「rl」の検索結果

Podcast knowledge workflows powered by Podwise CLI: search podcasts and episodes by keyword, monitor followed shows for new releases, find popular episodes, ask questions and extract insights from transcript content, process Podwise episode URLs, YouTube videos, Xiaoyuzhou links, and local audio or video files to retrieve transcripts, summaries, chapters, Q&A, mind maps, highlights, and keywords — plus catch up on your backlog, refine your listening taste, generate weekly recaps, export episode notes to PKM tools, research topics across podcasts, debate episode ideas, and generate language learning cards. Use when the user wants to find, summarize, transcribe, or extract insights from any podcast or audio content, or manage their listening library.

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 analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.

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。

Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.

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 doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).

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 the user explicitly asks for the Inngest REST API v2, raw HTTP, OpenAPI, API docs, API authentication, or an endpoint that the Inngest CLI does not expose. Covers api-docs.inngest.com, llms.txt, the OpenAPI v2 spec, Bearer authentication with API keys or signing keys, production and local base URLs, raw curl/fetch requests, request-shape discovery, pagination, secret redaction, and when to prefer the `inngest-api-cli` 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。

Capture one supplied product URL as auditable, unadopted FF&E evidence and inspect its retained history. Use to clip a page or review prior captures; not to save a library product or adopt a schedule item.

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。

Geospatial vector analysis extending pandas. Read/write spatial formats (Shapefile, GeoJSON, GeoPackage, Parquet, PostGIS), CRS handling, geometric ops (buffer, simplify, centroid, affine), spatial analysis (joins, overlays, dissolve, clipping, distance), visualization (choropleth, interactive maps, basemaps). Use for spatial joins, overlays, CRS transforms, area/distance, maps.

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。

Provides AWS Lambda integration patterns for Python with cold start optimization. Use when deploying Python functions to AWS Lambda, choosing between AWS Chalice and raw Python approaches, optimizing cold starts, configuring API Gateway or ALB integration, or implementing serverless Python applications. Triggers include "create lambda python", "deploy python lambda", "chalice lambda aws", "python lambda cold start", "aws lambda python performance", "python serverless framework".

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。

Provides AWS Lambda integration patterns for Java with cold start optimization. Use when deploying Java functions to AWS Lambda, choosing between Micronaut and Raw Java approaches, optimizing cold starts below 1 second, configuring API Gateway or ALB integration, or implementing serverless Java applications. Triggers include "create lambda java", "deploy java lambda", "micronaut lambda aws", "java lambda cold start", "aws lambda java performance", "java serverless framework".

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。

Generates professional board meeting presentation content (board-deck.md) with executive summary, financials, product updates, GTM metrics, team/hiring, strategic decisions, and appendix. Supports early-stage, growth-stage, and pre-IPO formats. Use when preparing board meeting materials, quarterly board updates, or investor presentations.

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。

Converts documents and URLs to markdown via tiered fallback (MCP markitdown, native tools, user notice). Use when a skill must ingest PDF, DOCX, or URL 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。

Use Fairlearn to assess group fairness, compute disparity metrics, visualize subgroup performance, and mitigate unfairness with preprocessing, reductions, postprocessing, or adversarial learning.

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。

Route DRL-Pytorch reinforcement-learning workflows for standalone PyTorch Q-learning, DQN-family, PPO, DDPG, TD3, SAC, Atari DQN, and Actor-Sharer-Learner scripts.

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 ROS/Gazebo Velodyne mobile-robot navigation with the DRL-robot-navigation TD3 implementation, including simulator setup, environment contracts, bounded training, checkpoints, and policy evaluation.

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 CleanRL's single-file reinforcement learning scripts, evaluation utilities, experiment operations, and repository maintenance workflows safely.

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。

自然言語メモリファイル（CLAUDE.md, todos, 設定）を原始人形式に圧縮し入力トークン削減。 技術内容・コード・URL・構造は完全保持。圧縮版が原ファイルを上書き、人間可読版は FILE.original.md として保存。「/genshijin-compress <filepath>」「メモリファイル圧縮」で起動。

Plan and implement interactive chapter or playground pages for this Docusaurus repo. Use when Codex needs to port AI-generated JSX into JoyRL Book, add a standalone interactive route under `src/pages/`, wire a chapter into interactive mode, or extend the current left-reading/right-playground interaction pattern.

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。

Sci-fi and punk world art direction for Blender including hard sci-fi, space, cyberpunk, steampunk, dieselpunk, atompunk, solarpunk, biopunk, and clockpunk.

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。

Painterly art direction spanning watercolor and oil-painting looks for Blender using soft edges, pigment texture, and illustrative lighting.

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。

Historical and period world art direction for Blender including Western, pirate, samurai/ninja, Viking, ancient Egypt/Greece/Rome, Victorian, modern, and military eras.

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。

Apocalyptic and dystopian world art direction for Blender including post-apocalyptic, zombie, alien invasion, post-human, dystopian, and utopian contrast sets.

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。

Fantasy world-building art direction for Blender covering medieval, high fantasy, dark fantasy, and urban fantasy asset language.

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。

Art direction for open world and sandbox games in Blender with biome landmarks, traversable scale, and discovery props.

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 and deploy serverless functions on AWS Lambda. Configure triggers, manage permissions, and optimize performance. Use when implementing serverless applications.

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。