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概要と使いどころ
Configure, compile, and test Yuzu with the repo's canonical Meson entrypoints and per-OS build directories. Use when validating code changes, selecting test suites, reconfiguring a build directory, or recovering from host/builddir mismatches on Linux, macOS, or Windows.
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。
Discovers requirements and generates architectural, design, and deployment guidance for dynamic hybrid search systems by combining semantic search and keyword search. Optimized for AlloyDB hybrid search use cases in Google Cloud. Use when users need vector search combined with structured SQL filtering, faceted attributes, semantic reranking, in-database AI validation, or serverless hosting across transactional relational databases, analytical data warehouses, or managed database engines. DON'T use this skill for simple keyword-only search, or when a standalone non-relational vector database is required.
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。
Semantic vector search with moflo — RAG over your own documents, similarity matching, context-aware retrieval via HNSW (node:sqlite-backed). Use when building retrieval layers for chat, search, or context-assembly.
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。
Resolve collector ownership from persisted source records and fail closed on missing owner OIDs.
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。
Master the `agentbrain` CLI (npm package `agentbrain-cli`). Use this skill whenever the user runs, installs, configures, or asks about `agentbrain` commands; when they interact with the AgentBrain enterprise data hub — organizations, connectors, knowledge bases, workflows, media/documents, knowledge graph, permissions, LLM/prompt config, cost & usage, governance, audit logs; when uploading documents/files to AgentBrain (`agentbrain media upload`); when authenticating (login/logout/token/apiKey); when retrieving MCP context (`agentbrain retrieve-context`); when running SQL against a connector; when the user pastes any `agentbrain …` command; when they edit `~/.agentbrain/config.json`; or when they mention AgentBrain, agent-brain, agentbrain-cli, or the `.agentbrain` folder.
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。
PXE/netboot 経由で Debian + HW RAID10 を自動インストール (OpenWrt ローカル TFTP + embed ipxe.efi + IPv4 リテラル mirror)。BMC USB redirector が累積劣化した機種 (TX1320 M3 等) や、 cross-site 拠点の install に使う。phase 19 で training-tx1320 で完遂、 物理操作なしで自力 SSH まで到達。
Run the same scrape or task across many accounts at once - each in its own browser profile with its own fingerprint, cookies and exit IP - and read data from sites that need a session or that answer a plain HTTP scraper with a captcha while answering a real browser. One command per site returns JSON, so there are no selectors to write or repair: Amazon and Walmart search, Google and DuckDuckGo results, Reddit posts and comments, X timeline, Medium, Yelp, Indeed job listings, Hacker News, GitHub, PyPI, npm, plus exit-IP and fingerprint checks. Use for multi-account operations you are authorized to run, price and listing monitoring per region, SERP collection, logged-in data, and scrapers that keep breaking. Also for 'scrape amazon', 'google search results', 'reddit data', 'scrape logged in site', 'run task on many accounts', 'site blocks my scraper', 'scraping without selectors'. Node or Python.
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 a new API connector or provider by matching the target repo's existing integration pattern exactly. Use when adding one more integration without inventing a second architecture.
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。
This skill should be used when the user asks to "attack Active Directory", "exploit AD", "Kerberoasting", "DCSync", "pass-the-hash", "BloodHound enumeration", "Golden Ticket", "Silver Ticket", "AS-REP roasting", "NTLM relay", or needs guidance on Windows domain penetration testing.
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。
Persistent vector memory for Claude Code via LanceDB. Use when: remembering across sessions, storing lessons, recalling past decisions, maintaining context continuity. Tools: memory_store, memory_recall, memory_update, memory_forget, memory_merge.
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。
Scope, preregister, execute, audit, normalize, and publish GEODE evaluations with research-question, reproduction, attempt-lineage, trajectory, verifier-receipt, and immutable artifact contracts. Use for benchmark runs or comparisons, eval-artifact and cache-accounting audits, GPT or subscription result normalization, research question or hypothesis framing, retry diagnosis, trajectory publication, DPO or reward-data readiness reviews, and requests involving MCPMark, tau2, BFCL, Agent-World, HAL, Terminal-Bench, or Toolathlon.
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。
Trae a este proyecto las mejoras que la plantilla de origen recibió después de la instanciación — lee .template-origin, calcula el diff del tooling (skills, hooks, scripts, workflows) contra la plantilla actual y propone aplicarlo. Úsalo cuando la persona quiera actualizar/sincronizar el proyecto con la plantilla (p. ej. "actualiza la plantilla", "trae las mejoras nuevas del template").
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。
Drafts corporate board of directors meeting minutes. Triggers on "board minutes", "minutes of board meeting", "board of directors meeting minutes", "corporate minutes", "board resolutions", or "bylaws compliance".
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。
Drafts U.S. corporate board-of-directors meeting minutes into formal, defensible records documenting valid corporate action and governance process. Triggers on board minutes, directors meeting record, board resolutions, quorum validation, motion and vote capture, corporate secretary records, governance drafting. Requires source materials such as agenda, attendance, bylaws, notices, reports, prior minutes, and resolutions.
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。
Professional network graph analyst identifying Gladwellian superconnectors, mavens, and influence brokers using betweenness centrality, structural holes theory, and multi-source network reconstruction. Activate on 'superconnectors', 'network analysis', 'who knows who', 'professional network', 'influence mapping', 'betweenness centrality'. NOT for surveillance, discrimination, stalking, privacy violation, or speculation without 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。
Use when running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).
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。
Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).
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 desktop window systems that feel native on macOS and Windows: split views, inspectors, auxiliary windows, tiling, snap-safe sizes, default placement, and chrome density. Use when a Tauri/Electron/WinUI/SwiftUI app feels awkward, overlapping, over-chromed, or generic, or when you need a real geometry contract for multiple surfaces. NOT for mobile layouts, marketing pages, or CSS-only component styling without multi-window or multi-pane behavior.
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。
Meta-skill that orchestrates the discourse skill suite: routes between steel-man-argument, socratic-questioning, toulmin-argument-analysis, logical-fallacy-detector, bad-faith-rhetoric-detector, discourse-elision-analyzer, forensic-speech-structure, and productive-discourse-facilitator. Use when analyzing conversations, facilitating discourse, or operating as a dialogue copilot. Maintains mode (silent analysis, coaching overlay, active facilitator) and decides which skills to invoke based on conversation dynamics.
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。
Fast parallel codebase scouting. Spawns multiple Explore subagents to search directories simultaneously, returning a consolidated file map with architecture fingerprint, complexity estimates, and routing suggestions. Use before planning, debugging, or any task spanning multiple directories. NOT for reading a single known file in depth (use Read directly); NOT for semantic find-usages or go-to-definition.
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。
Session-scoped directory edit restriction. Blocks Edit and Write outside the allowed path for the current session only. Use when debugging to prevent accidentally "fixing" unrelated code, or when you want to scope changes to one module. Use when asked to "freeze", "restrict edits", "only edit this folder", or "lock down edits". NOT for blocking destructive shell commands (see mk:careful).
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。
Bridge Codex to web-based AI model products by packaging local task context, scrub-checking it, sending it through an approved browser surface to ChatGPT Pro, Claude, Grok, Gemini, or another web model, waiting for the answer, and returning the model response to the user or Codex. Also guide DevSpace-like MCP Connector Mode when the user wants ChatGPT Pro or another MCP-capable web host to access approved local workspaces without relying on Codex browser automation. Use when the user asks for GPT Pro, ChatGPT Pro, Claude web, Grok, Gemini web, web model bridge, external model consult, ask another model, second opinion, use a web AI model, browserless agent access to GPT Pro, MCP connector, DevSpace-like workflow, or send local repo context to a browser-based model for planning, review, debugging, architecture discussion, or implementation guidance.
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 semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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。
Determines whether bone mineral density (BMD) measurement is indicated when patients have osteoporosis risk factors or have discontinued sex hormone therapy following gonadectomy. Clinical triggers include documented osteoporosis risk factors (e.g., low body weight, glucocorticoid use, prior fracture) or cessation of sex hormone therapy after surgical gonadectomy.
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。