データ分析、機械学習、LLMアプリ、プロンプト設計（9,426 件）
维护每个功能一份给人看的「需求设计文档」（docs/modules 下，一个功能一份）：待拍板置顶，按需写背景、目标、流程、布局、状态、交互细节、业务规则、召回、AI 生成（prompt）、效果、成本、系统，先图后字，只写当前设计，末尾记关键改动，附出图与上线前检查。新建、更新、同步、补充这份文档都用它，别直接手改——它有固定写法和检查。用户说「出设计文档」「PRD 太长看不懂」「把设计文档同步一下」「重拍截图」「上线前看文档跟上没有」时用；用户抱怨看不到功能现在的设计、不知道最近改了什么时也用；forge 各阶段改了规则、文案、交互、布局、阈值、prompt、模型、架构后收尾也用，哪怕用户没明说。不处理写给 AI 的 PRD/DESIGN（forge-prd、forge-design）、骨架上定布局（forge-design-lab）、改 prompt 本身（prompt-craft）、进度（forge-status）。
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。
Run an autonomous triage-resolve-review-merge loop to auto-pilot the GitHub issue backlog, resolving everything until done with zero prompts. Don't use for single-issue work (/issue-resolver), triage (/issue-triage), or PR review (/issue-pr-review).
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。
Talk to your Garmin data — ask questions about your activities, training load, VO2 Max, heart rate zones.
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。
Query and manage GPS travel data from Geomanic — your privacy-first GPS tracking platform.
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 DAKboard screens, devices, and push custom display data.
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。
Query weather data and forecasts for farm fields via the Agronomy module.
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。
Query ecobee thermostat data via Beestat API including temperature.
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 Arccos Golf performance data including club distances, strokes gained metrics, scoring patterns.
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。
Fetch aviation weather data (METAR, TAF, PIREPs)
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。
Expert-level materials informatics covering materials databases, machine learning for property prediction, high-throughput computation, and data-driven materials discovery.
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。
Track Air France flights using the Air France–KLM Open Data 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。
Expert-level computational biology covering molecular dynamics simulation, protein structure prediction, systems biology, network analysis, and machine learning in biology.
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。
Expert-level data structures covering arrays, linked lists, trees, heaps, hash tables, graphs, and advanced structures like segment trees, tries, and union-find.
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。
Expert-level analytical chemistry knowledge. Use when working with chromatography, spectroscopy, electroanalytical methods, sample preparation, quantitative analysis, calibration, statistics, or instrumental analysis. Also use when the user mentions 'HPLC', 'GC', 'mass spectrometry', 'atomic absorption', 'ICP', 'titration', 'calibration curve', 'detection limit', 'NMR', 'chromatography', 'electrochemistry', 'sample preparation', or 'method validation'.
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。
Expert-level physical chemistry knowledge. Use when working with thermodynamics, chemical kinetics, quantum chemistry, statistical mechanics, spectroscopy, electrochemistry, or surface chemistry. Also use when the user mentions 'Gibbs energy', 'equilibrium constant', 'reaction kinetics', 'rate law', 'activation energy', 'Arrhenius', 'partition function', 'Schrodinger equation', 'molecular orbital', 'electrochemistry', 'Nernst equation', or 'surface adsorption'.
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。
Expert-level linear algebra knowledge. Use when working with vectors, matrices, determinants, eigenvalues, linear transformations, vector spaces, inner products, decompositions, or applications in machine learning and physics. Also use when the user mentions 'matrix', 'determinant', 'eigenvalue', 'eigenvector', 'linear transformation', 'vector space', 'basis', 'orthogonality', 'SVD', 'PCA', 'least squares', 'null space', or 'rank'.
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。
Expert-level statistics knowledge. Use when working with probability distributions, hypothesis testing, regression, Bayesian statistics, statistical inference, experimental design, ANOVA, or statistical modeling. Also use when the user mentions 'p-value', 'confidence interval', 'hypothesis test', 'regression', 'ANOVA', 'chi-square', 't-test', 'Bayesian', 'maximum likelihood', 'statistical significance', 'correlation', 'normal distribution', or 'sampling 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。
Expert-level bioinformatics covering sequence analysis, structural bioinformatics, database searching, phylogenetic analysis, NGS data processing, single-cell analysis, and machine learning in biology.
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。
Guide for defining and using Claude subagents effectively. Use when (1) creating new subagent types, (2) learning how to delegate work to specialized subagents, (3) improving subagent delegation prompts, (4) understanding subagent orchestration patterns, or (5) debugging ineffective subagent usage.
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。
Run a Codex prompt on a cron schedule or at a specific future time. Codex app Automations is the official, always-on surface for durable recurring schedules — recommend it FIRST; this local skill is a terminal fallback that only fires while its daemon runs. Triggers include "/schedule", "cron", "every Monday 9am", "run this at 3pm", "schedule a codex prompt", "recurring codex task", and one-time future runs ("run once at 3pm", "remind me to check X tomorrow"). For fixed-interval repeats ("every N minutes"), use the separate `loop` skill instead.
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。
Run a Codex prompt repeatedly on a fixed interval. Use for "/loop", "run this every N minutes/hours", "poll X every 5 minutes", "repeat this Codex prompt", or any recurring interval-based Codex job. This is the interval-repeat companion to the separate `schedule` skill (cron / specific-time). For a durable, always-on alternative that survives reboots and terminal exits, prefer Codex app Automations; this local CLI is a terminal fallback that only fires while its daemon process is running.
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 writing, debugging, or configuring an omp hook or extension — blocking or rewriting tool calls, redacting tool output, reshaping LLM context, registering tools/commands, or wiring modules through config.yml. Covers ExtensionAPI (current) vs HookAPI (legacy), the event catalog, discovery and load order, and disable controls. Not for Claude Code hooks (~/.claude/settings.json) or the shared harness safety guard (~/.agents/harness/hooks/).
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 AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.
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 and commit a durable handoff document that gives a fresh agent the context and prompt to continue the current planning or implementation work. Use only when explicitly invoked as `$handoff` or when the user explicitly requests a handoff.
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。