「summarize」の検索結果

Researches a topic by breaking it into subtopics, gathering factual information with reasoning, and producing a structured summary with key findings and open questions. Use when the user asks to research, investigate, look up, summarize a topic, or says 'what is known about...' or 'learn about...'

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Write a structured interview guide — warm-up, core exploration, and wrap-up. Use before running interviews. For analysing what comes back, use `summarize-interview`.

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Turn one interview transcript into themes, supporting quotes, and action items. Use immediately after a session. For synthesising many sessions at once, use `affinity-diagram`.

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Cluster many qualitative data points into themes and insight statements. Use when synthesising across multiple sessions or sources. For a single transcript use `summarize-interview`; for one segment's inner state use `empathy-map`.

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。

Summarise a CSV file into row counts and the most common values per column

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Summarize deep research results into markdown report, cover all fields, skip uncertain values.

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Structure and data sources for the weekly inventory report. Load this when the task is "weekly report", "Monday report", or "summarize inventory status".

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Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Use this skill whenever the user mentions changelogs, release notes, version updates, "what changed", product updates, app store descriptions, or needs to summarize recent development work for non-technical audiences.

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Generate standardized figure legends for scientific figures and charts; use when preparing publication-ready legends that summarize design, variables, sample size, and key statistical notes.

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Transform lengthy academic papers into concise, structured 250-word abstracts.

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A medical-research-native literature reading skill for users with clinical, bioinformatics, translational, and basic experimental backgrounds. Use this skill whenever a user wants to read, analyze, critique, or interpret a medical or scientific paper — whether they provide a PDF, abstract, DOI, PMID, or just a title. Triggers include requests like \"analyze this paper\", \"critique this study\", \"is this a strong paper?\", \"give me similar studies\", \"prepare me for journal club\", \"help me understand this bioinformatics paper\", \"what are the weaknesses here?\", or \"turn this into a mind map\". Also activate for any downstream deliverables such as journal club kits, comparison tables, PI decision briefs, replication starters, or follow-up experiment designs. Do NOT treat as a generic summarizer — this skill performs structured evidence-type classification, track-specific critical appraisal, interpretation-boundary judgment, and research-grade follow-up generation.

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Summarize authored commits over a user-specified time period into a concise update

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Fetch and summarize review comments from the active pull request

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。

Structured literature search + synthesis with citation extraction, thematic clustering, and gap identification. Use when user says "find papers on X", "do a lit review", "what's the literature on...", "summarize what we know about...", "where's the gap in this field", "review recent work on Y". Produces a written review with BibTeX-ready citations. Uses WebSearch/WebFetch for recent work.

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视频内容逐字稿提取专用 skill。Use when the user provides a 抖音 or 小红书 URL and asks for逐字稿、视频转文字、听写视频或提取口播内容。Only extract transcript content; do not use this skill as the production subtitle clock, and do not summarize, rewrite, translate, title, or start production. Uses qushuiyin plus Paraformer ASR.

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Scrape BOSS直聘 (job listing site) via Chrome CDP. Searches jobs by keyword/city/filters, fetches JD details, outputs structured JSON/CSV with plaintext salary, and can summarize scraped results into a job-market prompt. Use when user wants to search/analyze jobs on BOSS直聘 or zhipin.com.

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Reads or exports the COMPLETE transcript of a Claude.ai web conversation — private /chat/... and public /share/... links — via Claude.ai's internal API in the user's logged-in Chrome, plus its files. Use when the user pastes a claude.ai link and asks to read, summarize, export, archive, or extract it — "读这个对话", "导出网页版对话", "拉到本地". Local sessions: read-claude-code-history; exported files: claude-export-txt-better.

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Turn interview notes into a structured candidate scorecard and hire recommendation. Use when asked to write an interview scorecard, a candidate evaluation, an interview debrief, or to summarize feedback into a hire/no-hire call. Produces a per-competency assessment with evidence and ratings, an overall recommendation with confidence, and the open questions for the next round — evidence-based, bias-aware, and decision-ready.

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Write a one-page briefing note that gets a busy principal up to speed fast. Use when asked to brief a minister/executive/official, prepare a briefing note or read-ahead, or summarize an issue for a decision or meeting. Produces a tight, single-page note: purpose, background, key facts/considerations, and a recommendation or the decision sought — scannable in two minutes.

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Write a PRD for an AI-powered feature, covering the things normal PRDs miss. Use when asked to spec an AI/LLM feature, write a PRD for a feature that uses a model, or plan an AI capability (assistant, summarizer, generator, classifier). Produces an AI feature PRD — problem & UX of uncertainty, model approach, eval criteria, guardrails, fallback behaviour, the data flywheel, and cost/latency budget.

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Summarize AI conversation histories for a specified date or period. Use for daily work recaps and cross-tool activity summaries.

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Consolidate all SAST vulnerability results from the sast/ folder into a single final report ranked by severity and confidentiality impact. Reads all *-results.md files and produces sast/final-report.md. Run after all vulnerability detection skills complete. Use when asked to generate a final report, consolidate findings, or summarize security results.

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Use when the user wants to read, search, summarize, draft or triage their Apple Mail / Gmail / Outlook / iCloud email in Apple Mail on macOS. Powered by LMCP's Mail tools, which are macOS-only.

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Use only after explicit Codex `$superloopy:superloopy-research` or Claude Code `/superloopy:superloopy-research` invocation, a research task started with a leading `loopy` or `루피` (such as `loopy research`), or an active Superloopy loop explicitly routing a research deliverable here. Evidence-backed Superloopy research orchestration with automatic advisory usage targets, parallel read-only lanes, per-retrieval verdicts, graded and dated sources, empirical verification, a priced claim ledger, cited synthesis, and optional reports. Do not activate from research, investigate, look-up, summarize, deep-dive, report, or similar vocabulary alone, in any language; ordinary questions, debugging, and implementation context-gathering stay with their primary workflows.

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。