Check workflows defined in CLAUDE.md for missing skills, incompatible JSON data formats, and inconsistent file names. Produce Markdown and JSON reports identifying broken handoffs, with an optional dry run using generated sample data.
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Screen US stocks for potential three to five day momentum moves using price gains, trading volume, and daily price ranges. Get rated candidates with entry and stop references, risk distances, and rejection reasons for manual review.
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Turn Stockbee Momentum Burst screening candidates into a study log. Track three-day and five-day returns, favorable and adverse price moves, and stop hits, then compare setup groups to learn from successes and failures.
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Screen futures markets for unusually crowded speculative positions using COT reports, which track traders’ holdings. Compare three-year and 26-week positioning measures, produce ranked reports, and identify markets for further contrarian research without generating trade signals.
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Turn daily US stock prices, trading volume, and market hypotheses into prioritized research tickets for buying strategies. Export supported candidates as strategy files and check compatibility before handing them to trade-strategy-pipeline for historical testing.
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Analyze dated strategy returns to separate baseline exposure from performance beyond that baseline. Test stability across time and alternative comparisons, then produce JSON and Markdown reports showing how strong or fragile the evidence is.
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Assess near-term U.S. equity market top risk using six indicators, including selling pressure, weakening leaders, and defensive sector rotation. Generate a heuristic score, risk zone, and reports to inform reviews of equity exposure over two to eight weeks.
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Organize US dividend tax planning by classifying distributions, checking holding periods, and comparing taxable and tax-advantaged account placement. Produce holding-level tables, placement rationales, and unresolved questions for review with a tax professional.
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Compare options strategies using theoretical prices, profit and loss simulations, and sensitivity measures that show how prices respond to market changes. Explore earnings scenarios, maximum losses, and position sizes with manual inputs or optional FMP data.
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Test a trading rule against historical price and volume data with manifoldbt. Calculate completed-trade statistics, including win rate, average gains and losses, and maximum drawdown, while accounting for costs and preparing measured inputs for backtest-expert.
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Find US-listed dividend growers with at least 1.5% yield, 12% annualized dividend growth, and RSI at or below 40, an indicator of recent price weakness. Rank candidates using dividend sustainability, financial quality, and price indicators.
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Check English and Japanese market reports for suspicious price scales, instrument notation, date and weekday mismatches, allocation totals, and units. Generate readable and machine-readable findings for human review without automatically blocking publication.
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Screen stocks after earnings announcements using five factors: price gaps, prior price trends, trading volume, and positions relative to two moving averages. Compare candidates with scores out of 100, A–D grades, and JSON and Markdown reports.
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Find stock pairs whose price relationship may return toward its historical average. Analyze correlation, test for a lasting statistical relationship, and measure current price gaps to produce pair candidates, entry and exit conditions, and position sizing guidance.
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Monitor dividend holdings for cuts, weakening finances, and filing-related warning signs. The skill assigns OK, WARN, or REVIEW states and creates evidence-backed reports and review tickets for human decisions, without automatically selling holdings.
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Combine market breadth, economic conditions, sector trends, and institutional flows into a one-page equity allocation summary. Review a recommended allocation ceiling, growth-versus-value preference, market participation, action recommendation, and confidence level.
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Plan and assess backtests, which test trading rules against historical data. Examine sensitivity to rule changes, trading costs, and data bias, then use supplied performance metrics to generate a structured evaluation with reasons that block adoption.
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Calculate share counts for long stock trades using account size, acceptable loss, and entry and stop prices. Compare sizing methods and apply position or sector limits, with reports showing trade value and risk.
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Review agent skills with repeatable automated checks and a separate LLM assessment of content and code. Combine both scores into JSON and Markdown reports, with concrete improvement items when the final score falls below 90.
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Assess crypto market conditions with six measures covering Bitcoin trends, altcoin participation, leverage, and momentum. Generate a 0–100 score and a market posture report using free public data or an offline snapshot, without API keys.
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Turn VCP screening results, which identify narrowing price swings, into breakout trade plans. Calculate entry, stop-loss, target prices, and position sizes using worst-case entries, while applying portfolio risk limits and producing Alpaca-compatible order templates.
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Check whether a market with heavily one-sided positioning moved against news that should have favored those traders. The skill tests price reactions statistically and produces a verdict with event evidence, including an insufficient-evidence result when needed.
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Check recorded trading losses and losing streaks against account-level limits to assess whether new trades should proceed. Generate a decision report with triggered rules, cooldown periods, and data-quality warnings using local records without external APIs.
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Analyze historical stock prices to measure how long declines from local peaks to troughs lasted and how deep they were. Generate interactive HTML histograms and statistical reports to compare correction durations across sectors and company sizes.
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