prefer dependency-free plain HTML/CSS/JavaScript/SVG for interactive exploratory charts; use local plotting tools such as matplotlib, seaborn, or Plotly when static/report-ready exports or specialized charting libraries are more appropriate. Use for trends, comparisons, distributions, report assets, CSV-to-chart work, and presentation-ready data visuals.

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 queried data for trends, week-over-week comparisons, distributions, funnels, cohorts, top-N lists, anomalies, sanity checks, and report-ready findings. Use after or alongside ClickHouse queries when the user wants insight rather than raw rows.

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 interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).

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。

Schedule social posts to any of 30+ providers via a running postiz instance (hosted at api.postiz.com or self-hosted). Use this skill whenever someone wants to post, schedule, or publish a draft to LinkedIn, Reddit, Bluesky, Mastodon, Threads, Instagram, TikTok, YouTube, Pinterest, Discord, Slack, or any non-Twitter social channel. ALWAYS chain content-atomizer first for platform-specific copy — this skill is a distribution layer only, it does not rewrite copy. For Twitter/X threads, use typefully instead (better thread UX). Triggers: "post to linkedin", "post to reddit", "post to bluesky", "post to mastodon", "post to threads", "schedule via postiz".

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。

First-run conversational setup wizard for marketing-cli. Use when /cmo detects no populated brand files and no cmo-preferences.md, when the user just installed marketing-cli for the first time, or when they say things like "set up marketing", "start marketing", "marketing wizard", "I just installed marketing-cli", "onboard me", "first time", "initial setup". Asks 3 sharp questions (identity, posture, distribution preferences), records the answers to brand/cmo-preferences.md, then hands off to /cmo's foundation flow which spawns 3 research agents in parallel. The user never has to type /mktg-setup directly — /cmo auto-routes here on first 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。

Take one piece of long-form content and atomize it into 10-20 platform-specific posts across 8 platforms (Twitter/X, LinkedIn, Instagram, Reddit, TikTok, YouTube, Threads, Bluesky). Turns blog posts, podcasts, videos, and newsletters into native social content for each platform. Use this skill whenever someone has existing content they want to distribute — even if they don't say 'atomize' explicitly. Triggers include: 'repurpose this', 'turn this into posts', 'social content from my blog', 'I wrote an article and want to promote it', 'cross-post this', 'content distribution', 'break this down for social', 'I have a podcast episode', 'turn this video into clips', 'make social posts from this', 'content calendar from this article', or any request to get more mileage from existing content.

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。

Programmatic canvas toolkit for creating, editing, and refining Excalidraw diagrams via MCP tools with real-time canvas sync. Use when an agent needs to (1) draw or lay out diagrams on a live canvas, (2) iteratively refine diagrams using describe_scene and get_canvas_screenshot to see its own work, (3) export/import .excalidraw files or PNG/SVG images, (4) save/restore canvas snapshots, (5) convert Mermaid to Excalidraw, or (6) perform element-level CRUD, alignment, distribution, grouping, duplication, and locking. Requires a running canvas server (EXPRESS_SERVER_URL, default http://127.0.0.1:3000).

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。

Audit, finish, or port PCB placement and routing using circuit intent, mechanical constraints, sourcing evidence, native DRC/connectivity, rendered views, and manufacturing feedback. Use before routing, after autorouting, before fabrication release, when adapting a proven board to another connector, enclosure, platform, or regional variant, or when reviewing layers, GND references, power distribution, decoupling, buses, controlled interfaces, RF keepouts, vias, cost-driving features, opens, or DRC findings.

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。

Inventory all founder resources across 8 categories for a one-person company. Use when Codex needs to systematically confirm what resources the founder has — experience, network, skills, relationships, channels, assets, time/money constraints, hard limits — by first doing a broad scan of each category, then drilling into specifics (distribution, usable portions, how to use, cost of use), and producing a confirmed detailed resource inventory written to `opc-doc/`. Does NOT analyze directions, preferences, suitability, or risk tolerance — those belong to downstream 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。

分发数据分析师技能。精通多平台数据聚合、效果评估、跨平台对比分析、竞品对标和优化建议。 触发词：数据分析、效果分析、数据复盘、ROI分析、A/B测试、数据报告、分发效果

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。

多平台内容分发技能包，涵盖12+平台发布规则、排期策略、数据分析和账号管理的完整知识体系。 触发词：内容分发、多平台发布、排期管理、发布规则、数据分析、账号管理

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。

内容多平台分发与复用策略工具集。提供跨平台分发规划、内容格式转化、复用矩阵设计、 分发效果追踪和平台适配优化功能。 触发词：内容分发、多平台发布、内容复用、格式转化、分发策略、社交媒体

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。