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Provides stock prices, fundamentals, financial statements, technical indicators, news, market assessments, screening, and AI-derived investment signals.
기능
도구
19
도구
get_earnings_calendar
Get Earnings Calendar
Upcoming earnings dates for stocks in the Stocklake universe.
- days: look-ahead window in days (default 7, max 30)
- Returns: { window_days, from_date, to_date, count, results[] }
- Each result: symbol, name, sector, market_cap, price, rsi,
earnings_date (ISO UTC), is_estimate, eps_trailing, eps_forward
- Sorted by earnings_date ascending.
- Dates sourced from market data — treat is_estimate=true dates as approximate.
Available to all tiers.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'days': {'type': 'integer', 'default': 7, 'description': 'Look-ahead window in days (default 7, max 30).'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_earnings_intelligence
Get Earnings Intelligence
Upcoming earnings with AI context — AI scores, verdicts, and risk factors per stock.
Combines the earnings calendar with AI pipeline data to surface which upcoming
earnings events are worth monitoring.
Parameters:
- days_ahead: look-ahead window in days (default 14, max 30)
- sector: filter to one sector (e.g. "Technology")
- min_ai_score: only return stocks with AI score >= this value, 0-100 (optional).
Renamed 2026-08-24 from the retired 0-10 min_flag_score — gates on the same
stock_ai_summary.py ai_score field the response already returns, rather than
the raw legacy flag_score field, which is no longer part of this fleet's
public vocabulary at all. Applied server-side before `limit` truncates the
result — a stock with a qualifying score always counts against `limit` ahead
of one without, rather than being cut off first for reporting later in the
earnings window.
- limit: max results to return (default 25, max 25). Each returned ticker
counts as one call toward your daily limit — see the docs' rate-limit section.
Returns per stock (sorted by earnings_date ascending):
- earnings_date: ISO UTC timestamp · is_estimate: whether date is estimated
- symbol, name, sector, price, rsi, market_cap
- eps_trailing, eps_forward (earnings expectations context)
- ai_verdict (positive/neutral/negative, from nightly AI pipeline)
- ai_score (0-100) / ai_score_band (Weak/Moderate/Strong/Very
Strong) — stock_ai_summary.py's own composite score, same 0-100 scale/band
convention as signals.signal_score but a distinct field/pipeline; null if
this stock has no ai_summary doc yet.
- ai_risks: top 2 AI-identified risk factors
- analyst_rating, analyst_target
Pro tier only — AI pipeline cost attached.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 25, 'description': 'Max results to return (default 25, max 25). Each returned ticker counts as one call toward your daily limit.'}, 'sector': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': 'Filter to one sector, e.g. "Technology".'}, 'days_ahead': {'type': 'integer', 'default': 14, 'description': 'Look-ahead window in days (default 14, max 30).'}, 'min_ai_score': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'default': None, 'description': 'Only return stocks with AI score >= this value, 0-100 (optional). Renamed 2026-08-24 from the retired 0-10 min_flag_score — gates on the same stock_ai_summary.py ai_score field the response already returns. Applied server-side before limit truncates the result, so a qualifying stock always counts against limit ahead of one without.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_economic_calendar
Get Economic Calendar
Upcoming and recently-released macro/economic events -- interest rate
decisions, CPI, GDP, PMI, unemployment, payrolls, retail sales, and more --
sourced from Yahoo Finance, the one calendar source confirmed safe for
external exposure (a second internal-only source, Trading Economics,
carries a ToS caveat and is not exposed here).
Two buckets:
- released_recent: events with a real reported value, within the last
`lookback_days` days. Every item here carries a real `actual` value
(never blank) plus `diff` (actual minus previous -- a plain arithmetic
difference, never a beat/miss or consensus judgment; Yahoo doesn't
provide point-in-time consensus data).
- upcoming: not-yet-released events within `days`. No item here ever
carries an `actual` value.
Every item in both buckets carries `key_event`: true for the handful of
event types that reliably move markets on their own (rate decisions, CPI,
GDP, headline Non-Farm Payrolls) -- an event-TYPE flag only, never a
beat/miss or directional judgment on the number itself. Set
`key_events_only=true` to filter to just these, or `major_only=true` to
restrict to the 8 largest economies.
Both buckets sort major-economy-first, then by recency -- truncating to
`limit` should never lose a US/EU/UK/JP/CN/DE/FR/CA print to an older or
thinner-economy one.
Pro tier only.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'days': {'type': 'integer', 'default': 3, 'description': 'Look-ahead window in days for upcoming events (default 3, max 14).'}, 'limit': {'type': 'integer', 'default': 20, 'description': 'Max results per bucket, released_recent and upcoming each capped independently (default 20, max 50).'}, 'major_only': {'type': 'boolean', 'default': False, 'description': 'Restrict to the 8 largest economies (United States, Euro Area, United Kingdom, Japan, China, Germany, France, Canada). Default false returns all countries.'}, 'lookback_days': {'type': 'integer', 'default': 2, 'description': "Look-back window in days for recently-released events (default 2, max 7). Yahoo's own actual value has a confirmed ~1-day reporting lag, so a same-day-only window misses real releases -- keep this at 2+ to reliably see them."}, 'key_events_only': {'type': 'boolean', 'default': False, 'description': 'Restrict to the small subset of event types that reliably move markets on their own: interest rate/rate decisions, CPI, GDP, and headline Non-Farm Payrolls. Default false returns every event matching the broader base filter (also includes PMI, unemployment, other payrolls components, retail sales, ADP, inflation).'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_indicator_history
Get Indicator History
Historical daily indicator snapshots for a stock — ideal for charting and trend detection.
Returns up to `days` days of data (max 730, default 90) from the stock_indicator_snapshots
collection which is populated daily by the indicator pipeline.
Every snapshot row contains:
- recorded_at: ISO date string
- price: closing price at snapshot time
- rsi: RSI(14) value (0-100)
- macd_histogram: MACD histogram value (positive = bullish momentum)
- bb_pct: Bollinger Band % position (0 = at lower, 100 = at upper band)
- sma20 / sma200: 20-day and 200-day simple moving averages
With full=true, each row also gets:
- williams_r: Williams %R (0 to -100; >-20 overbought, <-80 oversold)
- ultimate_osc: Ultimate Oscillator (0-100; >70 overbought, <30 oversold)
- vix_fix_value: Williams VIX Fix synthetic fear gauge (higher = more fear)
- williams_ad_trend: Accumulation/Distribution trend (rising/falling/flat)
- td_signal: DeMark TD Sequential signal (BUY_SETUP/SELL_SETUP/BUY_COUNTDOWN/SELL_COUNTDOWN/null)
- td_phase: DeMark phase (setup_active/setup_complete/countdown_active/countdown_done/null)
- analyst_rating: analyst consensus (buy/outperform/hold/underperform/sell or null)
- analyst_target: mean analyst price target or null
Returns {} if fewer than 3 snapshots found.
Pro tier only.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbol'], 'properties': {'days': {'type': 'integer', 'default': 90, 'description': 'Number of days of historical daily indicator snapshots to return (max 730, default 90). Returns {} if fewer than 3 snapshots are found in the window.'}, 'full': {'type': 'boolean', 'default': False, 'description': 'False (default) returns only recorded_at/price/rsi/macd_histogram/bb_pct/sma20/sma200 per day — enough for most charting/trend use. True adds the specialized indicators (williams_r, ultimate_osc, vix_fix_value, williams_ad_trend, td_signal, td_phase) plus analyst_rating/analyst_target, which barely change day to day and roughly double response size over a long window.'}, 'symbol': {'type': 'string', 'description': 'Stock ticker symbol. Also accepts a company name as a fallback when it uniquely resolves to one symbol.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_insider_activity
Get Insider Activity
Get AI-synthesized insider + institutional activity for a stock.
Returns combined signal (POSITIVE/NEGATIVE/NEUTRAL etc.), signal_score
(0-100, higher = stronger/more notable — the exact same field, formula,
scale and bands as get_signals()'s signal_score, no separate name) with
signal_score_band, per-source breakdown, and a human-readable summary.
Data covers insider transactions (SEC Form 4/BaFin/AFM/CNMV, with a
gap-fill from Yahoo where the regulatory source has nothing) and
institutional holdings — insider_buys/insider_sells, transactions (the
individual rows behind those counts, newest first, up to 50, each with
date/name/role/type/shares/price/value), top_holders (a union of
multiple data sources, up to 15, each with name/shares/pct_held/sources/
share_counts_by_source — the last two show which source(s) contributed
to a merged row and each one's own reported share count, useful for
spotting a false merge: two genuinely different holders should never
collide, but if they did, their per-source counts would diverge wildly),
holder_count_divergence (null unless every matched holder disagrees by
the same systemic multiplier across sources — e.g. an unrecorded
reverse split — a signal top_holders.shares may be unreliable for this
symbol; distinct from an ordinary two-holder mismatch, which is normal
data lag and stays unflagged), inst_ownership (0-100%), and
total_holders. Note: `summary` is a
separately-generated narrative on its own refresh cadence and may not
always match the live insider_buys/insider_sells/transactions counts —
trust the counts/transactions over the prose if they disagree.
Pro tier only — AI pipeline cost attached.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'description': 'Stock ticker symbol to fetch insider (SEC Form 4) and institutional-holdings activity for.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_market_assessment
Get Market Assessment
Combined AI market assessment: macro regime + market outlook in a single call.
Refreshed ~4x/day, weekdays only, during market hours (~2h apart) — dead
overnight and on weekends, not a continuous 4-hourly cadence. Check
regime_stale/outlook_stale below (which already account for the weekend
gap) before treating either as current, especially on a Monday morning.
Two distinct perspectives returned together:
- REGIME (RISK_OFF/CAUTIOUS/NEUTRAL/AGGRESSIVE): answers "how much equity risk to take"
→ use for position sizing and asset allocation decisions
- OUTLOOK (POSITIVE/NEUTRAL/NEGATIVE): answers "which direction and sectors to trade"
→ use for sector preference and directional bias
Both share the same pipeline run so they are always in sync.
- history_count: include last N prior assessments for each (0-3, default 0)
- regime_*: risk posture fields — regime, risk_appetite_score (0-100 re-expression of
regime, higher = current conditions support more risk-taking), regime_bias,
regime_bias_note (plain sentence on whether current conditions favor long or short
setups, or neither), regime_confidence, regime_rationale, key_risks,
watch_for, vix_at_assessment, regime_updated_at, regime_stale
- macro_score / regime_strength: macro_score is a real, continuous 0-100 read on how
much risk the current environment supports (0=RISK_OFF/capital preservation,
100=AGGRESSIVE/risk-on) — the same underlying number `regime` buckets into 4
discrete categories, blending arithmetic inputs (VIX level, breadth
oversold/overbought skew, SKEW-vs-VIX divergence, TD-exhaustion ratio) with
regime_strength, the AI's own 1-10 read of regime conviction. Distinct from
risk_appetite_score (a coarse 4-value lookup on `regime` alone) — macro_score is
the real underlying number. Null on a pre-2026-08-26 assessment that predates
this field. Not a call on any one stock.
- macro_score_trend: {change_7d, change_30d, direction} — whether macro_score itself
is improving/deteriorating/stable over the trailing 7/30 days, computed
automatically (no history_count needed). A bare 33 doesn't tell you whether the
environment is getting worse or just stabilized after a worse reading; this does.
Either leg is null without enough history yet.
- regime_stale / outlook_stale: true if that assessment is >72h old (the pipeline runs
weekdays only, so a normal Fri→Mon gap does not trip this — only a genuinely broken/stuck
pipeline does). null if the timestamp itself is missing.
- indicators.macro_data: FRED macro data (yield curve, Fed funds, cpi_index, unemployment, M2)
- indicators.volatility_term_structure: VIX spot/3M/6M term structure + contango signal
- indicators.market_sentiment: CNN Fear & Greed value and label
- market_context: price/RSI/SMA200/perf snapshot of SPY/QQQ/IWM/TLT/GLD/VIX/TNX + sectors
NOTE: point-in-time snapshot recorded when AI ran — not live prices (use get_market_pulse for live)
- outlook_*: directional fields — outlook, outlook_conviction, equity_view,
preferred_sectors, avoided_sectors, catalyst, outlook_key_risk, outlook_rationale,
outlook_updated_at, outlook_stale
Pro tier only — AI pipeline cost attached.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'history_count': {'type': 'integer', 'default': 0, 'description': 'Include the last N prior assessments for each of regime and outlook (0-3, default 0).'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_market_movers
Get Market Movers
Top market movers from the Stocklake universe — gainers, losers, most active.
- category: "gainers" | "losers" | "most_active" | "all" (default "all" = all 3 categories)
- limit: results per category (default 10, max 20). Each returned stock counts as
one call toward your daily limit — a symbol appearing in more than one category
(e.g. both "gainers" and "most_active") counts once per category it appears in.
- min_market_cap_b: filter to stocks above this market cap in billions of US dollars
(e.g. 1.0 = $1B+), compared against market_cap_usd
Returns per stock: symbol, name, sector, price, change_pct, volume, rsi, market_cap
(listing currency), market_cap_usd, currency, analyst_rating, atr_pct (atr_pct omitted when the underlying volatility reading is
missing or corrupted).
Available to all tiers.
Pro tier adds the minimum AI-narrative slice (ai_verdict, ai_headline,
ai_score 0-100, ai_score_band) — precomputed, no extra
AI cost. A big mover's price/volume/RSI alone doesn't say whether the
move matters; the one-line headline does. For the full research bundle
on any one mover, call get_stock_research(symbol).
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 10, 'description': 'Results per category (default 10, max 20). Each returned stock counts as one call toward your daily limit — a symbol appearing in more than one category (e.g. both "gainers" and "most_active") counts once per category it appears in.'}, 'category': {'type': 'string', 'default': 'all', 'description': 'Which movers category to return: "gainers" | "losers" | "most_active" | "all" (default "all" = all 3 categories).'}, 'min_market_cap_b': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Filter to stocks above this market cap in billions of US dollars, e.g. 1.0 = $1B+ (compared against market_cap_usd).'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_market_pulse
Get Market Pulse
Live market health snapshot in a single call.
Aggregates key market indicators without requiring multiple tool calls.
No AI cost — reads live data directly from the market data feed.
Returns:
- vix: VIX level and change_pct (from live stocks data)
- fear_greed: value (0-100) and label (e.g. "neutral", "greed", "fear")
- breadth: market-wide RSI distribution — oversold_pct, overbought_pct, neutral_pct, universe_size
- indices: SPY, QQQ, IWM prices + RSI + 1-week performance
- bonds_commodities: TLT (long-duration bonds), GLD (gold)
- updated_at: when the breadth/fear_greed snapshot was last recorded
Available to all tiers.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_news_feed
Get Market News Feed
Top AI-flagged news across all tracked stocks — the market-wide news briefing.
Unlike get_stock_news (per-symbol), this scans the entire universe and returns
the most notable articles ranked by signal_score, newest first within each score tier.
Use this for:
- Morning briefing: "what happened in the market this week?"
- Catalyst scanning: "what news is driving moves right now?"
- Event monitoring: "which stocks have high-impact news today?"
- min_signal_score: minimum signal_score (0-100, default 60) used to SELECT
articles server-side. Resolved per-article (stored/computed magnitude
preferred over an unfiltered Mongo `$gte`, since a formal live signal
doesn't exist for every article — see signal_score below), then
filtered/sorted in Python.
- days: look-back window in days (default 3, max 10)
- limit: max articles returned (default 10, max 25)
- Per article: symbol, title, published_at, ai_sentiment, ai_summary (full
text), signal_score (0-100), signal_score_band (Weak/Moderate/Strong/
Very Strong)
signal_score/signal_score_band: this symbol's LIVE signal score if a
news-sourced signal was raised for it in the last 90 days (same number
get_stock_news()/get_signals() report, kept in sync as that signal is
re-scored — one $in query per distinct symbol in the result, not per
article, so two articles about the same stock always show the same
value); otherwise a per-article magnitude computed from THIS article's own
sentiment/confidence/flag_score, so every article still gets a real,
rankable number. Always a single number — for a symbol whose live signal
is genuinely two-sided (real opposing bull/bear theses), this is the
STRONGER of the two sides, same as get_signals()/get_stock_news(). There is
deliberately no separate "news_score" field — one name for "how strong is
this idea," whether it's backed by a formal signal or just this article's
own classification.
Pro tier only — AI pipeline cost attached.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'days': {'type': 'integer', 'default': 3, 'description': 'Look-back window in days (default 3, max 10).'}, 'limit': {'type': 'integer', 'default': 10, 'description': 'Max articles returned (default 10, max 25).'}, 'min_signal_score': {'type': 'integer', 'default': 60, 'description': "Minimum signal_score used to SELECT articles server-side, 0-100 (default 60). Resolved per-article (this symbol's live signal_score if one exists, else a per-article magnitude computed from sentiment/confidence/flag_score) since a live signal doesn't exist for every article."}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_screener
Screen Stocks
Filter and rank stocks from the Stocklake universe — fundamentals, technicals, and AI signals in one tool.
Parameters:
- sector: e.g. "Technology", "Healthcare", "Financial Services"
- country: e.g. "United States", "Germany"
- min_rsi / max_rsi: exact RSI bounds (e.g. max_rsi=30 = oversold, min_rsi=70 = overbought)
- sma_trend: "above_200" (price above 200-day MA) | "below_200"
- macd_signal: "positive" (MACD line above signal) | "negative"
- min_perf_1d / max_perf_1d: 1-day performance % (e.g. min_perf_1d=2.0 = up 2%+ today)
- min_volume: minimum daily volume (e.g. 1000000)
- min_market_cap_b / max_market_cap_b: market cap in billions of US dollars,
compared against market_cap_usd (stocks with no FX rate for their currency
are excluded when either bound is set)
- max_pe_forward: maximum forward P/E (e.g. 20 = value screen)
- analyst_rating: "strong_buy" | "buy" | "hold" | "sell" | "strong_sell"
- min_ai_score: minimum AI score 0-100 (pro tier only — silently ignored for free).
Gates on stock_ai_summary.py's own composite ai_score — same 0-100 scale/band
convention as signals.signal_score, but a distinct field/pipeline (per-stock AI
summary confidence, not a directional trade idea). Renamed 2026-08-24 from the
retired 0-10 min_flag_score — the raw flag_score field it used to gate on is no
longer part of this fleet's public vocabulary at all (see ai_score below).
- preset: "oversold" | "overbought" | "momentum" | "high_conviction" (pro only)
oversold = RSI≤35 + above SMA200 · overbought = RSI≥65
momentum = RSI 50-70, above SMA200, up 0.5%+ today · high_conviction = ai_score≥70
- sort_by: "market_cap" | "rsi" | "perf_1d" | "volume" | "analyst_rating" | "rating" | "ai_score" (pro).
Defaults to "market_cap", except the "high_conviction" preset defaults to "ai_score"
(the dimension it's filtering by) unless you explicitly pass a different sort_by.
- sort_dir: "asc" | "desc" (default "desc")
- limit: 1–25 (default 20). Each returned stock counts as one call toward your daily limit.
Returns: { count, preset, filters, results[] } — each result includes symbol, name, sector,
industry, country, price, change_pct, volume, market_cap, market_cap_usd, currency,
pe_forward, rsi, macd_signal, sma200_trend, analyst_rating. market_cap is in the
listing's own currency (the currency field); market_cap_usd is converted to US
dollars and is what the market_cap sort and cap filters use.
Pro tier adds rating (0-10 composite score) + ai_verdict + ai_headline + ai_score
(0-100) + ai_score_band to every result row (the headline is the "why" — a bare
verdict alone isn't enough to act on), enables min_ai_score filter, high_conviction
preset, and sorting by rating/ai_score (sort_by silently falls back to market_cap on
free/guest for both). All other filters available to all tiers. For the full research
bundle on any one result, call get_stock_research(symbol).
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 20, 'description': 'Max results to return, 1-25 (default 20). Each returned stock counts as one call toward your daily limit.'}, 'preset': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': '"oversold" | "overbought" | "momentum" | "high_conviction" (pro only). oversold = RSI<=35 + above SMA200; overbought = RSI>=65; momentum = RSI 50-70, above SMA200, up 0.5%+ today; high_conviction = ai_score>=70.'}, 'sector': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': 'Filter by sector, e.g. "Technology", "Healthcare", "Financial Services".'}, 'country': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': 'Filter by country, e.g. "United States", "Germany".'}, 'max_rsi': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Maximum RSI bound (e.g. max_rsi=30 = oversold).'}, 'min_rsi': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Minimum RSI bound (e.g. min_rsi=70 = overbought).'}, 'sort_by': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': '"market_cap" | "rsi" | "perf_1d" | "volume" | "analyst_rating" | "rating" | "ai_score" (pro). Defaults to "market_cap", except the "high_conviction" preset defaults to "ai_score" (the dimension it\'s filtering by) unless you explicitly pass a different sort_by. Sorting by rating/ai_score silently falls back to market_cap on free/guest.'}, 'sort_dir': {'type': 'string', 'default': 'desc', 'description': 'Sort direction: "asc" | "desc" (default "desc").'}, 'sma_trend': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': '"above_200" (price above 200-day MA) | "below_200".'}, 'min_volume': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'default': None, 'description': 'Minimum daily volume, e.g. 1000000.'}, 'macd_signal': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': '"positive" (MACD line above signal) | "negative".'}, 'max_perf_1d': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Maximum 1-day performance %.'}, 'min_perf_1d': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Minimum 1-day performance %, e.g. min_perf_1d=2.0 = up 2%+ today.'}, 'min_ai_score': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'default': None, 'description': "Minimum AI score, 0-100 — pro tier only (silently ignored for free). Gates on stock_ai_summary.py's own composite ai_score, same 0-100 scale/band convention as signals.signal_score but a distinct field/pipeline (per-stock AI summary confidence, not a directional trade idea). Renamed 2026-08-24 from the retired 0-10 min_flag_score."}, 'analyst_rating': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': 'Filter by analyst consensus rating: "strong_buy" | "buy" | "hold" | "sell" | "strong_sell".'}, 'max_pe_forward': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Maximum forward P/E, e.g. 20 for a value screen.'}, 'max_market_cap_b': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Maximum market cap in billions of US dollars (compared against market_cap_usd).'}, 'min_market_cap_b': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'default': None, 'description': 'Minimum market cap in billions of US dollars (compared against market_cap_usd, so non-USD listings are converted first).'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_sector_intelligence
Get Sector Intelligence
AI-assessed sector intelligence: signal, cycle stage, rotation signal,
drivers, alerts, and computed statistics per sector (RSI distribution, breadth,
performance 1W/1M, top/bottom movers, historical percentiles).
Pass a sector name for a single sector, or omit the parameter (or pass None)
to get the latest assessment for all 11 sectors — the all-sectors call doubles as
the rotation view: use sort_by_strength to rank LEADING-first for finding leading
vs lagging sectors, and history_count for prior signal states per sector.
- sort_by_strength: sort all-sectors output LEADING→LAGGING instead of alphabetical
(all-sectors call only; ignored when a single sector is requested)
- history_count: include last N prior signal states per sector, 0-3 (default 0;
all-sectors call only)
- sector_score / strength_score: sector_score is a real, continuous 0-100 read on
this sector's relative strength/leadership (0=LAGGING, 100=LEADING) — the same
underlying number `signal` buckets into 5 discrete categories, blending
arithmetic inputs (RSI/perf percentiles, top-5 concentration, SMA200 breadth)
with strength_score, the AI's own 1-10 read. Comparable across all 11 sectors on
one absolute scale (not per-sector-relative). Null on a pre-2026-08-26 assessment
that predates this field. Not a buy/sell call.
- sector_score_trend: {change_7d, change_30d, direction} — whether this sector's
score is improving/deteriorating/stable over the trailing 7/30 days, computed
automatically. Single-sector calls only — this is the only trend view available
for one sector at all (history_count only applies to the all-sectors call).
Two sectors both reading STRONG/68 can be in opposite motion; this tells them
apart. Either leg is null without enough history yet.
Refreshed ~4x/day, weekdays only, during market hours (~2h apart) — dead
overnight and on weekends, not a continuous 4-hourly cadence. Check the
returned updated_at before treating this as current, especially on a
Monday morning or after a holiday.
Available to pro tier only (AI pipeline costs).
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'sector': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': "Pass a sector name for a single sector's assessment, or omit (None) to get the latest assessment for all 11 sectors at once — the all-sectors call doubles as the rotation view."}, 'history_count': {'type': 'integer', 'default': 0, 'description': 'Include the last N prior signal states per sector, 0-3 (default 0). Only applies to the all-sectors call.'}, 'sort_by_strength': {'type': 'boolean', 'default': False, 'description': 'Sort all-sectors output LEADING→LAGGING instead of alphabetical, for finding leading vs lagging sectors. Only applies to the all-sectors call; ignored when a single sector is requested.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_signals
Get Signals
AI-screened stock signals recently surfaced by the Stocklake pipeline —
sourced from news analysis, sector screening, and sentiment signals.
Shows what the pipeline noticed in the last 24 hours (falling back to the
most recent signals regardless of age if nothing has fired in that window
— see `window` in the response). This reflects what the AI pipeline found,
not whether Stocklake's own internal trading engine still holds it live —
a signal it later dropped or let expire is still shown here, since that's a
fact about our own trading state, not about the signal's informational value.
Parameters:
- direction: "POSITIVE" | "NEGATIVE" | "NEUTRAL" (default: all). NEUTRAL
covers both a flat/undecided read AND a genuinely two-sided idea (real
opposing bull/bear theses on the same symbol) — in the latter case
signal_score is the STRONGER of the two sides (see signal_score below),
so a high score alongside NEUTRAL means "real conviction here, just no
directional consensus," not "nothing going on." The two-sided detail is
in `rationale`.
- min_signal_score: minimum composite signal score 0-100 (default 60) — a
blend of conviction/confidence/flag_score, source track record, and real
technical factors. This is the field to filter on. Always compared
against a single number, including for NEUTRAL/two-sided ideas — a
result is never returned below your threshold on both sides.
- source: filter by signal source — "news" | "screener" | "sentiment" (default: all)
- limit: max results to return (default 25, max 50). Each returned signal counts
as one call toward your daily limit.
Returns:
- count: number of signals returned
- window: "24h" (fresh activity found) or a fallback note when the last 24h
had nothing and the response instead shows the most recent signals overall
- signals[]: each with symbol, direction, signal_score (0-100), signal_score_band
(human-readable label — "Weak"/"Moderate"/"Strong"/"Very Strong"),
source, rationale, expires, flagged_at
Pro tier only — AI pipeline cost attached.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {'limit': {'type': 'integer', 'default': 25, 'description': 'Max results to return (default 25, max 50). Each returned signal counts as one call toward your daily limit.'}, 'source': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': 'Filter by signal source: "news" | "screener" | "sentiment" (default: all).'}, 'direction': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'default': None, 'description': 'Filter by direction: "POSITIVE" | "NEGATIVE" | "NEUTRAL" (default: all). NEUTRAL covers both a flat/undecided read and a genuinely two-sided idea (see signal_score below).'}, 'min_signal_score': {'type': 'integer', 'default': 60, 'description': 'Minimum composite signal score, 0-100 (default 60) — a blend of conviction/confidence/flag_score, source track record, and real technical factors. This is the field to filter on.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_stock
Get Stock
Price, fundamentals, technical indicators, and company profile for a stock.
Returns all data needed to understand a stock in a single call.
Key fields:
- price, change_pct, prev_close, week52_high/low, volume, avg_volume
- market_cap, enterprise_value, beta
- pe_trailing, pe_forward, price_to_book, dividend_yield, dividend_rate
- debt_to_equity, profit_margins, return_on_equity, free_cashflow
- revenue_growth, earnings_growth, revenue_ttm, gross_profit_ttm
- analyst_rating: "strong_buy"|"buy"|"hold"|"sell"|"strong_sell" (analyst consensus)
- analyst_rating_score: 1.0–5.0 mean analyst recommendation (1=strong_buy, 5=strong_sell)
- analyst_target: mean analyst price target
- analyst_count: number of analyst opinions
- indicators: raw RSI, MACD, Bollinger Bands, SMA20/SMA200 (the canonical
50/200-day averages -- no separate top-level ma_50/ma_200 field), EMA20/EMA200, ATR
- description: company business description
- website, employees, officers (top 5: name, title, total_pay)
- updated_at: last data sync timestamp
Available to all tiers (raw indicator numbers, no interpretation). This basic six
(RSI/MACD/Bollinger/SMA/EMA/ATR) is standard, widely-available technical analysis.
Pro tier also unlocks 6 more specialized indicators inside the SAME `indicators` block
(williams_r, ultimate_osc, vix_fix, williams_ad, td_sequential, elliott_wave -- the
Larry Williams family, DeMark TD Sequential, and Elliott Wave) -- these are omitted
entirely from the free/guest response (tier-gating sweep, 2026-08-28), not merely
unlabeled; free/guest calls get indicators with only the basic six populated.
Pro tier adds four interpreted blocks computed from the same indicators, no extra AI cost,
plus a minimum AI-narrative slice — all five below are precomputed, none cost a live AI call:
- ai_verdict / ai_headline / ai_score / ai_score_band: the minimum useful
AI-narrative slice, shared by every pro-tier stock-returning tool. A bare verdict alone
isn't actionable (e.g. bearish while up 8% on the day with a strong_buy analyst rating is
genuinely ambiguous) — the one-line headline is the "why", ai_score is the 0-100
composite (same scale/band convention as get_signals' signal_score, distinct pipeline).
For the full text (summary/key_points/risks/near_term/longer_term) and cross-source
news/insider context, call get_stock_research(symbol) instead — that's the only tool
with the complete bundle.
- ai_score (0-100) / ai_score_band (Weak/Moderate/Strong/Very Strong):
stock_ai_summary.py's own composite score, on the same 0-100 scale and band boundaries
as get_signals()'s signal_score — but a different pipeline/collection, never the same
number for the same symbol by coincidence alone.
- rating: {score 0-10, direction POSITIVE/NEUTRAL/NEGATIVE, signals per-indicator breakdown}
— composite technical score
- signals: flat labeled signals (rsi/macd/bollinger/sma200/sma50/williams_r/ultimate_osc/
vix_fix/williams_ad/td_sequential/elliott_wave, each with a value + plain-English label)
— same indicators as 'indicators', pre-interpreted for programmatic use without parsing raw numbers
- stance_signals: unified list of per-source directional calls (technical rating, AI summary
near_term/longer_term, insider/institutional sentiment, analyst consensus, active screener
signals) — each entry {stance POSITIVE/NEGATIVE/NEUTRAL, conviction 0-10, horizon
INTRADAY/SWING/POSITION/LONG_TERM, edge_quality PROVEN/OBSERVATION/UNKNOWN (per-source
signal_backtest track record), source, raw_label, as_of}. Same canonical shape used on the
stock detail page — a source with missing/stale data is simply omitted, not nulled out.
- relative_strength: {windows: {5d/20d/60d/120d/12m -> {stock_return_pct, rs_vs_spy, rs_vs_qqq,
rs_vs_sector}}, verdict: one-line plain-language read (e.g. "Laggard — weak near- and long-term")}
— stock's own return minus each benchmark's return (percentage points, not a ratio) per window.
rs_vs_sector uses the stock's GICS sector SPDR ETF (Vanguard backup if the primary lacks
history); omitted for stocks with no resolvable sector (crypto, FX, indices). Windows/
benchmarks with insufficient history are omitted rather than null. null if not precomputed yet.
- market_risk: {beta_spy_1y, corr_spy_1y} — 1-year daily-return beta and correlation vs SPY.
Distinct from quote.beta (Yahoo's own longer-window beta calculation) — this is computed
fleet-wide from the same daily bars as relative_strength. Both fields null if not yet
precomputed for this symbol (populates on the next scheduled indicators run).
- forensic_scores: {altman_z, piotroski_f, beneish_m, computed_at} — three classic forensic-
accounting formulas (Altman 1968 bankruptcy-risk, Piotroski 2000 fundamental-strength,
Beneish 1999 earnings-manipulation-likelihood), computed from balance sheet/income
statement/cash flow data, refreshed on each company's own filing cadence (roughly annual).
Each sub-block is {score, note, ...} — altman_z adds `zone` (safe/grey/distress),
piotroski_f adds `strength` (strong/moderate/weak, 0-9 scale), beneish_m adds
`likely_manipulator` (bool, score > -1.78). `note` explains what the score measures and
its known caveats (e.g. Altman Z is not meaningful for banks/insurers and can flag REITs/
client-float businesses as "distress" by design) — always read alongside the score, not in
isolation. `score: null` means genuinely not computable for this company (common for
financial-sector names), not an error. No trading signal is derived from these scores
anywhere in this API today — treat as raw accounting-model output for your own research.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'description': 'Stock ticker symbol. Also accepts a company name as a fallback (e.g. "Apple") when it uniquely resolves to one symbol.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_stock_financials
Get Stock Financials
Full raw financial statements — balance sheet, income statement, and cash
flow line items over multiple periods. This is the underlying statement
data itself, not a derived summary — for the forensic-accounting scores
computed FROM these statements (Altman Z / Piotroski F / Beneish M), see
get_stock()'s forensic_scores block instead.
Each returned statement is shaped {line_item_name: {period_end_iso: value}}
— e.g. balance_sheet["Total Revenue"]["2025-12-31"] — so a caller gets
every available period per line item and can compute its own trends/
deltas/CAGRs, not just read the latest value.
period="annual" (default) returns up to 5 fiscal years — Yahoo's own real
ceiling, some symbols return fewer. period="quarterly" returns up to
roughly 7-8 of the most recent quarters. period="both" returns both
blocks in one call.
~50-60 curated line items per statement (not a raw dump of every row
Yahoo reports): balance sheet structure (assets/liabilities/equity/debt/
working capital), income statement (revenue through EPS), and cash flow
(operating/investing/financing, free cash flow, buybacks, stock-based
comp). Coverage genuinely varies by symbol and sector — a bank has no
"Inventory" line, a company with no buyback program has no "Repurchase
Of Capital Stock" entry. A missing line item means Yahoo doesn't report
it for this company, not a fetch error.
quarterly can come back null (with a quarterly_note) for a symbol whose
real quarterly data isn't available — rare in practice; live coverage
testing found real quarterly statements even for semi-annual-reporting
Hong Kong names. annual/quarterly can both be entirely absent if this
symbol hasn't yet been through the financials sync, or if it's not an
equity (this tool has no data for ETFs/crypto/forex/indices).
Pro tier only.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbol'], 'properties': {'period': {'type': 'string', 'default': 'annual', 'description': "'annual' (up to 5 fiscal years, default), 'quarterly' (up to ~7-8 most recent quarters), or 'both'."}, 'symbol': {'type': 'string', 'description': 'Stock ticker symbol. Also accepts a company name as a fallback when it uniquely resolves to one symbol.'}, 'statement': {'type': 'string', 'default': 'all', 'description': "'all' (default), 'balance_sheet', 'income_stmt', or 'cash_flow' — restricts which statement(s) are returned."}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_stock_history
Get Stock Price History
Daily OHLCV price history for a stock.
- days: number of trading days to return (default 90, max 365)
- Returns: { symbol, days_requested, days_returned, count, history[] } —
days_returned/count can be less than days_requested if less history exists
- Per bar: date, open, high, low, close, volume
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbol'], 'properties': {'days': {'type': 'integer', 'default': 90, 'description': 'Number of trading days of daily OHLCV history to return (default 90, max 365). days_returned/count in the response can be less than this if less history exists.'}, 'symbol': {'type': 'string', 'description': 'Stock ticker symbol. Also accepts a company name as a fallback when it uniquely resolves to one symbol.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_stock_news
Get Stock News
AI-analysed news for a stock, newest first.
Only returns articles processed by our AI pipeline (sentiment, signal_score, summary).
- days: look-back window in days. Requesting more than your tier's cap is
silently clamped down to it: 30 free/guest, 90 pro.
- limit: max articles returned. The `limit=10` default is a Pro-tier-shaped
value — on free/guest it's silently clamped down to that tier's cap (5),
so a free caller passing no `limit` effectively gets 5, not 10. Requesting
more than your tier's cap (5 free/guest, 50 pro) is likewise clamped down.
- status: "ok" = articles returned | "empty" = no news in window
- Per article: title, published_at, ai_sentiment, ai_summary (full text) — Pro only, see below
- signal_score (Pro only, 0-100 or null) / signal_score_band (Pro only, string
or null — "Weak"/"Moderate"/"Strong"/"Very Strong"): if this symbol has a
live news-sourced signal (raised in the last 90 days), every article
shows that SAME number — the same one get_signals()/get_stock_research()
report for this symbol (all three read the same underlying signal, via
the same shared resolver), staying live/synced: if the signal is later
re-scored, this reflects the update on your next call, not a frozen
snapshot from classification time. Always a single number (never a
two-sided split) — for a genuinely contested (two opposing theses)
signal, this is the STRONGER of the two sides. NOT gated on whether
Stocklake's own internal trading engine still considers the signal live
— a dropped/expired signal is still a real, useful fact about what the
pipeline found. When there's no live signal for this symbol at all, each
article instead gets its OWN per-article score (computed from that
article's sentiment/confidence/flag_score) — the same fallback
get_stock_research()'s news[] block uses, so a symbol with no active
thesis doesn't just go null across the board; different articles for the
same symbol can then legitimately show different numbers. Null only when
neither path can produce a value (article has no AI sentiment/confidence/
flag_score at all). There is deliberately no separate "news_score" field
— one name, kept in sync with the signal when one exists, computed
per-article when it doesn't.
Free tier: up to 5 articles, title + published_at only (no AI fields), 30-day window.
Pro tier: up to 50 articles with full AI fields, 90-day window.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbol'], 'properties': {'days': {'type': 'integer', 'default': 30, 'description': "Look-back window in days. Requesting more than your tier's cap is silently clamped down to it: 30 free/guest, 90 pro."}, 'limit': {'type': 'integer', 'default': 10, 'description': "Max articles returned. Default 10 is a Pro-tier-shaped value — on free/guest it's silently clamped down to that tier's cap (5), so a free caller passing no limit effectively gets 5, not 10. Requesting more than your tier's cap (5 free/guest, 50 pro) is likewise clamped down."}, 'symbol': {'type': 'string', 'description': 'Stock ticker symbol. Also accepts a company name as a fallback when it uniquely resolves to one symbol.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_stock_research
Get Stock Research
Full AI research bundle for a stock in one call — fundamentals, AI-generated
summary, recent AI-classified news, insider/institutional signal, and recent
trade signal history. Replaces 4 separate calls: get_stock + get_stock_news +
get_insider_activity + get_signals (for one symbol).
Returns:
- stock: price, name, sector, rsi, pe_forward, market_cap, 52-week range, analyst data
- ai_summary: verdict, ai_score (0-100)/ai_score_band (Weak/Moderate/Strong/
Very Strong — stock_ai_summary.py's own composite, same scale/band convention as
signal_score but a distinct field/pipeline), full summary, key_points, risks,
price_at_generation, generated_at, headline (one-sentence plain-language take), near_term
(stance/confidence over <4 weeks — technicals/momentum-weighted), longer_term
(stance/confidence over a multi-month horizon — fundamentals/analyst/institutional-flow-weighted).
headline/near_term/longer_term are null on summaries generated before this schema shipped —
until that symbol's next regeneration, fall back to verdict/ai_score.
- news: last 3 high-relevance articles (title, published_at, ai_sentiment,
ai_summary, signal_score [0-100]/signal_score_band — this symbol's LIVE
news-sourced signal score if one exists in the last 90 days [same number
as the `signals` list below and get_signals()/get_stock_news(), kept in
sync as it's re-scored], else a per-article magnitude computed from that
article's own classification. One name, no separate "news_score" field.)
- sentiment: signal, signal_score (0-100)/signal_score_band — one name, no
separate "insider_score" field, same as the news block above — insider_trend
(buying/selling/neutral, or null with no transactions in the window), institutional_pct
- signals[]: up to the 5 most recent trade signals for this symbol in the last
90 days (direction, rationale, signal_score [0-100], signal_score_band
[human-readable label — "Weak"/"Moderate"/"Strong"/"Very Strong" — or null
alongside a null signal_score], source, expires, flagged_at). Empty if
nothing in that window. Recency-gated, not gated on whether Stocklake's
own trading engine still holds the signal live — a signal it dropped or
let expire is still a real, useful fact about what the pipeline found, so
it stays in this list rather than disappearing the moment our own paper
trader moves on.
- forensic_scores: {altman_z, piotroski_f, beneish_m, computed_at} — three classic
forensic-accounting formulas (Z-Score bankruptcy risk / F-Score fundamental
quality / M-Score earnings-manipulation risk), computed from `stocks.financials`
(GH #107). Omitted entirely if this symbol has no forensic_scores doc yet — not
every symbol qualifies (financial-sector companies mostly return null on all
three by construction, see the field's own note text). A withheld individual
score always surfaces as {"score": null, "note": "<plain-English reason>"} —
never a bare 0, never silently dropped from its own sub-block. Same shape
get_stock()/get_stocks() already return.
All data is pre-computed by the Stocklake AI pipeline — no live AI calls on request.
Pro tier only. For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbol'], 'properties': {'symbol': {'type': 'string', 'description': 'Stock ticker symbol to fetch the full AI research bundle for.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_stocks
Get Multiple Stocks
Batch stock data for up to 25 symbols in a single call — the same fields
get_stock returns for the same key/symbol, so this is a true batch version,
not a thinned-down scan. Returns a dict keyed by symbol. Missing symbols
are omitted from the result. Each symbol in the batch counts as one call
toward the daily limit. A request over 25 symbols is rejected outright
(error: batch_too_large) rather than silently served on just the first
25 — split a larger list into multiple calls.
Available to all tiers (fundamentals/indicators/company profile, free).
Pro tier adds, per symbol, the same precomputed blocks get_stock adds —
rating {score, direction, signals}, signals (per-indicator breakdown),
relative_strength, market_risk {beta_spy_1y, corr_spy_1y}, and the minimum
AI-narrative slice (ai_verdict, ai_headline, ai_score,
ai_score_band). None of this costs a live AI call — it's all
precomputed and just needs projecting.
NOT included, even on pro — call get_stock(symbol) for stance_signals, or
get_stock_research(symbol) for the full ai_summary text (summary/key_points/
risks/near_term/longer_term) plus cross-source news/insider/signal context.
Response also carries `duplicates_collapsed`: how many input symbols
normalized (case-folding, share-class aliasing e.g. "BRK.B"->"BRK-B") or
literally repeated onto a symbol already counted elsewhere in this batch.
requested - len(missing or []) - duplicates_collapsed == count always holds.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'required': ['symbols'], 'properties': {'symbols': {'type': 'array', 'items': {'type': 'string'}, 'description': 'List of stock ticker symbols, up to 25 per call. Each symbol counts as one call toward the daily limit. A request over 25 symbols is rejected outright (error: batch_too_large) rather than silently served on just the first 25 — split a larger list into multiple calls.'}}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
get_watchlist
Get Watchlist
The caller's Stocklake watchlist (starred symbols from the web dashboard),
enriched with live price, technicals, and AI verdict.
Returns:
- count: number of symbols on the watchlist
- items[]: each with symbol, name, sector, price, change_pct, rsi, market_cap,
analyst_rating, atr_pct, ai_verdict, ai_headline, ai_score (0-100),
ai_score_band (Weak/Moderate/Strong/Very Strong),
added_at, price_at_add
- empty items[] if nothing is starred yet — star symbols at stocklake.dev/dashboard
Pro tier only.
For informational purposes only. Not financial advice.
읽기 전용
멱등성
입력 스키마
{'type': 'object', 'properties': {}, 'additionalProperties': False}
출력 스키마
{'type': 'object', 'additionalProperties': True}
기록
최근 도구 변경
변경됨
get_market_movers
2026년 9월 23일 2:42 AM
변경됨
get_screener
2026년 9월 23일 2:42 AM
변경됨
get_signals
2026년 9월 23일 2:42 AM
추가됨
get_earnings_intelligence
2026년 9월 17일 12:39 PM
추가됨
get_stock_research
2026년 9월 17일 12:39 PM
추가됨
get_economic_calendar
2026년 9월 17일 12:39 PM
추가됨
get_stock_financials
2026년 9월 17일 12:39 PM
추가됨
get_indicator_history
2026년 9월 17일 12:39 PM
추가됨
get_market_movers
2026년 9월 17일 12:39 PM
추가됨
get_screener
2026년 9월 17일 12:39 PM
추가됨
get_news_feed
2026년 9월 17일 12:39 PM
추가됨
get_watchlist
2026년 9월 17일 12:39 PM
추가됨
get_signals
2026년 9월 17일 12:39 PM
추가됨
get_market_pulse
2026년 9월 17일 12:39 PM
추가됨
get_stocks
2026년 9월 17일 12:39 PM
추가됨
get_insider_activity
2026년 9월 17일 12:39 PM
추가됨
get_sector_intelligence
2026년 9월 17일 12:39 PM
추가됨
get_market_assessment
2026년 9월 17일 12:39 PM
추가됨
get_earnings_calendar
2026년 9월 17일 12:39 PM
추가됨
get_stock_history
2026년 9월 17일 12:39 PM
추가됨
get_stock_news
2026년 9월 17일 12:39 PM
추가됨
get_stock
2026년 9월 17일 12:39 PM
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