「extract」の検索結果

Slackの同期データからメンションを検索しTODO/タスクを抽出・ステータス判定するスキル。 「Slackからタスク抽出」「TODO確認」「メンション確認」等のリクエストで発動。

Convert webinar recordings into blog posts, social snippets, email series. Extract key quotes, statistics, and soundbites.

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。

Transform webinar recordings into multiple content assets including blog post series, social media snippets, infographic ideas, email sequences, and sales one-pagers. Extracts key moments, quotes, and insights for maximum content ROI. Use when users need to repurpose webinars, video content, or live presentations into multi-channel marketing materials.

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。

Takes meeting transcripts, extracts action items with owners and deadlines, detects implicit commitments, generates structured meeting summaries, and outputs task files compatible with Linear, GitHub Issues, and other project management tools.

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 meeting transcripts to extract decisions, action items, blockers, sentiment, and generate follow-up emails. Use when user provides meeting notes, transcripts, or recordings and needs structured summaries or action tracking.

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 targeted prospect lists by analyzing LinkedIn profiles, extracting job titles, companies, locations, and recent activity. Identifies decision-makers, tracks job changes for warm outreach, and enriches contact data. Use when users need to find prospects, build lead lists, or track decision-maker movements.

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 quarterly business review from a client folder -- reports, usage exports, support tickets, meeting notes, emails. Extracts delivered value with receipts, surfaces risks before the client does, and drafts the QBR narrative plus expansion asks. For agencies, consultancies, and CS teams.

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。

Extract key concepts from any content and create spaced-repetition flashcards. Multiple formats: Anki-compatible, printable PDFs, interactive web.

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。

Extract and analyze data from invoices, receipts, bank statements, and financial documents. Categorize expenses, track recurring charges, and generate expense reports. Use when user provides financial PDFs or images.

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。

Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms. Performs sentiment analysis, identifies pain points, extracts feature feedback, generates marketing claims, and compares competitor reviews. Use when users need review analysis, competitive intelligence, or customer feedback insights.

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。

Analyzes a company's content to extract and codify their brand voice into a comprehensive style guide. Reads website copy, blog posts, emails, and social media to identify tone, vocabulary patterns, sentence structure, personality traits, and word preferences. Generates a brand-voice-guide.md and reviews new content against it.

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 ALL past Claude conversations to build a living 'User Manual About You'. Extract writing style, business context, goals, preferences, and patterns. Make all other skills smarter with context.

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 and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from multiple sources and provides enriched contact details. Use when users need to find contact information, build prospect lists, or enrich existing contact 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。

Review contracts for concerning clauses, extract key terms, compare to standard terms, and flag unusual provisions. Use when user needs contract review, legal document analysis, or agreement evaluation.

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。

Sweep a contracts folder and extract every renewal date, auto-renew clause, notice window, and price-escalation term into a renewal calendar -- then create calendar reminders ahead of each notice deadline via Cowork's calendar write tools. The skill that stops auto-renewals from ambushing you.

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。

Extracts writing style patterns from exemplar text into a reusable profile. Use when creating a style guide or learning a specific author's voice.

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。

Analyzes changesets with risk scoring, categorization by type and impact, and release note preparation. Use when extracting insights from raw change 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 applying a published cohort study's methodology to a different database. Extracts the design from the source paper, maps variables to the target database with a harmonization table, generates the analysis code and reports every forced deviation.

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 references in a .bib file (often from /search-lit) should land in Zotero and Obsidian. Syncs them to the Zotero library, writes Obsidian literature notes and extracts cross-cutting concept notes once enough accumulate. A folder of PDFs is /obsidian-paper-vault.

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Use when designing or auditing how an LLM or multimodal LLM is evaluated on a clinical task (report generation, VQA, text extraction). Covers reference standard, clinical-efficacy metrics beyond BLEU/ROUGE, hallucination, contamination and prompt sensitivity. Imaging models are /model-assessment.

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 turning a folder of research PDFs into Obsidian notes, even if Obsidian is not named. Writes one templated literature note per paper and extracts cross-linked atomic concept notes, never overwriting existing ones. A .bib or Zotero library is /lit-sync.

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 a systematic review and meta-analysis, DTA or intervention. Covers PROSPERO protocol, search, screening, extraction, risk of bias (QUADAS-3, RoB 2, ROBINS-I), bivariate/HSROC or random-effects pooling, forest plots, heterogeneity and PRISMA reporting. Topic scouting is /ma-scout.

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 you have a spec, design doc, structured plan, or prompt_plan and need to generate a pipeline Graphviz DOT file for headless autonomous building. The agent reads the spec, extracts build pipeline phases, determines tech stack, asks about human gates and model preferences, generates a validated DOT digraph with rich self-contained prompts, and saves it to the project root. Handles any language or framework.

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 face_recognition to detect faces, extract landmarks and encodings, compare identities, run the face_recognition and face_detection CLIs, and troubleshoot dlib/model installation.

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。