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Use when processing, summarizing, or extracting insights from meeting notes in the Obsidian vault. Triggers on "summarize meetings", "process meetings", "meeting summaries", "extract from meetings", "meeting insights".
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Analyze, summarize, and extract insights from DeLive transcription sessions. Use when: user mentions DeLive, transcription, meeting transcripts, live captions, audio transcription, AI correction, corrected transcript, or transcript analysis; user wants to search, retrieve, summarize, correct, or process recorded transcripts; user asks about meeting notes, action items, discussion summaries, or transcript quality from DeLive. Requires DeLive app running locally with its MCP server or REST API.
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Summarize long Isabelle or Coq proof scripts into high-level logical steps and reasoning flow. Use when users need to: (1) Understand the structure of a complex proof, (2) Document proof strategies for others, (3) Extract the key reasoning steps from verbose proof scripts, (4) Create readable proof outlines from detailed tactical proofs. Produces hierarchical outlines with moderate detail showing proof structure, main cases, key lemmas, and reasoning flow for both Isabelle/Isar and Coq proofs.
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Generate concise summaries of source code at multiple scales. Use when users ask to summarize, explain, or understand code - whether it's a single function, a class, a module, or an entire codebase. Handles function-level code by explaining intention and core logic, and large codebases by providing high-level overviews with drill-down capabilities for specific modules.
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Summarizes the complete lifecycle of a bug across code versions, tracking its introduction, detection, fixing attempts, and regression history. Use when users need to: (1) Understand how a bug evolved over time, (2) Trace when and how a bug was introduced, (3) Analyze fix attempts and their effectiveness, (4) Identify regression patterns, (5) Generate bug lifecycle reports for documentation or post-mortems. Takes a repository, bug identifier, and version history as input.
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Generates clear and structured pull request descriptions from code changes. Use when Claude needs to: (1) Create PR descriptions from git diffs or code changes, (2) Summarize what changed and why, (3) Document breaking changes with migration guides, (4) Add technical details and design decisions, (5) Provide testing instructions, (6) Enhance descriptions with security, performance, and architecture notes, (7) Document dependency changes. Takes code changes as input, outputs comprehensive PR description in Markdown.
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Performs abstract interpretation to produce summarized execution traces and high-level program behavior representations. Highlights key control flow paths, variable relationships, loop invariants, function summaries, and potential runtime states using abstract domains (intervals, signs, nullness, etc.). Use when analyzing program behavior, understanding execution paths, computing loop invariants, tracking variable ranges, detecting potential runtime errors, or generating program summaries without concrete execution.
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Summarize extracted paper text into concise Markdown memory for later Stage 2 and Stage 4 background use, with fixed section headings and no fabricated claims.
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Organize, categorize, and summarize business expenses for reimbursement and tax preparation. Use when a user asks to create an expense report, organize receipts, categorize expenses, summarize spending, prepare expenses for reimbursement, or compile business expenses for tax filing. Handles receipts, CSV data, and manual entries.
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Summarize noisy logs into likely causes and next steps. Use when a junior developer needs help interpreting logs.
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Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).
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Interpret video content visually by sampling frames into timestamped contact sheets that can be read as images. Use when: user asks what happens in a video; asks to summarize, describe, review, or QA video content or footage; asks about scenes, actions, people, or objects in a video; needs a storyboard-style overview of a clip; asks to find where something occurs in a video. Triggers on 'watch this video', 'what's in this video', 'summarize the video', 'describe the footage', 'contact sheet', 'storyboard', 'review this clip', 'find the scene where', 'scene detection', 'shot boundaries', 'detect cuts', 'dwell points'. For converting, trimming, or transcoding video, use processing-video instead.
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Summarize a user interview transcript into structured insights with key themes, quotes, and action items. Use after conducting user interviews to extract and share findings efficiently.
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Summarize a document at a requested length.
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AI Overview (AI Mode) scraping via Google Search. Returns AI-summarized key points for a single keyword, ideal for deep research, technical Q&A, long-tail product selection, and cross-border consumer preference analysis using the latest web information. Single-round only; follow-ups require the agent to summarize context and issue a new request. Triggered by: Google AI, AI Overview, AI Mode, Google AI search, AI search, deep research, consumer preference analysis, web summary, long-tail product research, cross-border market insights.
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Route requests to summarize files, URLs, images, inline text, or multiple sources. Select the requested format and preserve evidence, exact counts, uncertainty and source coverage through summarization, synthesis and agent-result relay.
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Use when a user says "summarise ecosystem results", "summarize this ty ecosystem report", "what changed in this ecosystem run?", or asks to summarise or summarize ty ecosystem results for a Ruff PR from a PR number, PR URL, GitHub ecosystem-results comment, or detailed HTML report.
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Summarizes audio content using AssemblyAI's LeMUR (Large Language Model for Audio Understanding) API. Chains the /v2/transcript endpoint with /lemur/v3/generate/summary for contextual audio intelligence.
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Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
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Summarize videos, audio files, and podcasts into key takeaways. Give it a YouTube/podcast URL or a local audio/video file — it transcribes locally (cached; repeat requests reuse the transcript) and distills the transcript into key points, summaries, or translations. Use when the user asks to summarize, get key points from, translate, or TL;DR any audio or video content.
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"Summarize and analyze earnings calls (法說會) including financial highlights, management commentary, guidance, and analyst Q&A key takeaways. Use this skill when the user needs to digest an earnings call transcript, extract key financial data and forward guidance, compare actual results vs consensus estimates, or prepare for an investor meeting — even if they say 'summarize this earnings call', 'what did management say about next quarter', 'did they beat estimates', or 'key takeaways from the 法說會'.".
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Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).
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Summarize support tickets, chats, and customer threads into issue, impact, status, owner, and next response. Use for customer service handoffs, escalation triage, and support backlog review.
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Summarize document-heavy inputs such as memos, policies, PDFs, research notes, proposals, and multi-document packets. Use when users need key points, obligations, questions, and action implications from documents.
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