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Found 345 Skills
This skill should be used when the user asks to "write an experiment report", "summarize experimental results", "do experiment retrospection", "write a results report", "写实验总结报告", "写实验复盘", or mentions turning completed experiment artifacts into a structured, decision-oriented research report. It assumes strict analysis should come from `results-analysis` first.
Video Transcript Extraction Expert (based on Doubao Video Understanding Model). Supports links from Bilibili, Douyin, Xiaohongshu, YouTube, or local video files. Runs entirely in the background (headless) on the user's computer, no pop-ups, no requirement to log in to video platforms. Outputs strict verbatim transcripts with "semantic segmentation + paragraph-level timestamps" (retains colloquial words, internet memes, pauses). Long videos are automatically segmented to avoid being summarized by the model. Trigger scenarios: - User says "generate transcript", "extract transcript", "convert to text", "video to text" - User says "dictate video", "extract video copy", "video subtitles" - User uses the /video-transcript command - User pastes a video link (Bilibili/Douyin/Xiaohongshu/YouTube) with the intention of getting a text version
Query and summarize site activity logs for a Webflow enterprise site. Surfaces recent changes, identifies who made them, and generates human-readable activity reports. Use for site monitoring, change tracking, publish preparation, or weekly activity summaries. Enterprise plans only.
Use this skill for "write a literature review", "synthesize papers", "review the literature", "summarize research findings", "identify research trends", "gap analysis", "thematic review", "systematic review", "scoping review", "narrative review", "compare studies", "research synthesis", or when the user wants to synthesize multiple papers into a cohesive literature review.
Use when asked to show messages, get an overview, or summarize x-bees chats for today, yesterday, a specific date, or a date range (e.g. current week)
Manage GitHub pull request workflows for coding agents. Use when Codex needs to open, update, monitor, or hand off a PR; wait for CI checks or reviewer feedback; inspect unresolved review threads; address requested changes; summarize PR status; or decide whether to continue, wait, report a timeout, or ask for human input.
Use when working with n8n workflows in any capacity. The always-on protocol for the n8n-skills plugin, loaded by the SessionStart hook every session. Routes to the right skill, summarizes every n8n MCP tool (closing the deferred-description gap), and lists the cross-cutting rules.
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.
Summarize a video by calling the VLM NIM or the Long Video Summarization (LVS) microservice directly. For short videos (under 60s) call the VLM's OpenAI-compatible chat completions endpoint; for long videos (60s or longer) call the LVS microservice. Use when asked to summarize a video, describe what happens in a video, analyze a recording, call or debug LVS summarize/model/health/recommended-config/metrics endpoints, or configure and troubleshoot the LVS service that backs long-video summarization.
Fetch and summarize review comments from the active pull request
Read and comprehend story texts, summarize characters, relationships, and plots, and organize them into a coherent outline. Suitable for quickly grasping the core of a story and providing an outline foundation for script creation
Summarizes Google Cloud Data Lineage graphs to help users debug data quality issues and understand data provenance for BQ/GCS. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).