Runs maximum-saturation research with a cooperating team, claim-graph gating, and a cited, QA'd deliverable. Use when the user explicitly asks for research or a deep investigation, including any 'ulw' research wording.
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。
調査、論文、教育、資格学習(4,139 件)
概要と使いどころ
Runs maximum-saturation research with a cooperating team, claim-graph gating, and a cited, QA'd deliverable. Use when the user explicitly asks for research or a deep investigation, including any 'ulw' research wording.
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。
Volatility Smile reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Hedging Scenarios reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Market Sentiment reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Unusual Options Activity reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Earnings IV Crush reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Put-spread Backtest reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Payoff Simulation reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Volatility Surface reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Find published research and institutional views with sources, dates and related assets. Use when the user asks to research reports with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Compare option candidates and score components, with funding, expiry and assignment risks. Use when the user asks to options strategies with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Supply-chain Bottlenecks reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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 report views, ratings, key assumptions and risks with sources and dates. Use when the user asks to research report breakdown with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Compare research records you provide to see changes in facts, scores and judgments. Use when the user asks to investment review with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Greeks reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Connect fundamentals, sentiment and risk to supporting and opposing evidence. Use when the user asks to stock opportunities with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Prediction Markets reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
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。
Company discovery and deep research skill. Researches a company's product and ICP, discovers target companies to sell to using Browserbase Search API, deeply researches each using a Plan→Research→Synthesize pattern, and scores ICP fit — compiled into a scored research report and CSV. Supports depth modes (quick/deep/deeper) for balancing scale vs intelligence. Use when the user wants to: (1) find companies to sell to, (2) research potential customers, (3) discover companies matching an ICP, (4) build a target company list, (5) do market research on prospects. Triggers: "find companies to sell to", "company research", "find prospects", "ICP research", "target companies", "who should we sell to", "market research", "lead research", "prospect list".
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。
Event prospecting skill. Takes a conference / event speakers URL, extracts the people, filters their companies against the user's ICP, then deep-researches only the speakers at ICP-fit companies. Outputs a person-first HTML report where each card answers "why should the AE talk to this person?" with all public links and a one-click DM opener. Use when the user wants to: (1) find leads at a specific conference, (2) prep for an event, (3) research event speakers, (4) build a target list from a sponsor/exhibitor page, (5) scrape conference speakers and rank by ICP fit. Triggers: "find leads at {event}", "research speakers at", "prospect this conference", "stripe sessions leads", "ai engineer summit prospects", "event prospecting", "scrape conference speakers", "who should I meet at".
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。
Self-improving browser automation via the auto-research loop. Iteratively runs a browsing task, reads the trace, and improves the navigation skill (strategy.md) until it reliably passes. Supports parallel runs across multiple tasks using sub-agents. Use when you want to build or improve browser automation skills for specific website tasks.
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 preparing manuscripts, conference papers, or academic posters that need venue-specific templates, LaTeX style files, author guidelines, page limits, anonymity rules, camera-ready formatting, or submission compliance 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。
Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.
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。
Stage-based submission checklists for papers/reports: pre-submission, submission, revision/rebuttal, camera-ready. Includes templates (cover letter, rebuttal matrix) and quality gates.
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。
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.
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。