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概要と使いどころ
Analyze code coverage and CRAP (Change Risk Anti-Patterns) scores to identify high-risk code. Use OpenCover format with ReportGenerator for Risk Hotspots showing cyclomatic complexity and untested code paths.
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。
Psychrometric Analysis Agent
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。
Cross-verify Claude-generated plans and code using OpenAI Codex and Google Gemini CLI. Provides code review, plan validation, and comparative analysis. Use when needing second opinions on Claude's code or plans, validating technical decisions, or seeking consensus from multiple AI models.
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。
Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
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。
Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.
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 markdown reports from issues. Filter by type, priority, epic, date range. Supports summary, detailed, progress, completion, velocity, and backlog analysis views.
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。
Expert research analyst specializing in comprehensive information gathering, synthesis, and insight generation. Masters research methodologies, data analysis, and report creation with focus on delivering actionable intelligence that drives informed 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。
Visual context analyzer for AI agents. Provides screenshots, accessibility scans, DOM snapshots, and element descriptions for web pages. Use when you need to see what a web page looks like, analyze accessibility issues, inspect DOM structure, or get detailed element information. Triggers on requests like "take a screenshot", "check accessibility", "what does this page look like", "analyze the UI", "inspect this element", or any visual/UI analysis task.
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。
Debug and troubleshoot ElevenLabs conversational AI agents and Twilio calls. Use when diagnosing agent issues, analyzing failed calls, troubleshooting audio problems, investigating conversation breakdowns, reviewing error logs, or optimizing underperforming agents. Includes transcript analysis, error diagnosis, and performance troubleshooting.
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。
Design and implement evaluation frameworks for AI agents. Use when testing agent reasoning quality, building graders, doing error analysis, or establishing regression protection. Framework-agnostic concepts that apply to any 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。
Appends relevant hashtags to journal entries based on content analysis. Intended for LLM execution.
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。
Create custom Claude Code sub-agents with specialized expertise and tool access. Use when you need to build reusable agents for specific tasks like code review, debugging, data analysis, or domain-specific 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。
Value investing analysis using Graham (NCAV/net-net/defensive-investor) and Buffett (economic moat/ROE/FCF) methodologies. Covers single-stock diagnostics and batch screening for both Graham cigar-butt and Buffett quality-compounder criteria. Runs cross-statement reconciliation before scoring. Data from Longbridge CLI first, MCP fallback, WebSearch only for genuine gaps. Triggers: "格雷厄姆", "巴菲特", "捡烟蒂", "烟蒂股", "NCAV", "净流动资产", "护城河", "价值投资", "安全边际", "深度价值", "撿煙蒂", "煙蒂股", "淨流動資產", "護城河", "安全邊際", "Graham", "Buffett", "cigar butt", "net-net", "NCAV screen", "moat", "value investing", "margin of safety", "deep value", "quality compounder", "價值投資", "深度價值", "防御型投资者", "防禦型投資者"
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Financial statements, business segments, dividends, valuation multiples (PE/PB/PS), industry comparison, operating data, corporate actions, company and executive profiles, cross-stock comparison, and valuation ranking via Longbridge. Also: DCF models, value investing screens (low PE/PB, margin of safety), and behavioral finance analysis frameworks. Triggers: "财报", "三表", "利润表", "资产负债", "现金流", "估值", "PE", "PB", "分红", "公司信息", "高管", "行业估值", "并购", "DCF", "内在价值", "低估值", "安全边际", "行为金融", "小盘成长", "专精特新", "主营业务", "业务构成", "收入结构", "业务分析", "是做什么的", "是干嘛的", "公司画像", "行业排名", "行业龙头", "市场份额", "收入占比", "业务结构", "財報", "估值", "分紅", "內在價值", "安全邊際", "主營業務", "業務構成", "收入結構", "行業排名", "行業龍頭", "financial report", "income statement", "balance sheet", "valuation", "dividend", "company info", "industry valuation", "DCF", "value screen", "behavioral finance", "main business", "business composition", "revenue structure", "what does XX do", "industry ranking", "market share", "利潤表", "資產負債", "現金流", "行業估值", "併購", "行為金融", "小盤成長"
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。
Technical analysis frameworks — candlestick patterns, Ichimoku cloud, technical indicators (RSI/MACD/EMA/Bollinger), harmonic patterns (Gartley/Bat/Butterfly/Crab), Elliott Wave, Chan Theory (缠论 bi/zhongshu/buy-sell points), Smart Money Concepts (BOS/FVG/Order Block), and Turtle Trading signals with ATR/Unit position sizing. Triggers: "技术分析", "K线形态", "蜡烛图", "一目均衡表", "RSI", "MACD", "布林带", "谐波形态", "艾略特波浪", "缠论", "分型", "笔", "中枢", "Smart Money", "BOS", "FVG", "海龟交易", "海龟信号", "K線形態", "蠟燭圖", "一目均衡表", "纏論", "ichimoku", "candlestick pattern", "K线形态识别", "形态识别", "识别K线", "识别形态", "harmonic", "Elliott Wave", "chan theory", "turtle trading", "SMC", "technical indicators", "技術分析", "海龜交易", "海龜信號", "諧波形態"
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。
Latest news articles, regulatory filings, community discussion topics for listed stocks, and SEC EDGAR filing analysis (10-K/10-Q/8-K/proxy/Form 4) via Longbridge. Triggers: "新闻", "公告", "资讯", "话题", "社区讨论", "SEC", "10-K", "10-Q", "8-K", "Form 4", "新聞", "公告", "資訊", "話題", "社區討論", "news", "filing", "announcement", "topic", "community", "SEC filing", "annual report", "quarterly report", "proxy", "insider filing", "regulatory rules", "监管规则", "涨跌停", "漲跌停", "T+1", "PDT rule", "熔断", "熔斷", "circuit breaker", "margin rules", "保证金", "保證金", "監管規則"
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。
Quantitative strategy frameworks: pairs trading/cointegration, volatility regime strategies, seasonality/calendar effects, multi-factor models (IC/IR), factor research and screening, correlation analysis, statistical methods (ADF/GARCH), strategy optimization, execution modeling, hedging, and ML-based prediction (sklearn). Also provides CLI access to run indicator scripts against K-line data. Triggers: "量化", "因子", "配对交易", "协整", "波动率策略", "季节性", "多因子", "IC", "机器学习", "对冲", "量化策略", "協整", "波動率策略", "季節性", "多因子", "對沖", "quant", "pairs trading", "cointegration", "volatility strategy", "seasonality", "multi-factor", "factor model", "IC IR", "machine learning", "hedging", "walk-forward", "配對交易", "機器學習", "因子選股"
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。
Builds an ideal customer profile from evidence: case studies, testimonials, customer logos, solutions pages, reviews and any sales notes you have. Produces market sizing layers, firmographic segments, a champion and an economic buyer persona, a negative ICP, intent signals, customer proof points and a voice-of-customer section in the buyers' own words, every claim sourced. Triggers: "ICP research", "ideal customer profile", "who are our customers", "customer segments", "buyer personas", "who should we target". Run after /company-context. Not for competitor analysis (use /competitor-research) or call transcript patterns (use /win-loss).
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。
Researches a company from its website and public sources and writes a company profile: what it sells, who buys it, traction, funding, team, hiring, tech stack, key people, red flags and the gaps you still need to fill, every claim tagged with a source and a confidence level. Use it as the first file in a marketing context folder, or to prep a discovery call or qualify a prospect. Triggers: "company research", "company background", "company context for", "qualify this prospect", "discovery call prep", "account brief", or a company URL handed over for research. Not for competitor analysis (use /competitor-research) or customer profiles (use /icp-research).
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。
Researches one B2B SaaS competitor across 13 dimensions (company, product, ICP, pricing, reviews, content, launches, search and AI visibility, tech stack, hiring, go-to-market, social, paid ads) and writes a sourced dossier with an executive summary, a threat level, strengths and weaknesses, and a data gaps section. Run it once per competitor, then compare. Triggers: "competitor analysis", "competitor research on", "what is [competitor] doing", "compare us to", "competitive landscape", "battlecard prep". Run after /company-context and /icp-research. Not for researching your own company (use /company-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。
Extract voice patterns from existing content (website, blog, social, sales-call transcripts) and codify into voice rules. Produces voice analysis + voice guidelines (rules per pattern + violation pattern + fix template). Writes to marketing/brand/brand-voice.md as the canonical voice rules every content skill reads. Triggers - "tone of voice", "brand voice", "voice guidelines", "TOV audit", "writing rules", "extract 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。
Run deep research on a single competitor. Produces a dossier with executive summary, position + messaging, status-quo alternatives, key differentiators, pricing position, where-they-win / where-they-lose, threat assessment, and what to watch. Writes to marketing/competitors/MMYY-{competitor-slug}.md. Triggers - "competitor research", "competitive analysis", "research competitor X", "battlecard prep", "analyze [competitor name]
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 research workflow skill for investment analysts and policy researchers. Three scope modes the user picks at trigger time — light (4-5 page decision memo, ~15 min, 0 charts), medium (12-15 page topic brief, ~1 h, 6-10 charts), heavy (flagship report 30-40 pages / 15k+ words, ~2-3 h, 25-35+ charts, multi-stage workflow, multi-LLM, PDF + Word + WeChat + HTML derivations). Reports default to English; the AI replies in the user's chat language. Battle-tested on real macro/policy/equity reports (e.g. Saudi Vision 2030 deep-dive). Triggers when user types /analyst-research, /flagship-research, or describes needs like "research report", "topic analysis", "investment research", "做研报", "投研报告", "主题分析", "深度分析", "policy assessment", "industry deep-dive". Not for: pure news commentary (use topic-brief), slide decks (use deckster-slide-generator), one-shot Q&A.
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。
System bottleneck identification, resource optimization, and performance analysis
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。