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概要と使いどころ
Performs web searches using DuckDuckGo to retrieve real-time information from the internet. Use when the user needs to search for current events, documentation, tutorials, or any information that requires web search capabilities.
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。
Search X (Twitter) in real time, extract relevant posts, and publish tweets/replies instantly—perfect for social listening, engagement, and rapid content ops.
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。
Control and manage VirtualBox virtual machines directly from openclaw. Start, stop, snapshot, clone, configure and monitor VMs using VBoxManage CLI. Supports full lifecycle management including VM creation, network configuration, shared folders, and performance monitoring.
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。
Performs paragraph-by-paragraph translation and deep linguistic analysis. Explains English syntax, grammar, and sentence structure in Chinese. References assets from the raw source directory.
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。
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
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 this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
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 any codebase's source code in depth and produce structured analysis documents saved as markdown files. Use this skill whenever the user asks to understand how a codebase works — architecture, module design, call flows, data models, design patterns, performance characteristics, or any implementation detail. Trigger on phrases like "analyze the source", "explain this code", "how does X work", "where is Y implemented", "trace the flow of", "what happens when", "read through the code", "code walkthrough", "源码分析", "代码解读", "实现原理", "架构分析", "调用链路", "模块分析", or any code-exploration request. Works with any programming language: TypeScript/JavaScript, Java, Python, Go, Rust, C/C++, and more. Even if the user's question seems simple (e.g., "这个文件是干什么的"), use this skill — a thorough, source-backed analysis document is always more valuable than a surface-level guess.
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。
Requires OFOX_API_KEY — create one at https://app.ofox.ai. Generate a handheld, phone-shot UGC clip — imperfect framing, one practical light, vertical, no cinematic grading, no beauty filter. It inverts the polish every other video skill here defaults to — a UGC clip that looks like an ad has failed. Use when a user wants a video that reads as filmed by a real customer rather than by an agency, e.g. "a real-looking phone unboxing of this product", "a creator first-impression clip for TikTok", "an honest review video, nothing slick", or "make it look like a customer shot it". Do not use for a polished brand ad (see seedance-ad-creative), plain catalog footage (see seedance-product-video), a dialogue scene between people (see seedance-short-drama), or a set of cheap vertical drafts to choose from (see shorts-reels).
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。
Requires OFOX_API_KEY — create one at https://app.ofox.ai. Generate a cinematic brand/product ad clip from a product description or photo using the Ofox video API (Seedance 2.5) — runs a short creative brief (product photo, brand tone, camera move, aspect ratio) when the request leaves them open, writes a timestamped shot-craft prompt (hook, showcase, slow-motion climax, hero close), shows a cost estimate, then calls ofox-video-core to submit, poll, download, and report the real cost. Use when a user asks for a commercial-style product or brand video, e.g. "give this perfume bottle a 10-second cinematic brand ad", "make a product ad for our new sneaker", "turn this product photo into a hero video for the landing page", or "I need a 15-second brand video with a slow orbit around the bottle". Do not use for dialogue-driven scenes with people talking (see seedance-short-drama).
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。
Monday morning full pipeline review with metrics, channel performance, and forecast. Reads all CRM tabs, calculates deltas vs previous week, and generates actionable recommendations.
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。
Reallocate ad budget across campaigns and channels using ROAS and marginal return 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。
Mine winning ad angles, hooks, and creative patterns from top-performing ads
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。
Deep technical SEO audit covering Core Web Vitals, crawlability, indexation, structured data, canonical/hreflang, redirect chains, and site architecture. Complements seo-auditor which focuses on on-page/off-page factors.
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。
Research top-performing LinkedIn content in your niche and generate a content playbook
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。
Analytical methods for decomposing expert performance into cognitive and physical task components
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。
Designs and audits data retention and file compaction for an embedded SQLite datastore in a long-lived service — a unified retention registry (one declared policy per table), TTL / absolute-age / row-count-cap policies, a fail-loud coverage guard, WAL/checkpoint tuning, and auto_vacuum/incremental-vacuum so pruning actually shrinks the file. Use when a SQLite DB grows unbounded, a table has an index but no DELETE, a pruned DB never shrinks on disk, metrics are stored as raw events forever, or a new table needs bounding. Keywords retention policy, TTL, reaper, prune, VACUUM, auto_vacuum, incremental_vacuum, WAL checkpoint, freelist, DB bloat, row cap, per-tenant quota. NOT for Postgres/MySQL/server-DB partitioning or TTL, log-line rate-limiting/sampling, backup/replication, schema migrations, or query-performance indexing.
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。
Snowflake, BigQuery, clustering, partitioning, and materialized views for warehouse performance. Activate on: Snowflake, BigQuery, Redshift, query optimization, clustering, partitioning, materialized view, warehouse cost, query profile. NOT for: dbt model structure (use dbt-analytics-engineer), data modeling (use dimensional-modeler).
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。
Matches natural language task descriptions to appropriate skills using semantic similarity, ranks candidates by fit and performance history, and maintains the skill catalog. Use when assigning skills to DAG nodes, searching for the right skill for a task, ranking competing skills, or browsing the skill catalog. Activate on "find skill", "match skill", "which skill", "skill for this task", "skill catalog", "rank skills", "best skill". NOT for executing DAGs (use dag-runtime), creating skills (use skill-architect), or grading skills (use skill-grader).
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。
Performs claim-evidence verification for agent outputs, recording supported, contradicted, or insufficient-evidence results alongside source accessibility. Activate on 'detect hallucination', 'fact check', 'verify claims', 'check accuracy', 'find fabrications'. NOT for validation (use dag-output-validator) or confidence scoring (use dag-confidence-scorer).
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。
Warehouse cost reduction, auto-scaling, query optimization, and lifecycle policies for data infrastructure. Activate on: data cost, warehouse credits, cost reduction, auto-scaling, lifecycle policy, cold storage, cost monitoring, resource optimization. NOT for: query performance tuning (use data-warehouse-optimizer), batch job optimization (use batch-processing-optimizer).
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 validate a static DAG reachability index from source-qualified path/chain decompositions and partial transitive-edge filtering. NOT for treating a partial edge filter as a complete transitive reduction or runtime scheduler.
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。
Investigates DAG incidents with a precise top event, timeline, competing hypotheses, barriers, propagation, and bounded recovery. NOT for automated root-cause classification, trace collection, or performance profiling.
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。
Central catalog of available skills with metadata, capabilities, and performance history. Provides skill discovery and lookup services. Activate on 'skill registry', 'list skills', 'skill catalog', 'available skills', 'skill metadata'. NOT for matching skills to tasks (use dag-semantic-matcher) or ranking (use dag-capability-ranker).
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。