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概要と使いどころ
CRE Asset Management analysis suite — 9 specialist skills for post-acquisition multifamily operations including annual budgeting, monthly variance analysis, rent collection, renewal decisions, lease-up tracking, capex execution, NOI improvement, hold/sell/refi scenario analysis, and quarterly asset review memos.
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 adding, importing, moving or loading textures, models, audio or scenes - per-platform compression, atlases, LODs, async loading per engine, engine metadata files (.meta, .import, .uid, .uasset), Git LFS, and asset validation tests.
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。
用户在评估不同资产类别（货币/黄金/房产/股票/加密等）的长期价值，或需要理解某类资产的根本经济属性时。 语言信号:"黄金值不值得投"/"比特币有没有价值"/"房产vs股票哪个好"/"为什么持有现金会亏" 不适用于:不需要跨资产类别比较的纯个股分析。
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。
Check the health of a data table/asset using Monte Carlo. Activates on "how is table X", "check health of X", "is X healthy", "status of X", "check on X table", or any health/status question about a data asset.
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。
Generate per-asset visual specifications and AI generation prompts from GDDs, level docs, or character profiles. Produces structured spec files and updates the master asset manifest. Run after art bible and GDD/level design are approved, before production begins.
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。
Audits game assets for compliance with naming conventions, file size budgets, format standards, and pipeline requirements. Identifies orphaned assets, missing references, and standard violations.
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。
Generates placeholder .aseprite files from asset specs using the Aseprite MCP. Reads asset specs and art bible, creates sprites with correct dimensions/palette/layers, exports PNGs. Run after /asset-spec has produced specs and /art-bible exists.
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。
Classify curriculum content into Know, Understand, and Do categories to align teaching and assessment approaches. Use when planning units, writing objectives, or selecting assessment methods.
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。
Select the right formative assessment technique for a specific learning moment, purpose, and age group. Use when choosing how to check understanding during, between, or after lessons.
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。
When the user wants to find, qualify, and build a list of prospects to reach out to — across B2B SaaS, general B2B, or local small businesses. Also use when the user mentions "prospecting," "build a prospect list," "find prospects," "find leads," "lead gen list," "find SaaS companies that," "find B2B companies," "find local businesses," "ICP-fit accounts," "who should we go after," "outbound list," "target account list," "find clients near me," "businesses without websites," "prospect research," or "qualified leads." Use this for the list-building and qualification phase. For writing the outbound copy after the list is built, see cold-email. For deep competitive research on specific accounts, see competitor-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。
Search free commercial-use creative assets across multiple online sources — photos, illustrations, icons, video footage, music, sound effects, and fonts. Use when the user needs to find assets for videos, PPTs, articles, or any content creation. Trigger on phrases like "find me a photo of", "search for icons", "I need background music", "find video footage", "search fonts", "找一张图片", "搜素材", "帮我找图标/视频/音乐/字体". Covers Pexels, Unsplash, Pixabay, Iconify, Freesound, Google Fonts and more — with API-backed search where available.
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。
Evaluates environmental liability exposure with remediation cost estimation, regulatory compliance requirements, and insurance coverage assessment. Use when analyzing environmental liabilities, estimating cleanup costs, or assessing environmental risk.
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。
Activates Warren Buffett's complete investment thinking system. The following scenarios must trigger it: analyzing any stock or company, evaluating investment opportunities, interpreting financial reports/annual reports/shareholder letters, assessing business moats or competitive advantages, evaluating management quality and integrity, making buy/hold/sell decisions, understanding core value investing concepts (compounding/intrinsic value/margin of safety/circle of competence/Mr. Market), analyzing any industry (insurance/banking/consumer/media/energy/railroads/technology), handling capital allocation/buybacks/dividends questions, assessing market sentiment and macro risks, exploring when to sell, analyzing institutional imperative or management behavior. Even if the user does not mention "Buffett," proactively trigger whenever the topic involves investment analysis, business quality assessment, or investment decision-making.
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。
Assesses physical and transition climate risk for CRE properties and portfolios. Translates hazard exposure (flood, wind, wildfire, extreme heat, sea level rise) and regulatory/market shifts into financial impacts on NOI, cap rates, insurance costs, and tenant demand. Produces dollar-denominated risk, not abstract hazard scores.
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。
Lee Cronin's Assembly Theory for molecular complexity measurement and life detection via assembly index computation.
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。
Assesses agent capabilities by analyzing agent files and determining what tasks they can handle. Use when you need to evaluate if an existing agent can handle a task or if a new agent is needed. Reviews agent descriptions, skills, and workflows to determine capability match.
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。
Dissect the current or given task plan, treated as an epic, domain-wise and logically into cohesive parts and materialize each part as its own separate task plan. Use when the user calls to "dissect", "split", "break up", or "decompose" a large "task" or "plan".
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。
Dissect the current Git change set, treated as an epic, domain-wise and logically into cohesive parts and materialize each part in its own dedicated Git WorkTree. Use when the user calls to "dissect", "split", "break up", or "decompose" a large change set into atomic, separately committable parts.
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。
End to end Product Hunt launch skill for developer tools. Generates listing assets (tagline, description, maker comment, visual asset spec, social proof) and a dated launch plan with workstreams, asset inventory, day of runsheet, and post launch sequence. Use when: prepare a Product Hunt launch, plan a PH launch, write PH listing copy, build PH launch checklist, generate PH launch plan.
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。
Personal AI Infrastructure (PAI) - PAI System Template MUST BE USED proactively for all user requests. USE PROACTIVELY to ensure complete context availability. === CORE IDENTITY (Always Active) === Your Name: [CUSTOMIZE - e.g., Kai, Nova, Atlas] Your Role: [CUSTOMIZE - e.g., User's AI assistant and future friend] Personality: [CUSTOMIZE - e.g., Friendly, professional, resilient to user frustration. Be snarky back when the mistake is user's, not yours.] Operating Environment: Personal AI infrastructure built around Claude Code with Skills-based context management Message to AI: [CUSTOMIZE - Add personal message about interaction style, handling frustration, etc.] === ESSENTIAL CONTACTS (Always Available) === - [Primary Contact Name] [Relationship]: email@example.com - [Secondary Contact] [Relationship]: email@example.com - [Third Contact] [Relationship]: email@example.com Full contact list in SKILL.md extended section below === CORE STACK PREFERENCES (Always Active) === - Primary Language: [e.g., TypeScript, Python, Rust] - Package managers: [e.g., bun for JS/TS, uv for Python] - Analysis vs Action: If asked to analyze, do analysis only - don't change things unless explicitly asked - Scratchpad: Use ~/.claude/scratchpad/ with timestamps for test/random tasks === CRITICAL SECURITY (Always Active) === - NEVER COMMIT FROM WRONG DIRECTORY - Run `git remote -v` BEFORE every commit - `~/.claude/` CONTAINS EXTREMELY SENSITIVE PRIVATE DATA - NEVER commit to public repos - CHECK THREE TIMES before git add/commit from any directory - [ADD YOUR SPECIFIC WARNINGS - e.g., iCloud directory, company repos, etc.] === RESPONSE FORMAT (Always Use) === Use this structured format for every response: 📋 SUMMARY: Brief overview of request and accomplishment 🔍 ANALYSIS: Key findings and context ⚡ ACTIONS: Steps taken with tools used ✅ RESULTS: Outcomes and changes made - SHOW ACTUAL OUTPUT CONTENT 📊 STATUS: Current state after completion ➡️ NEXT: Recommended follow-up actions 🎯 COMPLETED: [Task description in 12 words - NOT "Completed X"] 🗣️ CUSTOM COMPLETED: [Voice-optimized response under 8 words] === PAI/KAI SYSTEM ARCHITECTURE === This description provides: core identity + essential contacts + stack preferences + critical security + response format (always in system prompt). Full context loaded from SKILL.md for comprehensive tasks, including: - Complete contact list and social media accounts - Voice IDs for agent routing (if using ElevenLabs) - Extended security procedures and infrastructure caution - Detailed scratchpad instructions === CONTEXT LOADING STRATEGY === - Tier 1 (Always On): This description in system prompt (~1500-2000 tokens) - essentials immediately available - Tier 2 (On Demand): Read SKILL.md for full context - comprehensive details === WHEN TO LOAD FULL CONTEXT === Load SKILL.md for: Complex multi-faceted tasks, need complete contact list, voice routing for agents, extended security procedures, or explicit comprehensive PAI context requests. === DATE AWARENESS === Always use today's actual date from the date command (YEAR MONTH DAY HOURS MINUTES SECONDS PST), not training data cutoff date.
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。
Streams audio from Twilio Media Streams over WebSocket to AssemblyAI real-time transcription, extracting speaker-diarized transcripts with word-level timestamps. Triggers entity detection and sentiment analysis via AssemblyAI LeMUR on completed call segments. Results are pushed to HubSpot or Salesforce contact records via their REST APIs.
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 structured intelligence from audio using the AssemblyAI API with sentiment analysis, entity detection, topic modeling, and auto-chapter generation. Uses the assemblyai Python SDK for transcript processing pipelines.
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。
Transcribes audio and generates auto-chapters with summaries using AssemblyAI's /v2/transcript endpoint with auto_chapters=true. Extracts key topics, sentiment analysis, and content safety labels via AssemblyAI SDK.
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。
Assesses energy transition investments with battery storage, grid modernization, EV charging, and hydrogen infrastructure analysis. Use when modeling energy transition assets, evaluating storage economics, or analyzing grid infrastructure.
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。