Use the GitHub command-line tool to inspect issues, pull requests, and automated workflow runs. Check failed steps and logs, retrieve additional details through the API, and extract selected fields into structured results.
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Design and improve DeepTutor skills by turning concrete usage examples into reusable instructions. Learn how to write descriptions that signal when to use a skill, structure SKILL.md, and separate supporting reference material.
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Read, summarize, create, and edit Word documents in .docx format. Build reports with headings, tables, and images, replace text in existing files, or add tracked changes and comments for document review.
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Set up and manage DeepTutor from the command line, a text interface for running commands. Run learning tasks, build searchable document collections, manage sessions and notebooks, diagnose installation issues, and launch the server or Web app.
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Create PowerPoint presentations from outlines, update text, tables, charts, and images in existing slides, or extract slide text and speaker notes. Export decks to PDF or images when the required conversion tools are available.
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Read, create, and edit Excel workbooks, including formulas, formatting, charts, and multiple sheets. Clean CSV or TSV tables and prepare spreadsheet deliverables, with guidance on choosing fixed calculated values or formulas that update later.
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Extract text and tables from PDFs, create new documents, and reorganize pages. Use it to merge or split files, fill forms, add watermarks or password protection, and turn pages into images for visual inspection.
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Retrieve price and trading volume data for US, Hong Kong, and Canadian stocks, ETFs, and indices through Yahoo Finance. Also gather company profiles, financial statements, dividends, and ownership data for market research and historical strategy testing.
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Review trading rules across China A-shares, Hong Kong stocks, US stocks, and crypto markets. Use comparison tables and checklists to identify execution limits, short-selling constraints, trading hours, fees, and tax considerations when designing historical trading simulations.
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Backtest stock and cryptocurrency option strategies using theoretical prices derived from underlying prices. Simulate combinations of option positions, track profit and loss, and export Greeks, measures of sensitivity to price, volatility, and time.
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Analyze option strategies with profit and loss charts, breakeven points, and maximum risk calculations. Compare single options and combinations, and explore how underlying prices and volatility affect theoretical values for research and backtesting.
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Analyze public blockchain records to assess crypto market conditions. Combine network activity, large-holder transfers, decentralized finance liquidity, and valuation measures into a report with indicator comparisons, a composite score, and an interpretation of market signals.
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Generates buy, sell, or stand-aside signals from calendar patterns using price and volume data. Supports configurable months and weekdays, including combined conditions, for testing seasonal trading ideas against historical data.
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Analyze scheduled token releases, their recipients, and trading volume to estimate potential selling pressure. Review project treasury holdings, operating runway, and token supply growth to assess funding sustainability and the effect of dilution on staking yields.
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Turn academic papers and research reports into investment signals and trading strategies. Coordinate existing tools to extract formulas, implement rules, test them on historical data, store results, and monitor whether their effectiveness declines over time.
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Track USDT, USDC, and other stablecoins to assess capital entering or leaving crypto markets. Combine supply changes, issuance and redemption, exchange balances, transfer activity, and movements between blockchains into a structured liquidity report.
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Provides guidance for retrieving China A-share prices and trading volumes through the TDX protocol. The source is currently retired from automatic routing because servers stopped responding, with explicit selection retained for possible future recovery.
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Evaluate companies using projected cash flows, dividends, business segments, and comparisons with peers. Select suitable valuation methods, examine how assumptions change estimated value, and check for problems that can make a seemingly cheap stock misleading.
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Analyze crypto perpetual futures funding payments and spot–futures price differences to assess carry trades. Compare exchanges, identify crowded positions, and summarize potential returns alongside risks such as funding reversals and liquidation.
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Explain portfolio performance by separating the effects of sector allocation, stock selection, market factors, and timing. Compare results with a benchmark, assess risk-adjusted returns, and prepare a report showing where excess returns came from.
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Turn trading rules into Python code and configuration files, then test them against historical data. Review performance, position sizing, and trading costs, and revise strategies using the results produced by the backtest engine.
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Turn stock, industry, strategy, or backtest research into structured Markdown reports. Present conclusions, supporting data, ratings, risks, and recommendations using consistent tables and terminology, with PDF delivery supported through the specified rendering tool.
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Retrieve cryptocurrency prices, candlesticks, order books, funding rates, and open interest from OKX’s public API. Use spot, derivatives, and index data for market research without registering an account or configuring authentication.
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Check investment research for bias before searching and before writing conclusions. A short checklist broadens coverage beyond large companies and English sources, challenges bullish assumptions, and checks whether important figures are current.
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