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Granola archive: search, sync freshness, notes, transcripts, panels, SQL counts, and Graincrawl repo work.

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。

Gemini CLIで質問への回答や文章生成、ファイル内容の要約を単発で実行します。モデルやJSON出力の指定、拡張機能などの管理コマンドも扱います。

• メモファイルを要約したいとき
• 単発の依頼で文章を生成したいとき
• 回答をJSON形式で受け取りたいとき

Optimize LLM prompt caching hit rate to reduce API costs and improve latency. Analyzes prompt structure, identifies cacheable vs non-cacheable content, and recommends restructuring to maximize cache reuse. TRIGGER when: user says "prompt cache", "cache hit rate", "reduce LLM cost", "optimize token usage", "cheaper LLM calls", or asks about prompt caching strategies for OpenAI/Anthropic/other providers. DO NOT TRIGGER when: user just wants to optimize a single prompt's quality (use prompt-optimizer instead), or asks about general caching 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。

MyBatis and MyBatis-Spring patterns for mapper design, XML and annotation SQL, result mapping, dynamic SQL safety, transactions, batching, pagination, and query performance. Use when building or reviewing Java persistence code with MyBatis, Spring Boot, MyBatis-Spring, or MyBatis-based legacy 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。

Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines. Use when checking whether agents actually follow the skills, rules, and definitions they were given, rather than assuming they do.

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。

Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work. Use when building or reviewing a Spring Boot backend — REST layer, services, data access, caching, or async work.

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。

Quarkus 3.x LTS architecture patterns with Camel for messaging, RESTful API design, CDI services, data access with Panache, and async processing. Use for Java Quarkus backend work with event-driven architectures. Use when building or reviewing a Quarkus service, especially with Camel messaging or Panache data access.

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。

Decision framework for parsing structured text (quizzes, forms, invoices, receipts, tables) with a hybrid regex-first pipeline — regex extraction handles 95%+ cheaply, a confidence scorer flags low-confidence items, and an LLM validator fixes only the edge cases. Use when choosing between regex and LLM for text extraction, building a cheap document parser, or optimizing extraction cost and accuracy.

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。

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading. Use when writing or reviewing PyTorch training loops, model architectures, or data loading, or when a run will not reproduce.

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。

Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced For You algorithm. Use this skill whenever the user is building any system that picks "the top K items for a (user, context)" — social feeds, content CMSs, RAG rerankers, task prioritizers, notification triage, search reranking, ad ranking.

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 prediction-market, basket, oracle, and trading-agent workflows for compliance, safety, data-quality, privacy, and execution risk. Use before any workflow handles venue auth, user portfolio data, API keys, or trade planning.

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 draft prompts, detect intent and missing context, match ECC commands, skills, and agents, and output a ready-to-paste optimized prompt with diagnosis and rationale — advisory only, never executes the task. Use when the user says 'optimize prompt', 'improve my prompt', 'rewrite this prompt', 'help me prompt', 优化prompt, 改进prompt, 怎么写prompt, or 帮我优化这个指令; not for requests to optimize code or performance.

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。

Redis data structure patterns, caching strategies, distributed locks, rate limiting, pub/sub, and connection management for production applications. Use when adding caching, a distributed lock, rate limiting, or pub/sub with Redis, or when key design needs 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。

Nuxt 4 app patterns for hydration safety, performance, route rules, lazy loading, and SSR-safe data fetching with useFetch and useAsyncData. Use when building or reviewing a Nuxt 4 app, or debugging hydration mismatches and SSR-safe data fetching.

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。

MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends. Use when designing MySQL or MariaDB schemas and indexes, or when a query, transaction, or replica lags.

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。

End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model.

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。

Optimize and verify latency-sensitive systems — realtime dashboards, market data feeds, streaming agents, execution gateways, queues, and caches — by tracking p50/p95/p99 latency, freshness age, and queue depth, mapping hot paths, and running live readbacks. Use when p95 latency, throughput, or data freshness matters.

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。

为 OpenClaw AI Agent 锻造完整的龙虾灵魂方案。根据用户偏好或随机抽卡， 输出身份定位、灵魂描述(SOUL.md)、角色化底线规则、名字和头像生图提示词。 如当前环境提供已审核的生图 skill，可自动生成统一风格头像图片。 当用户需要创建、设计或定制 OpenClaw 龙虾灵魂时使用。 不适用于：微调已有 SOUL.md、非 OpenClaw 平台的角色设计、纯工具型无性格 Agent。 触发词：龙虾灵魂、虾魂、OpenClaw 灵魂、养虾灵魂、龙虾角色、龙虾定位、 龙虾剧本杀角色、龙虾游戏角色、龙虾 NPC、龙虾性格、龙虾背景故事、 lobster soul、lobster character、抽卡、随机龙虾、龙虾 SOUL、gacha。 Use when creating, designing, or customizing an OpenClaw lobster persona — identity, SOUL.md, name, or avatar prompt.

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 configure hookify rules — markdown files with YAML frontmatter that match bash, file, prompt, or stop events by regex or conditions and show warn/block messages to the agent. Use when creating a hookify rule, writing hook rule syntax, configuring hookify, or adding pattern guardrails such as blocking dangerous commands, .env edits, or debug code.

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。

Read-only Itô basket and prediction-market data skill. Index the live basket catalog, compare a basket against user-supplied research or a watchlist, build a source-grounded market brief, or draft a non-executable planning worksheet. Use when a user asks to browse or index Itô baskets, compare a basket against notes or a thesis, research prediction-market events/venues/liquidity, or plan a basket or market idea without trading. Never advises, orders, trades, reserves, or executes.

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。

Inspect the availability of ML training on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed training manifest. Use after ito-compute has booked GPU nodes and the user wants pre-training, fine-tuning, or RL on that metal. ECC implements no training stack of its own.

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。

Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+. Use when adding on-device LLM features with Apple FoundationModels on iOS 26+.

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 reproducible, cross-platform (macOS/Linux) development environments with Flox, a declarative Nix-based environment manager. Use when setting up project toolchains, installing system-level dependencies (compilers, databases, native libs), pinning exact package versions for a team, onboarding developers, running local services (PostgreSQL, Redis, Kafka), or solving 'works on my machine' problems — including agent/vibe-coding setups that need project-scoped tools without sudo. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.

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。

PreToolUse fact-forcing gate that denies the first Edit/Write/Bash (including MultiEdit) attempt until the agent presents concrete facts (importers, data schemas, verbatim user instruction), then allows retry; A/B-tested at +2.25 quality points. Use when enabling or configuring the GateGuard hook, exempting paths via env vars, or handling first-touch denials.

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。