データ分析、機械学習、LLMアプリ、プロンプト設計（8,834 件）
概要と使いどころ
Operações de LLM — RAG, embeddings, bancos de dados vetoriais, fine-tuning, prompt engineering avançado, custos de LLM, avaliações de qualidade e arquiteturas de IA para produção.
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。
Construa pipelines de dados escaláveis, data warehouses modernos e arquiteturas de streaming em tempo real. Implementa Apache Spark, dbt, Airflow e plataformas de dados nativas em nuvem.
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。
Cientista de dados especializado em análises avançadas, machine learning e modelagem estatística. Trabalha com análise de dados complexa, modelagem preditiva e business intelligence.
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。
Curação de dados acelerada por GPU para treinamento de LLM. Suporta texto/imagem/vídeo/áudio. Recursos incluem deduplicação fuzzy (16× mais rápida), filtragem de qualidade (30+ heurísticas), deduplicação semântica, redação de PII, detecção NSFW. Escala em GPUs com RAPIDS. Use para preparar datasets de treinamento de alta qualidade, limpar dados web ou deduplicar grandes corpora.
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。
Processamento escalável de dados para workloads de ML. Execução em streaming em CPU/GPU, suporta Parquet/CSV/JSON/imagens. Integra-se com Ray Train, PyTorch, TensorFlow. Escala de uma única máquina para centenas de nós. Use para inferência em lote, pré-processamento de dados, carregamento de dados multi-modal ou pipelines distribuídos de ETL.
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。
Load this skill whenever the project contains HTML data tables (<table> elements). Under no circumstances use tables for layout purposes. Absolutely always include <th> elements with appropriate scope attributes, a <caption> or aria-labelledby, and ensure complex tables have headers associated with data cells. Apply these rules to every data table without exception.
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。
Load this skill whenever the project contains SVG graphics — inline SVGs, external SVG files, SVG icons, SVG illustrations, or SVG-based data visualizations. Under no circumstances use SVG without proper accessible titles, descriptions, and ARIA roles where required. Absolutely always add <title> and <desc> to meaningful SVGs and set role="img" with aria-labelledby pointing to those elements. Also apply this skill whenever the project accepts untrusted or user-uploaded SVG content, which requires sanitization before rendering.
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。
**REQUIRED** - Always activate FIRST on any git/VCS operations (commit, status, branch, push, etc.), especially when HEAD is detached. If `.jj/` exists -> this is a Jujutsu (jj) repo - raw git commands can corrupt data. Essential git safety instructions inside. DO NOT IGNORE.
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。
Load this skill whenever the project contains charts, graphs, data visualizations, infographics, or any visual representation of data (bar charts, line charts, pie charts, scatter plots, dashboards). Under no circumstances render a chart without a text alternative, data table, or summary. Prioritize conveying the same information through non-visual means.
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。
Normalizes company names, industries, domains, locations, and descriptions. Use when the user provides company records and wants consistent canonical fields with confidence and unresolved items flagged.
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。
Qualifies and scores B2B prospects against a supplied ideal customer profile. Use when the user provides a lead list, company records, prospect data, or qualification criteria and wants prioritization, fit analysis, or disqualification reasons.
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。
Normalizes and improves the consistency of prospect-list data. Use when the user provides a messy prospect or lead export and wants standardized records, flagged issues, and a cleanup summary.
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。
Divides records into geographic or account-ownership territories. Use when the user provides records with location or account data and wants consistent territory assignments with unresolved locations flagged.
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 spend analytics and dashboards from Qdrant vector data. Covers bulk scroll extraction, aggregation patterns, vendor grouping, and Chart.js visualization. Use when building analytics features, aggregating procurement data, or creating dashboards.
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。
Detect anomalies in procurement data using Qdrant vector operations. Covers centroid-based outlier detection, near-duplicate finding via batch recommend, amount z-score analysis, and vendor variance scoring. Use when building anomaly detection, fraud detection, or data quality features.
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。
Improves Agent Skills via validate → rule-based eval cases → plugin-eval → prompt evals → bounded edits with held-out gates. Use when tuning skill quality, routing, or adopting Chrome/Microsoft T-named quality gates—not for bulk validate-only or SkillOpt automation.
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。
「開発日誌更新」「開発日誌作って」の言及時に使用。esa-llm-scoped-guardで開発日誌を新規作成・更新します。
Use when creating a new project folder, starter pack, app scaffold, or agent-ready workspace — AGENTS.md, README, TASKS, DECISIONS, PROMPTS, an idempotent bootstrap script, and starter-pack modes.
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。
プロジェクトの構造インデックスと依存関係トレースにより、RAG的なコンテキスト取得を実現するスキル
Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
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。
把多页 HTML 报告(主页 + N 子页 + PNG 资产)合并为单一独立 HTML / PDF / XLSX 三件交付物。 Use when finalizing a disease market sizing report and need shareable deliverables — single-file HTML for email/IM(零依赖,双击浏览器开), optional PDF for print/archive, XLSX for data export. 领域无关、跨疾病通用。 下游 of disease-market-sizing-html-template;上游 of email/IM/print 分发。 Use proactively whenever the user says "做交付物" / "生成 PDF" / "导 Excel" / "合并单文件 HTML"。
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。
Phase 4.5 hook by Phase-2-Quality-Fix sprint. 封装 mmdc/npx Mermaid CLI subprocess,把 LLM 输出的 `<div class="mermaid">...</div>` block 渲染为 PNG。Use AFTER cite-bound-content-generator (Phase 4 Turn 1) and BEFORE report-bundle-builder (Phase 5). Production smoke must fail closed if rendering fails.
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。
Discover ordinary public webpages with LLM-optimized Tavily search results. Use when no specific URL is known and the user needs a quick public-web lookup, articles, recent news, sources, or domain-filtered results. This is the default Tavily leaf for simple public-web discovery. Do not use when the user already supplied the target URL (use tavily-extract), wants URLs under one known site (tavily-map), wants many pages' content (tavily-crawl), needs a full cited synthesis (tavily-research), or needs named platforms, login state, platform-native content, or cross-platform collection (Agent Reach).
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 an agent needs to drive a real Chrome window via opencli — inspect a page, fill forms, click through logged-in flows, or extract data ad-hoc. Covers the selector-first target contract, compound form fields, stale-ref handling, network capture, and the agent-native envelopes the CLI returns. Not for writing adapters — see opencli-adapter-author 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。