Retrieve economic release schedules from FXMacroData and check event timing and importance. Use confirmed announcements to inform trade planning, position sizing, and follow-up reviews around inflation reports, employment data, and central bank decisions.
中文简介正在准备中。当前显示英语简介。
Fetch official FXMacroData macro release-calendar events for trade planning, macro regime checks, and event-risk filters. Use before CPI, NFP, GDP, PCE, retail sales, PMI, and central-bank decision windows.
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Retrieve official-source macro release-calendar events from FXMacroData. Use this skill when a trade plan needs event timing, confirmed release dates, or a top-tier macro risk check.
Run the calendar script:
python3 skills/fxmacrodata-calendar/scripts/fetch_calendar.py --currency usd --min-tier 1
Review events[] for top-tier releases.
Treat a nonzero exit as an unverified event-risk state, never as an empty
calendar. Only a successful response containing events: [] establishes
that no matching events were returned. The client accepts results only when
the response currency matches the request and data_quality confirms an
official, current, non-proxy, non-fallback, timestamp-complete,
point-in-time-safe source. Each event must include an announcement timestamp
and a non-empty release identifier.
Fold the event timing into the trade plan:
Set FXMACRODATA_API_KEY for authenticated FXMacroData endpoints. Public USD
calendar rows can be fetched without a key. The client uses the canonical
https://api.fxmacrodata.com/v1 endpoint and accepts --min-tier values 1,
2, or 3 only. Live calendar responses currently include market_tier; the
skill treats it as an extension field and requires integer values 1 through 3
for filtering, although the current CalendarReleaseRow OpenAPI schema does
not declare that field.
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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.
中文简介正在准备中。当前显示英语简介。
Assess how broadly US stock market gains are shared across stocks using public CSV data and optional charts. Produce English reports covering market conditions, trading signals, scenarios, and positioning for different investment timeframes.
中文简介正在准备中。当前显示英语简介。
Analyze chart images showing how broadly US stocks are participating in market trends. Assess medium-term conditions and short-term signals, then produce an English report with positioning guidance, alternative scenarios, and risks based on the visible data.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
Screen US growth stocks with William O'Neil's CANSLIM method, which evaluates seven factors including earnings, price strength, trading volume, and market direction. Receive ranked candidates with composite scores, factor breakdowns, market warnings, and data quality notes.
中文简介正在准备中。当前显示英语简介。
Combine three reports on crowded positions, failed reactions to news, and weekly price reversals into one trading setup status. Identify missing or invalid evidence and determine whether the setup is ready for planning.
中文简介正在准备中。当前显示英语简介。