922 件 ・ 関連度順
概要と使いどころ
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm
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 context manager specializing in information storage, retrieval, and synchronization across multi-agent systems. Masters state management, version control, and data lifecycle with focus on ensuring consistency, accessibility, and performance at scale.
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。
Assess MotherDuck costs, plan fit, and ROI using current pricing and the workload’s compute and storage needs.
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 files, object storage, dataframes, or external databases into MotherDuck using an appropriate bulk ingestion path.
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。
Implement the separately maintained Documents React client for AuthCrunch encrypted storage, recovery keys, chunk upload/download, recipient sharing, and safe session handling. Does not implement manager/profile APIs or provision the backend.
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。
Maintain the opt-in encrypted Documents API, immutable account ownership, SQLite ciphertext storage, chunk transactions, recipient key envelopes, configuration parser, and TLS/browser cryptographic tests. The separately maintained React application has its own integration skill.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for crypto, encoding, steganography, APK, IPA, and mobile trust-boundary challenges. Use when the user asks to decode a blob, recover a transform chain or key, inspect hidden media payloads, hook an APK or IPA signer, inspect app storage, or replay mobile request-signing logic. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
Working memory protocol — routes to session protocol, memory audit, MCP/URI integration, or storage details based on the current need. Keeps default continuity usage cheap.
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 GitHub Backup when an agent needs to mirror repositories, release assets, and gists into local storage on a schedule, instead of manually exporting GitHub content repo by repo.
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。
Builds Apify Actors for scalable cloud scraping with automatic proxy management and storage. Uses the Apify SDK (Actor, Dataset, KeyValueStore, RequestQueue) and Crawlee library for robust crawling.
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。
Appwrite is an open-source backend platform for web, mobile, and AI apps. This skill helps agents use Appwrite's real services—Auth, Databases, Storage, Functions, Messaging, Realtime, and Sites—instead of inventing a generic backend workflow.
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。
Deploys custom Apify Actors via the Apify API v2 for large-scale web crawling using CrawleeJS. Leverages Apify dataset storage, RequestQueue, and proxy configuration for distributed scraping at scale.
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。
Appwrite is an open-source, self-hosted backend platform that provides authentication, databases, storage, functions, messaging, and realtime APIs out of the box. It serves as a privacy-first alternative to Firebase and Supabase, packaged as Docker microservices for full data ownership.
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 any Supabase project for security vulnerabilities, RLS misconfigurations, exposed API keys, auth bypasses, and storage issues. Use this skill whenever the user mentions Supabase security, RLS policies, database security audit, security review, penetration testing a Supabase app, checking if their database is exposed, hardening their Supabase project, fixing RLS, or anything related to securing a Supabase or vibe-coded application. Also trigger when the user asks about securing apps built with Lovable, Bolt, Replit, Cursor, or any AI coding tool that uses Supabase as a backend. Even if the user just says 'is my app secure' or 'check my database' and their project uses Supabase, use this skill. (DEPRECATED: this skill is a backwards-compat shim. Prefer the multi-backend `database-sentinel` skill, which covers Supabase plus Firebase, MongoDB, self-hosted Postgres, and self-hosted MySQL.)
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。
Nature-style hydrology manuscript reviewer skill for testing streamflow, runoff, groundwater, water storage, drought, flood, hydroclimate and water-resource claims against water-balance closure, hydrologic signatures, model structure and observational constraints.
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。
Comprehensive Cloudflare platform skill covering Workers, Pages, storage (KV, D1, R2), AI (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), security (WAF, DDoS), and infrastructure-as-code (Terraform, Pulumi). Use for any Cloudflare development task. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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 working on imp's quantization formats, loaders, or dequant paths - GGUF Q4_0...Q8_0/Q*_K/IQ4/MXFP4, NVFP4 two-level scaling (Modelopt vs compressed-tensors layouts), FP8 E4M3, StorageTier, decode cache, KV-cache dtypes (auto/fp16/fp8/int8/int4/nvfp4/mxfp4), "which quant should I use", "which KV dtype", scale-factor layout, dequant kernel wiring, imp-quantize / AWQ, judging quant quality (PPL). Do NOT use for writing/optimizing GEMM/GEMV kernels (sm120-cuda-expert) or measuring quant perf (benchmark-cuda).
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。
Evaluates commodity swaps, options, and exotic structures with seasonality, convenience yield, and storage cost analysis. Use when pricing commodity derivatives, analyzing energy structures, or evaluating commodity hedging.
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。
Entity and relation tracking skill using MCP memory server patterns and local knowledge graph storage. Build persistent knowledge graphs of entities, relationships, and observations across agent sessions. Covers the MCP memory server (@modelcontextprotocol/server-memory), local JSON-based graphs, and entity-relation querying patterns for long-running agents.
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。
診斷並清理 macOS 磁碟空間，特別是「系統資料 / System Data」這類看不出內容的用量。涵蓋開發者工具殘骸（Xcode iOS DeviceSupport、Simulator runtime、DerivedData）、套件管理器快取（Homebrew、pnpm、pip、npm、cargo、go、uv）、容器與 VM 磁碟（Docker、podman、lima）、瀏覽器 profile、以及已移除 app 的孤兒 container。使用時機：(1) 使用者說磁碟快滿了、System Data 佔太多、想清空間 (2) 詢問某個資料夾或快取能不能刪 (3) 移除 app 後想清乾淨殘留檔案、完整解除安裝 (4) 想知道 Docker.raw、Group Containers、Library/Caches 這些是什麼、佔了多少。Also triggers in English — disk full, startup disk almost full, free up disk space, clean up Mac storage, what is System Data on my Mac, what is taking up space, safe to delete this cache, uninstall app leftovers, reclaim disk space, Docker.raw huge, Xcode taking too much space
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 working with iOS/macOS Keychain Services (SecItem queries, kSecClass, OSStatus errors), biometric authentication (LAContext, Face ID, Touch ID), CryptoKit (AES-GCM, ChaChaPoly, ECDSA, ECDH, HPKE, ML-KEM), Secure Enclave, secure credential storage (OAuth tokens, API keys), certificate pinning (SecTrust, SPKI), keychain sharing across apps/extensions, migrating secrets from UserDefaults or plists, or OWASP MASVS/MASTG mobile compliance on Apple platforms.
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。
Purify water from wild sources using boiling, filtration, and chemical methods. Covers source assessment and priority ranking, sediment pre-filtering, method selection (boiling, chemical, UV, filter), altitude-adjusted boiling procedure, chemical treatment dosages, and safe storage practices. Use when needing drinking water in a wilderness setting, when available water sources are of unknown quality, in an emergency survival situation where dehydration is a risk, or when making water safe for cooking or wound cleaning.
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。
Set up centralized log aggregation with Loki and Promtail (or ELK stack), including log parsing, label extraction, retention policies, and integration with metrics for correlation. Use when consolidating logs from multiple services into a searchable system, replacing local log files with centralized queryable storage, correlating logs with metrics and traces, implementing structured logging with label extraction, or troubleshooting production incidents requiring cross-service log analysis.
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。