Tool Reference

Every Stocklake tool - parameters, response fields, and examples. Organized by what you're paying for: data is free, intelligence is Pro. ← Getting Started

Not financial advice. All data, ratings, signals, and AI assessments are for informational and research purposes only. Nothing here constitutes investment advice or a recommendation to buy or sell any security.

Data usage. Stocklake data is for your own use - research, analysis, and your own agents and tools. Reselling or redistributing API data or access, bulk-exporting data beyond normal API usage, or building a mirror or downstream feed on top of the API is not allowed, and accounts that do so can be suspended. See Acceptable Use in the Terms.

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get_stock free

Returns price, fundamentals, technical indicators, and company profile for a ticker - everything you need about a stock in one call.

Parameters

Name	Type	Description
symbol	string	Ticker symbol, e.g. AAPL. Case-insensitive.

Response fields

Field	Type	Description
symbol	string	Ticker
name	string	Company full name
sector / industry	string	Sector and industry classification
country / currency / exchange	string	Country, reporting currency, exchange code
price	number	Current market price (multi-source, authoritative)
change_pct	number	Day change %
volume / avg_volume	number	Day volume and average volume
prev_close	number	Previous close
week52_high / week52_low	number	52-week range
market_cap / enterprise_value	number	Market cap and enterprise value, in the listing's own currency (see currency)
market_cap_usd	number \| null	Market cap converted to US dollars; null when no FX rate is available for the listing currency
beta	number	Beta vs market
pe_trailing / pe_forward	number	Trailing and forward P/E ratios
price_to_book	number	Price-to-book ratio
dividend_yield / dividend_rate / ex_dividend_date	number / string	Dividend info
debt_to_equity	number	D/E ratio
profit_margins / operating_margins / gross_margins	number	Net, operating and gross profit margins (ratios, e.g. 0.25 = 25%)
revenue_growth / earnings_growth	number	YoY growth rates
earnings_date / earnings_is_estimate / last_earnings_date	string / bool / string	Next scheduled earnings report (UTC ISO; null when no date has been announced) and whether that date is an estimate; last_earnings_date is the most recent report
revenue_ttm / gross_profit_ttm	number	Trailing twelve-month revenue and gross profit
free_cashflow	number	Free cash flow (TTM), in the listing currency. Converted from the filing currency when they differ; null with a financials_note when no rate is available
financial_currency	string	Currency the company files its statements in (e.g. CNY for BABA)
return_on_equity	number	ROE
analyst_rating	string	Analyst consensus label: strong_buy · buy · hold · sell · strong_sell
analyst_rating_score	number	Mean analyst recommendation score: 1.0 = strong buy, 5.0 = strong sell (lower is better)
analyst_target / analyst_count	number	Mean price target and number of analyst opinions
indicators	object	RSI, MACD {macd_line, signal_line, histogram}, Bollinger Bands {upper_band, middle_band, lower_band}, SMA20/SMA200, EMA20/EMA200, ATR (all tiers). pro also unlocks every other field inside this same object: williams_r, ultimate_osc, vix_fix {value, percentile, spike}, williams_ad {trend, divergence}, td_sequential {setup_count, setup_direction (the setup currently counting: downtrend_exhaustion = counting falling closes, a decline that may be running out; uptrend_exhaustion = counting rising closes), countdown_count, countdown_complete, countdown_direction (same two values, for the countdown; can differ from setup_direction), signal (the most recent completed setup or countdown: DOWNTREND_EXHAUSTION_SETUP / UPTREND_EXHAUSTION_SETUP / DOWNTREND_EXHAUSTION_COUNTDOWN / UPTREND_EXHAUSTION_COUNTDOWN. It can be weeks old. For the count running now, read setup_direction with setup_count, or countdown_direction with countdown_count), phase}, elliott_wave {signal, trade_signal}, adx {adx, plus_di, minus_di}, ichimoku {tenkan, kijun, cloud_top, cloud_bot, above_cloud, below_cloud}, squeeze {squeeze_on, hist}, rs_rank (relative-strength rank 1-99, stocks only: past-year return with the latest quarter counted double, ranked against every tracked stock; 99 = strongest) - omitted entirely (not just unlabeled) for free/guest, along with any indicator added later.
description	string	Long-form company business description
website	string	Company website URL
employees	integer	Full-time employee count
officers	array	Top 5 executives: name, title, total_pay
updated_at	string	Data freshness timestamp (ISO 8601 UTC)
rating	object	pro Composite technical score: score (0-10), direction (POSITIVE/NEUTRAL/NEGATIVE), signals (per-indicator breakdown). Computed from the same indicators block, no extra AI cost.
signals	object	pro Flat labeled technical signals - overall + rsi/macd/bollinger/sma200/sma50/williams_r/ultimate_osc/vix_fix/williams_ad/td_sequential/elliott_wave, each with a plain-English label pre-interpreted for programmatic use.
stance_signals	array	pro Unified list of per-source directional calls - technical rating, AI summary (near_term + longer_term), insider/institutional sentiment, analyst consensus, and any active screener signals. Each entry: stance (POSITIVE/NEGATIVE/NEUTRAL), conviction (0-10), horizon (INTRADAY/SWING/POSITION/LONG_TERM), edge_quality (PROVEN/OBSERVATION/UNKNOWN - that source's own signal_backtest track record), source, raw_label, as_of. A source with no data for this stock is simply omitted, not returned as null.
relative_strength	object	pro Multi-window relative strength vs SPY, QQQ, and the stock's GICS sector ETF. windows: 5d/20d/60d/120d/12m → stock_return_pct plus rs_vs_spy/rs_vs_qqq/rs_vs_sector (percentage-point spread, stock return minus benchmark return - not a ratio). verdict: one-line plain-language read, e.g. "Laggard - weak near- and long-term". Windows/benchmarks with insufficient history are simply omitted; null if not precomputed yet for this symbol.
ai_verdict / ai_headline	string / string	pro The minimum useful AI-narrative slice, precomputed (no extra AI cost) - positive/neutral/negative verdict and a one-line "why". For the full text (summary/key_points/risks/near_term/longer_term), call get_stock_research.
ai_score / ai_score_band	number \| null / string \| null	pro 0-100 AI research composite score - same 0-100 scale/band convention as get_signals' signal_score but a distinct field/pipeline. Band: Weak / Moderate / Strong / Very Strong. Null if no ai_summary doc exists yet.
forensic_scores	object	pro Three classic forensic-accounting formulas computed from balance sheet/income statement/cash flow data, refreshed on each company's own filing cadence (roughly annual): altman_z {score, zone: safe/grey/distress} - Altman 1968 bankruptcy-risk composite; piotroski_f {score 0-9, strength: strong/moderate/weak} - Piotroski 2000 fundamental-strength score; beneish_m {score, likely_manipulator: bool} - Beneish 1999 earnings-manipulation-likelihood score (a screening heuristic, not a determination of actual manipulation). Every sub-block also carries a note explaining what it measures and known caveats - e.g. Altman Z isn't meaningful for banks/insurers and can flag REITs or client-money-float businesses as "distress" by design, not because anything is wrong. score: null means genuinely not computable for this company (common for financial-sector names), not an error. computed_at: ISO 8601 timestamp. No trading signal is derived from these scores anywhere in this API today.
sector_context	object	pro Where this stock's fundamentals sit versus the other tracked equities in its own sector: revenue_growth, gross_margin and operating_margin, each {value, sector_median, percentile, n} - percentile is 0-100 (share of sector peers below this stock, ties counted half), n the number of peers with data. Purely descriptive positioning - no interpretation or direction. A metric is omitted when the stock has no value or the sector has fewer than 15 peers with data; the whole block is omitted when nothing is computable. Sectors are pooled globally across all tracked equities; baseline refreshed daily (as_of). get_stock (not get_stocks) also returns trend: {period: "quarterly", points: [...]}, oldest first - the same three metrics for the last few quarters (revenue growth is year-over-year), each as {value, sector_median, n} beside the sector median for that quarter, so you can see whether a company is gaining or losing ground on its peers. Off-cycle fiscal quarters are matched to the nearest calendar quarter; a quarter or metric is left out where either side lacks data.

Example

{
  "symbol": "NVDA",
  "name": "NVIDIA Corporation",
  "price": 116.78,
  "change_pct": 2.31,
  "market_cap": 2847000000000,
  "pe_trailing": 38.2,
  "analyst_rating": "buy",
  "analyst_target": 165.00,
  "indicators": {
    "rsi": 58.4,
    "macd": { "macd_line": 1.23, "signal_line": 0.94, "histogram": 0.29 },
    "bollinger_bands": { "upper_band": 124.1, "middle_band": 114.3, "lower_band": 104.5 }
  }
}

Example - META (Communication Services, strong buy consensus)

{
  "symbol": "META",
  "name": "Meta Platforms Inc.",
  "short_name": "Meta",
  "price": 635.29,
  "change_pct": 1.54,
  "volume": 18720000,
  "market_cap": 1612600000000,
  "pe_trailing": 27.8,
  "analyst_rating": "strong_buy",
  "analyst_target": 725.00,
  "indicators": {
    "rsi": 65.3,
    "macd": { "macd_line": 8.45, "signal_line": 6.12, "histogram": 2.33 },
    "bollinger_bands": { "upper_band": 652.80, "middle_band": 598.40, "lower_band": 544.00 }
  }
}

Example - Pro tier rating + signals (appended alongside the fields above)

{
  "rating": { "score": 6.0, "direction": "POSITIVE",
    "signals": { "rsi": { "verdict": "mild_negative", "text": "strong (65.7) - mild negative" },
      "macd": { "verdict": "positive", "text": "above signal - positive crossover" },
      "trend": { "verdict": "positive", "text": "price > SMA50 > SMA200 - strong uptrend" } } },
  "signals": { "overall": "POSITIVE",
    "rsi": { "value": 65.7, "signal": "approaching_overbought" },
    "macd": { "signal": "positive", "histogram": 0.8984, "strength": "moderate" },
    "sma200": { "trend": "above", "gap_pct": 20.7 } }
}

Example - Pro tier stance_signals (appended alongside the fields above)

{
  "stance_signals": [
    { "stance": "POSITIVE", "conviction": 2, "horizon": "SWING",
      "edge_quality": "UNKNOWN", "source": "technical_rating", "raw_label": "6.0/10", "as_of": "2026-07-31T14:02:11+00:00" },
    { "stance": "POSITIVE", "conviction": 7, "horizon": "LONG_TERM",
      "edge_quality": "UNKNOWN", "source": "ai_summary", "raw_label": "Cloud momentum accelerating into next earnings", "as_of": "2026-07-30T22:15:00+00:00" },
    { "stance": "POSITIVE", "conviction": 9, "horizon": "LONG_TERM",
      "edge_quality": "UNKNOWN", "source": "analyst_consensus", "raw_label": "Strong Buy (58 analysts)", "as_of": "2026-07-31T14:02:11+00:00" }
  ]
}

Example - Pro tier relative_strength (appended alongside the fields above)

{
  "relative_strength": {
    "windows": {
      "5d":   { "stock_return_pct": -8.31, "rs_vs_spy": -9.38, "rs_vs_qqq": -9.17, "rs_vs_sector": -8.91 },
      "20d":  { "stock_return_pct": -1.25, "rs_vs_spy": -0.68, "rs_vs_qqq": 3.57,  "rs_vs_sector": 3.23 },
      "60d":  { "stock_return_pct": 7.54,  "rs_vs_spy": 5.48,  "rs_vs_qqq": 8.55,  "rs_vs_sector": 4.29 },
      "120d": { "stock_return_pct": 12.59, "rs_vs_spy": 4.37,  "rs_vs_qqq": 0.33,  "rs_vs_sector": -10.03 },
      "12m":  { "stock_return_pct": 49.41, "rs_vs_spy": 29.91, "rs_vs_qqq": 27.06, "rs_vs_sector": 15.23 }
    },
    "verdict": "Mixed - lagging near-term, outperforming long-term"
  }
}

Example - Pro tier AI-narrative slice (appended alongside the fields above)

{
  "ai_verdict": "positive",
  "ai_headline": "Data center demand still outpacing supply into next quarter",
  "ai_score": 72, "ai_score_band": "Strong"
}

get_stocks free+

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, not a thinned-down scan. Returns prices, fundamentals, and indicators keyed by symbol. Each symbol in the batch counts as one call toward your daily limit. Pro tier adds the same precomputed rating/signals/relative_strength blocks as get_stock, together with forensic_scores, market_risk and sector_context (without its quarterly trend), plus ai_verdict/ai_headline/ai_score/ai_score_band per symbol - no extra AI cost. Not included even on Pro: stance_signals and the full ai_summary text - call get_stock/get_stock_research for those.

Parameter	Type	Default	Description
symbols	array of strings	required	Stock tickers (max 25). Symbols with hyphens (e.g. BRK-B) are supported. Invalid symbols are silently skipped.

curl -s https://api.stocklake.dev/mcp \
  -H "Authorization: Bearer sl_your_key" \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_stocks","arguments":{"symbols":["JPM","GS"]}}}'

Example response

{
  "count": 2,
  "symbols": {
    "JPM": {
      "symbol": "JPM",
      "name": "JPMorgan Chase & Co.",
      "sector": "Financial Services",
      "price": 296.73,
      "change_pct": -0.42,
      "volume": 8930000,
      "analyst_rating": "strong_buy",
      "indicators": {
        "rsi": 42.6,
        "macd": { "macd_line": -1.20, "signal_line": -0.80, "histogram": -0.40 },
        "bollinger_bands": { "upper_band": 312.50, "middle_band": 298.10, "lower_band": 283.70 }
      },
      "updated_at": "2026-06-01T14:00:00+00:00"
    },
    "GS": {
      "symbol": "GS",
      "name": "The Goldman Sachs Group Inc.",
      "sector": "Financial Services",
      "price": 1008.37,
      "change_pct": 0.87,
      "volume": 2100000,
      "analyst_rating": "buy",
      "indicators": {
        "rsi": 68.2,
        "macd": { "macd_line": 5.60, "signal_line": 4.10, "histogram": 1.50 },
        "bollinger_bands": { "upper_band": 1050.00, "middle_band": 985.00, "lower_band": 920.00 }
      },
      "updated_at": "2026-06-01T14:00:00+00:00"
    }
  },
  "requested": 2
}

Response includes the count of matched symbols plus a map with per-symbol data in the same format as get_stock. Requested symbols not found in the database are omitted from the result.

get_stock_history free+

Daily OHLCV price history for a ticker. Returns bars sorted oldest-first.

Parameters

Name	Type	Default	Description
symbol	string	-	Ticker symbol
days	integer	90	Number of trading days to return. Guest and free: max 365 (1 year). Pro: full history, up to 20,000 trading days - most established names go back decades. A full pull can be 10,000+ bars, so request only the window you need.

Response fields

Field	Type	Description
symbol	string	Ticker
days_requested	integer	The `days` you asked for, before any tier cap
days_returned	integer	Bars in this response (same as `count`)
count	integer	Bars actually returned (may be less if data is newer)
history	array	OHLCV bars: date, open, high, low, close, volume
history_available	object	`{bars, earliest_date}` - how much daily history exists for this ticker in total, regardless of the window returned
pro_unlocks	string	Present when a guest/free call asked for more than 365 days and was capped: says what Pro unlocks (the full history)

Example

{
  "symbol": "AAPL",
  "days": 5,
  "count": 5,
  "history": [
    { "date": "2026-04-29", "open": 208.40, "high": 212.10, "low": 207.80, "close": 211.50, "volume": 52183000 },
    { "date": "2026-04-30", "open": 211.20, "high": 214.60, "low": 210.90, "close": 213.45, "volume": 48921000 }
  ]
}

Example - AMZN 30-day history

{
  "symbol": "AMZN",
  "days": 30,
  "count": 22,
  "history": [
    { "date": "2026-04-29", "open": 247.40, "high": 250.60, "low": 246.80, "close": 249.75, "volume": 31045000 },
    { "date": "2026-04-30", "open": 250.00, "high": 256.10, "low": 249.20, "close": 255.30, "volume": 28760000 },
    { "date": "2026-05-01", "open": 257.10, "high": 264.80, "low": 256.40, "close": 263.90, "volume": 35412000 }
  ]
}

get_market_pulse free

Live market health snapshot in a single call. Aggregates VIX, Fear & Greed index, market breadth, and key index prices - no AI cost, always live data.

Use this as a lightweight context check before making any investment decisions. Replaces the need to call multiple separate endpoints for basic macro state.

No parameters - returns the current market snapshot.

Response fields

Field	Type	Description
vix	number	VIX level at last pipeline run
fear_greed.value	number	Fear & Greed index 0-100
fear_greed.description	string	Label: "extreme fear" · "fear" · "neutral" · "greed" · "extreme greed"
breadth.oversold_pct	number	% of tracked stocks with RSI < 30
breadth.overbought_pct	number	% of tracked stocks with RSI > 70
breadth.neutral_pct	number	% of tracked stocks with RSI 30-70
breadth.universe_size	integer	Total stocks in the tracked universe
indices.spy / qqq / iwm	object	Live price, change_pct, RSI for SPY / QQQ / IWM
bonds_commodities.tlt / gld	object	TLT (long bonds) and GLD (gold) - price, change_pct, RSI
updated_at	string	ISO 8601 UTC timestamp of breadth + fear/greed snapshot - vix/indices/bonds_commodities above are live, but this snapshot comes from the same market intelligence pipeline as get_market_assessment (~4x/day, weekdays only, during market hours - dead overnight/weekends)

Example response

{
  "vix": 15.71,
  "fear_greed": { "value": 55.0, "description": "neutral" },
  "breadth": {
    "universe_size": 3501,
    "oversold_pct": 2.0,
    "overbought_pct": 7.6,
    "neutral_pct": 90.4
  },
  "indices": {
    "spy": { "price": 757.09, "change_pct": 0.38, "rsi": 67.97 },
    "qqq": { "price": 733.81, "change_pct": 0.62, "rsi": 73.66 },
    "iwm": { "price": 292.01, "change_pct": -0.31, "rsi": 57.73 }
  },
  "bonds_commodities": {
    "tlt": { "price": 85.64, "change_pct": -0.42, "rsi": 52.41 },
    "gld": { "price": 411.27, "change_pct": -0.18, "rsi": 38.43 }
  },
  "data_age_hours": 0.7
}

get_earnings_calendar free+

Upcoming earnings dates for all stocks in the Stocklake universe, within a configurable look-ahead window. Dates sourced from market data - treat is_estimate: true dates as approximate.

Parameters

Parameter	Type	Default	Description
days	integer	7	Look-ahead window in days (max 30)

Response

Field	Type	Description
window_days	number	Effective look-ahead window applied
from_date	string	Window start (UTC ISO)
to_date	string	Window end (UTC ISO)
count	number	Total results returned
results[].symbol	string	Ticker symbol
results[].name	string	Company short name
results[].sector	string	Sector
results[].market_cap	number	Market capitalisation in reporting currency
results[].price	number	Current stock price
results[].rsi	number \| null	Current RSI - useful for pre-earnings momentum screening
results[].earnings_date	string	Expected earnings timestamp (UTC ISO)
results[].is_estimate	boolean	True if the date is an estimate - treat as approximate
results[].eps_trailing	number \| null	Trailing 12-month EPS
results[].eps_forward	number \| null	Forward EPS estimate

Example response

{
  "window_days": 7,
  "from_date": "2026-05-06T10:00:00+00:00",
  "to_date": "2026-05-13T10:00:00+00:00",
  "count": 3,
  "results": [
    {
      "symbol": "AAPL",
      "name": "Apple Inc.",
      "sector": "Technology",
      "market_cap": 3200000000000,
      "earnings_date": "2026-05-08T20:30:00+00:00",
      "is_estimate": false,
      "eps_trailing": 6.97,
      "eps_forward": 7.54
    }
  ]
}

Example - 30-day window

{
  "window_days": 30,
  "from_date": "2026-05-06T10:00:00+00:00",
  "to_date": "2026-06-05T10:00:00+00:00",
  "count": 4,
  "results": [
    {
      "symbol": "AMD",
      "name": "Advanced Micro Devices Inc.",
      "sector": "Technology",
      "market_cap": 845000000000,
      "earnings_date": "2026-05-20T20:30:00+00:00",
      "is_estimate": false,
      "eps_trailing": 3.95,
      "eps_forward": 4.82
    },
    {
      "symbol": "INTC",
      "name": "Intel Corporation",
      "sector": "Technology",
      "market_cap": 608000000000,
      "earnings_date": "2026-05-22T21:00:00+00:00",
      "is_estimate": false,
      "eps_trailing": 2.41,
      "eps_forward": 3.10
    },
    {
      "symbol": "IBM",
      "name": "International Business Machines Corp.",
      "sector": "Technology",
      "market_cap": 248000000000,
      "earnings_date": "2026-05-28T20:30:00+00:00",
      "is_estimate": true,
      "eps_trailing": 6.58,
      "eps_forward": 7.22
    }
  ]
}

get_screener free

Filter and rank stocks from the Stocklake universe - fundamentals, technicals, and (Pro) AI signals in one tool. Presets provide one-call screens for common setups.

Parameters

Name	Type	Default	Description
preset	string	-	oversold (RSI≤35, above SMA200) · overbought (RSI≥65) · momentum (RSI 50-70, above SMA200, up 0.5%+) · high_conviction (ai_score≥70, Pro only)
sector	string	-	e.g. "Technology", "Healthcare"
country	string	-	e.g. "United States", "Germany"
min_rsi / max_rsi	number	-	Exact RSI bounds (e.g. min_rsi=30, max_rsi=50 = post-oversold recovery zone)
sma_trend	string	-	above_200 / below_200 - price vs 200-day MA
macd_signal	string	-	positive / negative - MACD line vs signal line
min_perf_1d / max_perf_1d	number	-	1-day performance % bounds (e.g. min_perf_1d=2.0 = up 2%+ today)
min_volume	integer	-	Minimum daily volume. e.g. 1000000
min_market_cap_b / max_market_cap_b	number	-	Market cap in billions of US dollars, compared against market_cap_usd (non-USD listings are converted first)
max_pe_forward	number	-	Maximum forward P/E
analyst_rating	string	-	strong_buy / buy / hold / sell / strong_sell
min_ai_score	integer	-	Minimum AI score 0-100 - Pro tier only. Gates on the same `ai_score` field returned below (renamed 2026-08-24 from the retired 0-10 `min_flag_score`).
sort_by	string	market_cap	market_cap / rsi / perf_1d / volume / analyst_rating / rating / ai_score (Pro)
sort_dir	string	desc	asc / desc
limit	integer	20	1-25. Each returned stock counts as one call toward your daily limit.

Response fields (per result)

Field	Type	Description
symbol, name, sector, industry, country	string	Stock identity
price, change_pct, volume	number	Current price, 1-day change %, day volume
market_cap, pe_forward	number	Fundamentals (market_cap in the listing's own currency)
market_cap_usd, currency	number \| null, string	Market cap in US dollars (what the market_cap sort and cap filters use) and the listing currency
rsi	number	RSI value
macd_signal	string	positive / negative / neutral
sma200_trend	string	above / below
analyst_rating	string	buy / hold / sell etc.
rating	number	0-10 technical composite score
ai_verdict	string	Pro only - positive / neutral / negative
ai_score	number \| null	Pro only - 0-100 AI research composite score, same scale/band convention as get_signals' signal_score but a distinct field/pipeline. Null if no ai_summary doc exists yet.
ai_score_band	string \| null	Pro only - Weak / Moderate / Strong / Very Strong, or null

Example - preset: oversold

{
  "count": 8,
  "preset": "oversold",
  "filters": { "max_rsi": 35, "sma_trend": "above_200", "sort_by": "market_cap", "sort_dir": "desc" },
  "results": [
    { "symbol": "VZ", "name": "Verizon Communications", "sector": "Communication Services", "industry": "Telecom Services", "country": "United States",
      "price": 38.42, "change_pct": -0.8, "volume": 18400000, "rsi": 28.9, "macd_signal": "negative",
      "sma200_trend": "above", "analyst_rating": "hold", "rating": 3.4,
      "ai_score": 62, "ai_score_band": "Moderate" }
  ]
}

get_market_movers free

Top market movers from the Stocklake universe - gainers, losers, and most active by volume. A fast way to see what's moving in the market right now.

Parameters

Name	Type	Default	Description
category	string	all	gainers / losers / most_active / all (all returns all 3 categories)
limit	integer	10	Results per category (max 20). Each returned stock counts as one call toward your daily limit - a symbol appearing in more than one category counts once per category.
min_market_cap_b	number	-	Filter to stocks above this market cap in billions of US dollars (e.g. 1.0 = $1B+ only), compared against market_cap_usd

Response

Returns gainers[], losers[], most_active[] (whichever categories requested). Each entry: symbol, name, sector, price, change_pct, volume, rsi, market_cap (listing currency), market_cap_usd, currency, analyst_rating, atr_pct (volatility as % of price - omitted when the underlying reading is missing or corrupted). pro adds ai_verdict / ai_headline / ai_score (0-100) / ai_score_band (Weak/Moderate/Strong/Very Strong) - a big move's price/volume/RSI alone doesn't say whether it matters; the headline is the "why".

Example

{
  "category": "all", "limit_per_category": 3,
  "gainers": [
    { "symbol": "SMCI", "name": "Super Micro Computer", "sector": "Technology",
      "price": 48.20, "change_pct": 18.4, "volume": 42810000, "rsi": 67.2, "market_cap": 28400000000, "analyst_rating": "buy", "atr_pct": 6.85,
      "ai_verdict": "positive", "ai_headline": "Server backlog extending into next fiscal year",
      "ai_score": 69, "ai_score_band": "Strong" }
  ],
  "losers": [
    { "symbol": "WBA", "name": "Walgreens Boots Alliance", "sector": "Healthcare",
      "price": 9.82, "change_pct": -12.7, "volume": 18200000, "rsi": 22.4, "market_cap": 8500000000, "analyst_rating": "hold", "atr_pct": 4.12 }
  ],
  "most_active": [
    { "symbol": "TSLA", "name": "Tesla", "sector": "Consumer Cyclical",
      "price": 192.40, "change_pct": 2.1, "volume": 94000000, "rsi": 54.8, "market_cap": 614000000000, "analyst_rating": "buy", "atr_pct": 3.27 }
  ]
}

get_indicator_history pro

Daily indicator snapshots for a symbol - up to 2 years of history. Default returns RSI, MACD histogram, Bollinger band position, and 20/200-day SMA per day - enough for most charting and trend analysis. Pass full=true to also get Williams %R, VIX Fix, Williams A/D trend, DeMark TD Sequential, and analyst rating/target, which barely change day to day and roughly double response size over a long window.

Parameters

Name	Type	Default	Description
symbol	string	-	Ticker symbol
days	integer	90	Number of calendar days to look back. Max 730 (2 years).
full	boolean	false	false returns the 5 basic fields below per day; true adds the 8 specialized/slow-moving fields marked "full only".

Response fields

Field	Type	Description
symbol	string	Ticker
days	integer	Days requested
full	boolean	Echoes the requested full param
count	integer	Snapshots returned
snapshots	array	Snapshots sorted oldest-first (see fields below). Empty (with a note field instead) if fewer than 3 found.
snapshots[].recorded_at	string	Snapshot date, YYYY-MM-DD
snapshots[].price	number	Price at snapshot time
snapshots[].rsi	number	RSI(14) value
snapshots[].macd_histogram	number	MACD histogram (line − signal)
snapshots[].bb_pct	number	Bollinger band position 0-100: 0 = at lower band, 100 = at upper band
snapshots[].sma20 / sma200	number	20-day and 200-day simple moving averages
snapshots[].williams_r	number	full only. Williams %R (0 to −100)
snapshots[].ultimate_osc	number	full only. Ultimate Oscillator (0-100; >70 overbought, <30 oversold)
snapshots[].vix_fix_value	number	full only. Williams VIX Fix synthetic fear gauge (higher = more fear)
snapshots[].williams_ad_trend	string	full only. rising / falling / flat
snapshots[].td_signal	string \| null	full only. The most recent completed TD Sequential setup or countdown as of that day, named for the move that is running out: DOWNTREND_EXHAUSTION_SETUP / UPTREND_EXHAUSTION_SETUP / DOWNTREND_EXHAUSTION_COUNTDOWN / UPTREND_EXHAUSTION_COUNTDOWN / null
snapshots[].td_phase	string \| null	full only. setup_active / setup_complete / countdown_active / countdown_done / null
snapshots[].analyst_rating	string \| null	full only. buy / outperform / hold / underperform / sell / null
snapshots[].analyst_target	number \| null	full only. Mean analyst price target

Example - default (full=false)

{
  "symbol": "NVDA",
  "days": 90,
  "full": false,
  "count": 87,
  "snapshots": [
    {
      "recorded_at": "2026-04-02",
      "price": 103.20,
      "rsi": 28.4,
      "macd_histogram": -1.82,
      "bb_pct": 6.3,
      "sma20": 112.40,
      "sma200": 128.90
    }
  ]
}

Example - full=true

{
  "symbol": "NVDA",
  "days": 90,
  "full": true,
  "count": 87,
  "snapshots": [
    {
      "recorded_at": "2026-04-02",
      "price": 103.20,
      "rsi": 28.4,
      "macd_histogram": -1.82,
      "bb_pct": 6.3,
      "sma20": 112.40,
      "sma200": 128.90,
      "williams_r": -88.1,
      "ultimate_osc": 22.7,
      "vix_fix_value": 18.6,
      "williams_ad_trend": "falling",
      "td_signal": null,
      "td_phase": null,
      "analyst_rating": "buy",
      "analyst_target": 142.00
    },
    {
      "recorded_at": "2026-07-01",
      "price": 142.85,
      "rsi": 61.3,
      "macd_histogram": 2.14,
      "bb_pct": 68.7,
      "sma20": 136.10,
      "sma200": 131.20,
      "williams_r": -24.5,
      "ultimate_osc": 58.1,
      "vix_fix_value": 9.3,
      "williams_ad_trend": "rising",
      "td_signal": "DOWNTREND_EXHAUSTION_SETUP",
      "td_phase": "setup_active",
      "analyst_rating": "buy",
      "analyst_target": 160.00
    }
  ]
}

get_stock_financials free+

Raw financial statements - balance sheet, income statement, and cash flow line items. 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 you get every available period per line item and can compute your own trends/deltas/CAGRs, not just the latest value. Values are in the company's reporting currency (financial_currency), which can differ from the trading currency. ~50-60 curated line items per statement (not a raw dump of every reported row); 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 the company doesn't report it, not a fetch error.

Free and guest get the latest fiscal year: all three statements, one period per line item, and the statement filter works. Asking for quarterly or both returns that latest annual year with quarterly: null and a pro_unlocks note, not an error. Pro gets up to 5 fiscal years, the ~7-8 most recent quarters, and period=both.

Parameters

Name	Type	Default	Description
symbol	string	-	Ticker symbol. Also accepts a company name as a fallback when it uniquely resolves to one symbol.
period	string	annual	annual (Pro: up to 5 fiscal years; free: the latest fiscal year), quarterly (Pro: up to ~7-8 most recent quarters), or both (Pro). Free/guest asking for quarterly/both get the latest annual year plus pro_unlocks.
statement	string	all	all, balance_sheet, income_stmt, or cash_flow - restricts which statement(s) come back.

Response fields

Field	Type	Description
symbol	string	Ticker
period	string	Echoes the requested period
statement	string	Echoes the requested statement
period_end	string	Latest annual fiscal-year-end on file, for reference
financial_currency	string	Reporting currency of the statement values, e.g. USD, EUR, JPY
annual	object \| null	Present when period is annual or both, and always for free/guest. On free/guest it holds only the latest fiscal year (periods has one date). {periods: [...], balance_sheet: {...}, income_stmt: {...}, cash_flow: {...}} (narrowed to one statement key if statement isn't all). null with an annual_note if this symbol hasn't been widened yet.
quarterly	object \| null	Present when period is quarterly or both. Same shape as annual. null with a quarterly_note if not yet fetched, or if this symbol genuinely has no usable quarterly data. Always null for free/guest (see pro_unlocks).
annual_periods_available	integer	Free/guest only: how many fiscal years are on file, i.e. what Pro would return
pro_unlocks	string	Free/guest only: what Pro adds for this symbol (more fiscal years, quarterly statements)
note	string	Present instead of annual/quarterly when this symbol has no financials data on file at all (not yet synced, or a non-equity with no statement data - ETFs/crypto/forex/indices aren't covered by this tool).

Example - Pro, period=annual, statement=income_stmt

{
  "symbol": "MSFT",
  "period": "annual",
  "statement": "income_stmt",
  "period_end": "2026-06-30",
  "annual": {
    "periods": ["2026-06-30", "2025-06-30", "2024-06-30", "2023-06-30", "2022-06-30"],
    "income_stmt": {
      "Total Revenue": {"2026-06-30": 315000000000, "2025-06-30": 281000000000},
      "Diluted EPS": {"2026-06-30": 13.42, "2025-06-30": 11.80}
    }
  }
}

Example - free tier, period=quarterly, statement=cash_flow

{
  "symbol": "AAPL",
  "period": "quarterly",
  "statement": "cash_flow",
  "period_end": "2025-09-30",
  "financial_currency": "USD",
  "annual": {
    "periods": ["2025-09-30"],
    "cash_flow": {
      "Operating Cash Flow": {"2025-09-30": 111482000000},
      "Free Cash Flow": {"2025-09-30": 98767000000}
    }
  },
  "quarterly": null,
  "annual_periods_available": 5,
  "pro_unlocks": "Free returns the latest fiscal year only. Pro unlocks the full 5-year annual history on file for this symbol and the most recent ~7-8 quarters - for trend, growth and margin analysis."
}

get_analyst_trend pro

How analyst consensus on a stock has moved over time - the trajectory of the rating and the price targets, not just today's value. get_stock gives the current analyst_rating and analyst_target; this tool answers "are analysts getting more or less positive on this name?" with one row per day, up to a year back. Snapshots are taken once per weekday, so a 90-day window is roughly 60 rows. History begins July 2026 and grows daily.

Parameters

Name	Type	Default	Description
symbol	string	-	Ticker symbol. A company name is accepted as a fallback when it resolves to exactly one symbol.
days	integer	90	Number of calendar days to look back. Max 365.

Response fields

Field	Type	Description
symbol	string	Ticker
days	integer	Days requested (after clamping to 1-365)
count	integer	Snapshots returned
snapshots	array	Snapshots sorted oldest-first (see fields below). Empty, with a note field instead, if fewer than 2 exist in the window - a single point is not a trend.
snapshots[].date	string	Snapshot date, YYYY-MM-DD
snapshots[].analyst_rating	string \| null	Consensus label: strong_buy / buy / hold / underperform / sell / strong_sell. Derived from analyst_rating_score on days the source reports no label.
snapshots[].analyst_rating_score	number \| null	Mean recommendation: 1.0 = strong buy, 5.0 = strong sell (lower is more positive). Same scale as get_stock.
snapshots[].analyst_count	integer \| null	Number of analysts contributing
snapshots[].analyst_target	number \| null	Mean analyst price target
snapshots[].analyst_target_high / analyst_target_low	number \| null	Highest and lowest individual price target
snapshots[].analyst_target_median	number \| null	Median price target
snapshots[].price	number \| null	The stock's price on that date, so a target can be read against where the stock actually traded

A field is null on a day the source reported none - a symbol's rating can be null on some days even when its price targets are present, because the source occasionally drops the consensus label. A weekday can also be missing entirely when the daily snapshot did not run; those days cannot be reconstructed, so the date is simply absent. Most of the tracked universe has a usable history; ETFs and other instruments with no analyst coverage return an empty snapshots array. For price and indicator history, see get_indicator_history - this tool covers analyst consensus only.

Example - AAPL, consensus drifting slightly less positive as the mean target rises

{
  "symbol": "AAPL",
  "days": 90,
  "count": 3,
  "snapshots": [
    {
      "date": "2026-07-10",
      "analyst_rating": "buy",
      "analyst_rating_score": 2.02,
      "analyst_count": 42,
      "analyst_target": 315.57,
      "analyst_target_high": 400.0,
      "analyst_target_low": 215.0,
      "analyst_target_median": 315.0,
      "price": 316.75
    },
    {
      "date": "2026-08-14",
      "analyst_rating": "buy",
      "analyst_rating_score": 2.13,
      "analyst_count": 41,
      "analyst_target": 322.28,
      "analyst_target_high": 400.0,
      "analyst_target_low": 215.0,
      "analyst_target_median": 335.0,
      "price": 305.7
    },
    {
      "date": "2026-09-18",
      "analyst_rating": "buy",
      "analyst_rating_score": 2.2,
      "analyst_count": 39,
      "analyst_target": 327.84,
      "analyst_target_high": 405.0,
      "analyst_target_low": 215.0,
      "analyst_target_median": 340.0,
      "price": 335.94
    }
  ]
}

get_economic_calendar free+

Upcoming and recently-released macro/economic events - interest rate decisions, CPI, GDP, PMI, unemployment, payrolls, retail sales, and more.

Two buckets: released_recent always carries a real actual value (never blank) plus diff - a plain arithmetic difference, actual minus previous, never a beat/miss or consensus judgment, since point-in-time consensus is not available. upcoming never 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.

Free vs Pro. Every tier gets the same tool, filters and response shape - only the window differs. Guest and free: up to 7 days ahead (days), 2 days back (lookback_days) and 20 results per bucket (limit). Pro: up to 14 days ahead, 7 days back and 50 per bucket. A guest/free value above its cap is served at the cap, and the response adds capped and a pro_unlocks note - never an error.

Parameters

Name	Type	Default	Description
days	integer	3	Look-ahead window in days for upcoming events. Max 7 on guest/free, 14 on Pro.
lookback_days	integer	2	Look-back window in days for recently-released events. Max 2 on guest/free, 7 on Pro. Actual values arrive with about a 1-day reporting lag - keep this at 2+ to reliably see real releases.
limit	integer	20	Max results per bucket - released_recent and upcoming each capped independently. Max 20 on guest/free, 50 on Pro.
major_only	boolean	false	Restrict to the 8 largest economies: United States, Euro Area, United Kingdom, Japan, China, Germany, France, Canada.
key_events_only	boolean	false	Restrict to rate decisions, CPI, GDP, and headline Non-Farm Payrolls - the subset flagged key_event: true.

Response fields

Field	Type	Description
window_days	integer	Effective look-ahead window applied
lookback_days	integer	Effective look-back window applied
today	string	Server's current date, YYYY-MM-DD (UTC)
released_recent	array	Recently-released events, major-economy-first then most-recent-first
released_recent[].country	string	Country or region name
released_recent[].event	string	Event name
released_recent[].date	string	Release date, YYYY-MM-DD
released_recent[].time	string \| null	Release time, UTC, when known
released_recent[].actual	string	Reported value. Always present in this bucket.
released_recent[].previous	string \| null	Prior period's value
released_recent[].consensus	string \| null	Market consensus, when one is available (often null - see note above)
released_recent[].diff	string \| null	actual minus previous, signed (e.g. "+0.1", "-2.7"). Null if either value is missing or non-numeric. Never a beat/miss judgment.
released_recent[].key_event	boolean	true for rate decisions, CPI, GDP, or headline Non-Farm Payrolls
upcoming	array	Not-yet-released events, major-economy-first then soonest-first. Same fields as released_recent except no actual/diff.
released_total / upcoming_total	integer	How many events matched before the row limit was applied.
truncated_note	string	Present only when the row limit cut a list. Lists are major-economy-first, so a cut list can end days before the window does; narrow with key_events_only or major_only.
capped	object	Guest/free only, present only when a value was above the free cap. One entry per capped param, e.g. {"days": {"requested": 14, "served": 7}}.
pro_unlocks	string	Present alongside capped: what Pro unlocks (14 days ahead, 7 back, 50 per bucket).

Example

{
  "window_days": 3,
  "lookback_days": 2,
  "today": "2026-09-02",
  "released_recent": [
    {
      "country": "Germany",
      "event": "CPI Prelim YY *",
      "date": "2026-08-31",
      "time": "12:00 UTC",
      "actual": "2.9",
      "previous": "2.8",
      "consensus": null,
      "diff": "+0.1",
      "key_event": true
    },
    {
      "country": "United States",
      "event": "ISM Manufacturing PMI",
      "date": "2026-09-01",
      "time": "14:00 UTC",
      "actual": "54.6",
      "previous": "55.6",
      "consensus": null,
      "diff": "-1",
      "key_event": false
    }
  ],
  "upcoming": [
    {
      "country": "Canada",
      "event": "BoC Rate Decision",
      "date": "2026-09-02",
      "time": "14:00 UTC",
      "actual": null,
      "previous": "2.25",
      "consensus": null,
      "key_event": true
    },
    {
      "country": "United States",
      "event": "Non-Farm Payrolls",
      "date": "2026-09-04",
      "time": null,
      "actual": null,
      "previous": "-23",
      "consensus": null,
      "key_event": true
    }
  ]
}

get_stock_news free+ AI

Returns AI-analysed news articles for a ticker. Each article has been processed by our AI pipeline - raw article content is not exposed. Free/guest get up to 5 headlines (title and date, no AI fields); Pro gets up to 50 articles with a full AI summary, plus this symbol's live signal_score, over a 90-day window.

One article per event: articles about the same event are merged into the newest one, so limit counts distinct events. Articles without a usable summary are left out.

When no articles are found, the ticker is automatically queued for a background refresh. Re-queuing an already-pending ticker does not count against your limit.

Parameters

Name	Type	Description
symbol	string	Ticker symbol
limit	integer	Max articles to return. Default 10. Guest and free: up to 5. Pro: up to 50.
days	integer	Look-back window in days. Default 30. Guest and free: max 30. Pro: max 90.

Response

Outer envelope fields:

Field	Type	Description
symbol	string	Ticker
status	string	ok empty - see below
count	integer	Number of articles returned
days	integer	Effective look-back window in days (guest and free max 30, Pro max 90)
articles	array	Article objects (see below)
message	string	Present when status is empty

Status values:

ok - articles returned
empty - no news found for this window; pipeline triggered in background if data was stale

Per-article fields:

Field	Type	Description
title	string	Article headline
published_at	datetime	Publication timestamp (ISO 8601)
ai_sentiment	string	Pro only. POSITIVE / NEUTRAL / NEGATIVE / MIXED
ai_summary	string	Pro only. Full AI-generated summary of the article's relevance to the stock
signal_score	number \| null	Pro only. If this symbol has a currently-active news-sourced signal, every article shows that LIVE score - same value get_signals/get_stock_research report, kept in sync as the signal is re-scored (a per-symbol value, so every article for the symbol shows the same number then). Always a single number even then - for a genuinely two-sided signal (real opposing bull/bear theses, direction NEUTRAL), this is the stronger of the two sides. When there's no active signal for the symbol, each article instead gets its own per-article magnitude computed from that article's own AI classification - so different articles can show different numbers in that case. Null only when neither a live signal nor a computable per-article value exists.
signal_score_band	string \| null	Pro only. Weak / Moderate / Strong / Very Strong. Null when signal_score is null.
collapsed_count	integer	Present only when several articles reported the same event (for example one analyst's target change carried by several outlets). Only the newest is returned; this is the number of articles merged into it.

Note: there is no field called news_score anywhere on this API - signal_score is the one name, whether it resolves to a per-symbol live signal (preferred here when one exists) or a per-article magnitude (the fallback here when it doesn't, and the norm on get_news_feed, ranked by its own AI-assessed strength).

Example - status ok

{
  "symbol": "TSLA",
  "status": "ok",
  "count": 3,
  "days": 30,
  "articles": [
    {
      "title": "Tesla Q1 deliveries beat expectations",
      "published_at": "2026-04-03T14:00:00+00:00",
      "ai_sentiment": "positive",
      "ai_summary": "Q1 deliveries of 387k beat analyst consensus of 375k, signalling demand stabilisation and easing investor concerns over weakening EV demand.",
      "signal_score": { "POSITIVE": 72.3, "NEGATIVE": 39.6 }, "signal_score_band": null
    }
  ]
}

Example - status empty

{
  "symbol": "RKLB",
  "status": "empty",
  "count": 0,
  "days": 30,
  "articles": [],
   "message": "No news available for RKLB in the last 30d."
}

get_stock_research pro AI

Full research bundle for a symbol in one call - replaces 4 separate calls: get_stock + get_stock_news + get_insider_activity + get_signals (filtered to one symbol), plus the AI-generated summary (verdict, narrative, key points, risks) bundled in as ai_summary. All data is pre-computed by the nightly AI pipeline; no live AI calls on request.

Parameters

Name	Type	Description
symbol	string	Ticker symbol

Response sections

Section	Key fields
stock	symbol, name, sector, price, change_pct, market_cap, pe_forward, pe_trailing, beta, dividend_yield, week52_high/low, analyst_rating, analyst_target, rsi, sma200_trend
ai_summary	verdict, ai_score (0-100) / ai_score_band (Weak/Moderate/Strong/Very Strong - the AI research composite, same scale/band convention as signal_score but a distinct field/pipeline), summary, key_points[] (3-5 specific positive/neutral observations), risks[] (2-3 specific risk factors), price_at_generation (stock price when the summary was generated), generated_at, headline (one-sentence plain-language take), near_term {stance, confidence} (view over <4 weeks, technicals/momentum-weighted), longer_term {stance, confidence} (view over a multi-month horizon, fundamentals/analyst/institutional-flow-weighted) - headline/near_term/longer_term are null on summaries generated before this schema shipped; fall back to verdict/ai_score until that symbol's next regeneration
news	Last 3 AI-flagged articles, one per event: title, published_at, ai_sentiment, ai_summary, signal_score (0-100)/signal_score_band, and collapsed_count (articles merged into it) when several reported the same event
sentiment	signal, signal_score (0-100) / signal_score_band (Weak/Moderate/Strong/Very Strong - no separate "insider_score" field, same name/formula as every other signal_score on this API), insider_trend (buying/selling/neutral, or null with no transactions in the window), institutional_pct, updated_at
signals	Up to the 5 most recent signals for this symbol in the last 90 days (array - a symbol can have more than one over that window): direction, signal_score (0-100 - always a single number, even for a NEUTRAL/two-sided idea, see get_signals' own signal_score row above), signal_score_band, source, rationale, expires, flagged_at. Recency-gated, not gated on whether Stocklake's own trading engine still holds the signal live. Empty array if none in that window.
directional_conflict	Only present when ai_summary.verdict and the most recent active signal's direction genuinely disagree (e.g. verdict=negative alongside an active POSITIVE signal) - these come from independent AI pipelines with different horizons and can legitimately point opposite ways. Fields: ai_summary_verdict, signal_direction, note. Absent (not null) when there's nothing to compare or the two agree.
forensic_scores	Same object as `get_stock`'s `forensic_scores` block - three classic forensic-accounting formulas: altman_z {score, zone: safe/grey/distress}, piotroski_f {score 0-9, strength: strong/moderate/weak}, beneish_m {score, likely_manipulator: bool}, each with its own note. score: null means genuinely not computable for this company (common for financial-sector names), not an error. Absent (no key at all) if this symbol has no forensic_scores doc yet.

Example (condensed)

{
  "stock": {
    "symbol": "ORCL", "name": "Oracle Corporation", "sector": "Technology",
    "price": 192.40, "change_pct": 1.4, "rsi": 68.9, "sma200_trend": "above",
    "analyst_rating": "buy", "analyst_target": 210.0
  },
  "ai_summary": {
    "verdict": "positive",
    "ai_score": 78, "ai_score_band": "Strong",
    "summary": "Strong cloud momentum, AI workload growth accelerating...",
    "key_points": ["Cloud ARR up 23% YoY", "AI training contracts with major hyperscalers"],
    "risks": ["Elevated valuation at 28x forward earnings"],
    "price_at_generation": 192.40, "generated_at": "2026-06-10T20:30:38+00:00",
    "headline": "Cloud momentum accelerating into next earnings",
    "near_term": { "stance": "POSITIVE", "confidence": 7 },
    "longer_term": { "stance": "POSITIVE", "confidence": 8 }
  },
  "news": [
    { "title": "Oracle beats Q3 earnings, cloud growth accelerates",
      "published_at": "2026-06-10T20:15:00+00:00", "ai_sentiment": "positive",
      "ai_summary": "Beat on EPS and revenue, cloud segment +31%..." }
  ],
  "sentiment": {
    "signal": "POSITIVE", "signal_score": 68, "signal_score_band": "Strong", "insider_trend": "neutral",
    "institutional_pct": 72.1, "updated_at": "2026-06-04T23:07:46+00:00"
  },
  "signals": [
    {
      "direction": "POSITIVE", "signal_score": 84, "signal_score_band": "Very Strong",
      "source": "screener", "rationale": "Strong AI cloud catalyst, momentum breakout...",
      "expires": "2026-06-12", "flagged_at": "2026-06-05T14:22:00+00:00"
    }
  ]
}

get_insider_activity free+ AI

Insider transactions for a stock, from regulatory insider filings for the US, Germany, the Netherlands and Spain. Where no regulatory filing is on record, market data fills the gap and the response says so. The filing facts are free: every tier gets buy/sell counts and the individual filings behind them. Pro adds the AI read of insider and institutional activity and the institutional holder data.

Free / guest: insider_buys, insider_sells, summary and the 5 most recent transactions over a fixed 90-day window. A larger days is capped at 90 and the response says so in days_note. No AI fields, no institutional holders.
Pro: days up to 365, up to 50 transactions, plus signal, signal_score, insider_signal/inst_signal, ai_commentary, top_holders, inst_ownership, total_holders and holder_count_divergence.

The counts and the rows come from the same merge and the same window, so they always agree, and the free counts match what Pro returns for the same window. Coverage outside the US is narrower than in the US, so an empty list for a non-US company often means no filing on record, not a broken lookup. Institutional holders are merged from two feeds and refreshed nightly.

Parameters

Parameter	Type	Required	Default	Description
symbol	string	✓	-	Ticker symbol (e.g. AAPL, TSLA)
days	integer		90	Insider-transaction window in days. Pro: 1-365. Free/guest: 1-90 (a larger value is capped at 90). Applies to `transactions`, `insider_buys` and `insider_sells`.

Response fields

Field	Type	Description
symbol	string	Ticker
insider_buys	int	Insider buy filings in the window (open-market purchases; grants, gifts and option exercises are excluded)
insider_sells	int	Insider sell filings in the window
transactions	array	The filings behind those counts, newest first: `date`, `name`, `role`, `type` (BUY/SELL), `shares`, `price`, `value`. Free/guest: up to 5. Pro: up to 50.
summary	string	One-line factual readout computed from the returned `transactions`/counts above: buy/sell counts, dollar totals, insider count and date range. Always agrees with the counts and rows next to it.
insider_buy_value	number	Total value of the buy filings in the window (listing currency)
insider_sell_value	number	Total value of the sell filings in the window (listing currency)
window_days	int	The window actually applied
source / source_name	string \| null	Which kind of feed was used: `regulatory_filing` or `market_data` (gap fill only). Null when nothing is on record.
updated_at	string	ISO 8601 UTC time the filings behind `transactions` were last fetched.
days_requested	int	Free/guest only. The `days` you asked for, before the 90-day cap.
days_note	string	Free/guest only, present when `days` was capped.
transactions_note	string	Free/guest only, present when there are more filings in the window than the 5 returned.
note	string	Present when no insider buys or sells are on record in the window.
pro_unlocks	string	Free/guest only. What Pro adds.
signal	string	pro Combined AI sentiment: STRONG_POSITIVE, POSITIVE, NEUTRAL, NEGATIVE, STRONG_NEGATIVE
signal_score	number \| null	pro 0-100, higher = stronger/more notable - the exact same field, formula, scale and bands as every other signal_score on this API.
signal_score_band	string \| null	pro Weak/Moderate/Strong/Very Strong. Null when signal_score is null.
insider_signal	string	pro Insider-only AI signal: POSITIVE, NEGATIVE, NEUTRAL, NONE
inst_signal	string	pro Institutional-only AI signal: POSITIVE, NEGATIVE, NEUTRAL, NONE
ai_commentary / ai_commentary_as_of	string \| null	pro A separately-generated AI narrative (names, amounts, direction) on its own refresh cadence, with the time it was written. It can lag the current filings - trust `summary` and `transactions` if they disagree.
top_holders	array	pro Up to 15 institutional holders: `name`, `shares`, `pct_held`, `sources`, `share_counts_by_source`
holder_count_divergence	object \| null	pro Non-null when the two holder feeds (`filings`, `market_data`) disagree on share counts by the same factor, which means holder share counts for this symbol may be unreliable
inst_ownership	number \| null	pro Institutional ownership percentage as a float (e.g. 74.55)
total_holders	int \| null	pro Total institutional holders

Example response

Example - free/guest, NVDA with days=365 (capped at 90)

{
  "symbol": "NVDA",
  "days_requested": 365,
  "insider_buys": 0,
  "insider_sells": 7,
  "transactions": [
    {
      "date": "2026-09-17T00:00:00+00:00",
      "name": "Kress Colette",
      "role": "EVP & Chief Financial Officer",
      "type": "SELL",
      "shares": 34918,
      "price": 219.0455,
      "value": 7648632.46
    },
    {
      "date": "2026-09-04T00:00:00+00:00",
      "name": "STEVENS MARK A",
      "role": "Director",
      "type": "SELL",
      "shares": 622239,
      "price": 231.6199,
      "value": 144122944.06
    },
    {
      "date": "2026-09-03T00:00:00+00:00",
      "name": "STEVENS MARK A",
      "role": "Director",
      "type": "SELL",
      "shares": 400000,
      "price": 228.7848,
      "value": 91513923.35
    },
    {
      "date": "2026-09-02T00:00:00+00:00",
      "name": "STEVENS MARK A",
      "role": "Director",
      "type": "SELL",
      "shares": 1200000,
      "price": 223.3346,
      "value": 268001520.0
    },
    {
      "date": "2026-09-01T00:00:00+00:00",
      "name": "STEVENS MARK A",
      "role": "Director",
      "type": "SELL",
      "shares": 63501,
      "price": 220.0589,
      "value": 13973960.21
    }
  ],
  "window_days": 90,
  "source": "regulatory_filing",
  "source_name": "Regulatory insider filings",
  "transactions_note": "Showing the 5 most recent of 7 filings in the last 90 days.",
  "days_note": "days=365 capped at 90 on the free tier; Pro allows up to 365.",
  "pro_unlocks": "Pro adds the AI read (signal, signal_score, insider_signal/inst_signal and a written summary), a window of up to 365 days with up to 50 filings, and institutional holders (top_holders, inst_ownership, total_holders, holder_count_divergence)."
}

Example - Pro (transactions, window_days, source, top_holders and holder_count_divergence omitted here for brevity)

{
  "symbol": "BG",
  "signal": "POSITIVE",
  "signal_score": 68,
  "signal_score_band": "Strong",
  "insider_signal": "NEGATIVE",
  "inst_signal": "POSITIVE",
  "summary": "0 buys ($0) and 1 sell ($337K) by 1 insider, on 2026-08-14.",
  "ai_commentary": "COO Garros Julio sold $337K - lone negative insider signal. Institutions strongly positive: 377 holders increased (+28.6M sh) vs 283 decreased. 128 new holders added 20.9M sh.",
  "insider_buys": 0,
  "insider_sells": 1,
  "inst_ownership": 99.81,
  "total_holders": 758,
  "updated_at": "2026-05-11T22:16:29.930700+00:00"
}

Example - CRM (STRONG_POSITIVE, high insider buying)

{
  "symbol": "CRM",
  "signal": "STRONG_POSITIVE",
  "signal_score": 91,
  "signal_score_band": "Very Strong",
  "insider_signal": "POSITIVE",
  "inst_signal": "POSITIVE",
  "summary": "4 buys ($16.6M) and 0 sells ($0) by 4 insiders, 2026-07-02 to 2026-08-11.",
  "ai_commentary": "CEO Benioff bought $12.4M worth of shares - largest insider buy in 3 years. Three additional C-suite insiders added $4.2M combined. Institutions increased holdings by 3.2% this quarter with 42 new holders opening positions. Strong alignment between insider and institutional conviction.",
  "insider_buys": 4,
  "insider_sells": 0,
  "inst_ownership": 82.15,
  "total_holders": 2410,
  "updated_at": "2026-05-28T06:15:00+00:00"
}

get_signals pro AI

Live AI signal queue - stocks actively flagged by the Stocklake pipeline as worth attention. Sourced from sector screening, news analysis, and sentiment signals. Signals expire daily; this always reflects the pipeline's current view.

Pipeline dependency. Signals are refreshed by scheduled AI jobs. If the pipeline hasn't run recently, results may be sparse. Check flagged_at on each signal to assess freshness.

Parameters

Name	Type	Default	Description
direction	string	-	POSITIVE · NEGATIVE · NEUTRAL - filter by trade direction. NEUTRAL covers both a flat/undecided read and a genuinely two-sided idea (real opposing bull/bear theses - see signal_score below). Omit for all.
min_signal_score	integer	60	Minimum composite signal score (0-100) - blends conviction/confidence/flag_score, source track record, and real technical factors. This is the field to filter on.
source	string	-	Filter by signal source: news · screener · sentiment
limit	integer	25	Max signals to return (max 50 - pass a higher value explicitly for the broader feed). Results sorted by recency. Each returned signal counts as one call toward your daily limit.

Response fields

Field	Type	Description
count	integer	Number of signals returned
window	string	"24h" if fresh activity was found, otherwise a note that the response falls back to the most recent signals regardless of age
signals[].symbol	string	Ticker
signals[].direction	string	POSITIVE · NEGATIVE · NEUTRAL
signals[].signal_score	number	Composite AI score 0-100 - the current, single source of truth for signal quality. Always a single number, including for a NEUTRAL signal (a genuinely two-sided idea, real opposing bull/bear theses) - in that case this is the STRONGER of the two sides, since that's the more actionable fact; the two-sided detail is in rationale.
signals[].signal_score_band	string \| null	Human-readable label: Weak · Moderate · Strong · Very Strong. Null only when signal_score itself is null.
signals[].source	string	Primary pipeline source that flagged this stock
signals[].sources	array	All sources that contributed (when merged across sources)
signals[].rationale	string	AI rationale - why the pipeline flagged this stock
signals[].expires	string	Date after which this signal is considered stale (YYYY-MM-DD)
signals[].flagged_at	string	ISO 8601 UTC timestamp when this signal was last flagged by the pipeline

Example

{
  "count": 2,
  "window": "24h",
  "signals": [
    {
      "symbol": "MGM", "direction": "POSITIVE",
      "signal_score": 88, "signal_score_band": "Very Strong",
      "source": "news", "sources": ["news"],
      "rationale": "flag=10/10 | positive | impact=95/100 | MGM Resorts acquisition by Apollo rumored at 25% premium",
      "expires": "2026-06-06", "flagged_at": "2026-06-05T20:48:00Z"
    },
    {
      "symbol": "CMA", "direction": "NEUTRAL",
      "signal_score": 62, "signal_score_band": "Strong",
      "source": "news", "sources": ["news"],
      "rationale": "flag=9/10 | mixed | impact=85/100 | Comerica net interest income guidance raised on rate optimism - a real bull case (37/100) and bear case (62/100) at once",
      "expires": "2026-06-06", "flagged_at": "2026-06-05T19:57:00Z"
    }
  ]
}

CMA above is a NEUTRAL signal - the pipeline sees a genuine bull case (37/100) and bear case (62/100) at once, no directional consensus. signal_score reports the STRONGER side (62), so a high score alongside NEUTRAL means real conviction with a contested direction, not "nothing going on" - the two-sided detail is in rationale.

get_news_feed pro AI

Market-wide AI-flagged news briefing - top articles across all tracked stocks ranked by signal strength. Unlike get_stock_news (per-symbol), this scans the entire universe and surfaces the most notable news regardless of ticker. No URLs or source domains exposed.

Parameters

Name	Type	Default	Description
min_signal_score	integer	60	Minimum `signal_score` (0-100) used to select articles server-side. Replaces the old `min_flag_score` (0-10, gated on the legacy `ai_flag_score` field) - 2026-08-24, signal_score consistency initiative.
days	integer	3	Look-back window in days (max 10)
limit	integer	10	Max articles returned (max 25)

Each article also carries signal_score (0-100, always a single number) and signal_score_band ("Weak"/"Moderate"/"Strong"/"Very Strong"). Prefers this symbol's LIVE news-sourced signal score if one was raised in the last 90 days - same value get_signals/get_stock_news report for that symbol, kept in sync as it's re-scored, and not gated on whether Stocklake's own trading engine still considers the signal live (a dropped/expired signal still shows here); this is a per-symbol fact, not a per-article judgment, so two articles about the same stock always show the same value. Otherwise a per-article magnitude computed from that article's own AI classification, so every article still gets a real, rankable number. There is 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.

One article per event: when several articles report the same event, the highest-ranked one is kept and carries collapsed_count, the number of articles merged into it. limit counts distinct events. Articles without a usable summary are left out.

Example

{
  "count": 10, "days": 3, "min_signal_score": 60,
  "articles": [
    { "symbol": "NVDA", "title": "Nvidia unveils GB300 chip, accelerating AI data center roadmap",
      "published_at": "2026-06-04T14:30:00+00:00",
      "ai_sentiment": "positive",
      "ai_summary": "New GB300 architecture delivers 2× throughput over H100. Roadmap acceleration strengthens moat vs AMD...",
      "signal_score": 78, "signal_score_band": "Strong" }
  ]
}

get_market_assessment pro AI

Combined 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 before treating this as current. Returns two complementary perspectives:

Regime (regime_* fields) - answers "how much equity risk to take" → use for position sizing and asset allocation
Outlook (outlook_* fields) - answers "which direction and sectors to trade" → use for sector preference and directional bias

Note: market_context is a point-in-time snapshot from when the AI ran - not live. Use get_market_pulse for live prices.

Parameters

Name	Type	Default	Description
history_count	integer	0	Include last N prior assessments for each perspective (0-3). Returns `regime_history[]` and `outlook_history[]`.

Response - Regime fields

Field	Type	Description
regime	string	RISK_OFF / CAUTIOUS / NEUTRAL / AGGRESSIVE
risk_appetite_score	number	0-100. Plain re-expression of `regime` as a score (RISK_OFF ≈ 10 → AGGRESSIVE ≈ 90). Higher = the tape currently supports more risk-taking.
macro_score	number \| null	0-100. The REAL, continuous number `regime` buckets into 4 categories - a blend of arithmetic inputs (VIX level, breadth oversold/overbought skew, SKEW-vs-VIX divergence, TD-exhaustion ratio) and the AI's own `regime_strength` read. Distinct from `risk_appetite_score`, which is just a coarse 4-value lookup on `regime` alone - `macro_score` is the finer-grained real number. Null on an assessment from before this field existed (2026-08-26).
regime_strength	number \| null	1-10. The AI's own read of regime conviction - one of the two inputs blended into `macro_score` above.
macro_score_trend	object	`{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 say whether the environment is getting worse or just stabilized after a worse reading - this does. Either leg is `null` without enough history yet.
regime_bias	string	"Long Setups Only" / "Short Setups Only" / "Both Directions" - whether current market conditions favor one trade direction over the other
regime_bias_note	string	Plain-language sentence explaining what `regime_bias` means, framed as a market-conditions read
regime_confidence	number	1-10. Clarity of the regime call.
regime_rationale	string	Core thesis in plain language
key_risks	string[]	2-3 tail risks that could invalidate the call
watch_for	string[]	Triggers that would cause a regime change
vix_at_assessment	number	VIX level when assessment was made
regime_updated_at	string	ISO 8601 UTC timestamp of last assessment
indicators.macro_data	object	Macro data: yield_spread_10y2y, fed_funds_rate, cpi_index (BLS index level ~332, not YoY %), unemployment, breakeven_10y, usd_index, m2 - each with value, date, delta_3m
indicators.volatility_term_structure	object	VIX / VIX3M / VIX6M last 5 closes + contango/backwardation signal
indicators.market_sentiment	object	Fear & Greed value (0-100) and label
indicators.breadth	object	Live market-wide RSI breadth (universe_size, oversold/overbought/neutral counts + percentages) - same live numbers as get_market_pulse's `breadth`, bundled here too so a regime read doesn't need a second call.
market_context	object	Point-in-time snapshot: price/RSI/SMA200/perf for SPY, QQQ, IWM, TLT, GLD, VIX, TNX, HYG, sector ETFs. Recorded when AI ran - not live.

Response - Outlook fields

Field	Type	Description
outlook	string	POSITIVE / NEUTRAL / NEGATIVE
outlook_conviction	number	1-10. Strength of the directional call.
equity_view	string	Plain language directional narrative
preferred_sectors	string[]	Sectors to overweight
avoided_sectors	string[]	Sectors to underweight
catalyst	string	Primary catalyst driving the outlook
outlook_key_risk	string	Key risk to the outlook thesis
outlook_rationale	string	Detailed reasoning
outlook_updated_at	string	ISO 8601 UTC timestamp of last assessment
regime_history[]	object[]	Prior regime states (when history_count > 0): regime, risk_appetite_score, macro_score, regime_bias, regime_confidence, vix_at_assessment, updated_at
outlook_history[]	object[]	Prior outlook states (when history_count > 0): outlook, conviction, at

Example (condensed)

{
  "regime": "CAUTIOUS", "risk_appetite_score": 35, "macro_score": 33, "regime_strength": 4,
  "macro_score_trend": { "change_7d": -11, "change_30d": -22, "direction": "deteriorating" },
  "regime_bias": "Both Directions", "regime_confidence": 6,
  "regime_rationale": "Equity uptrend intact. HYG diverging - credit not confirming SPY highs.",
  "key_risks": ["HYG breaking below $79.50", "VIX closing above 20"],
  "watch_for": ["HYG reclaiming $80.50 → upgrade to NEUTRAL"],
  "vix_at_assessment": 16.94, "regime_updated_at": "2026-05-06T09:14:56+00:00",
  "indicators": {
    "macro_data": { "yield_spread_10y2y": { "value": 0.21, "delta_3m": 0.15 } },
    "market_sentiment": { "value": 54.0, "description": "Neutral" }
  },
  "market_context": { /* NOT live - snapshot from regime_updated_at */
    "spy": { "price": 574.12, "rsi": 70.3, "above_200sma": true }
  },
  "outlook": "POSITIVE", "outlook_conviction": 7,
  "equity_view": "Momentum intact. Tech leading. Small-caps lagging but not breaking down.",
  "preferred_sectors": ["Technology", "Industrials"],
  "avoided_sectors": ["Utilities", "Real Estate"],
  "catalyst": "AI spending cycle intact. Macro resilience.",
  "outlook_updated_at": "2026-05-06T09:14:56+00:00"
}

get_sector_intelligence pro AI

AI-assessed sector intelligence with signals (LEADING/STRONG/NEUTRAL/WEAK/LAGGING), drivers, alerts, and computed statistics. Pass a sector for deep single-sector analysis, or omit for all 11 sectors at once - the all-sectors call doubles as the rotation view (sort_by_strength + history_count). 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.

Parameters

Parameter	Type	Required	Default	Description
sector	string	-	None	Sector name (e.g. Technology, Healthcare). Omit to list all sectors.
sort_by_strength	boolean	-	false	All-sectors call only: sort LEADING→LAGGING instead of alphabetical - for finding leading vs lagging sectors
history_count	integer	-	0	All-sectors call only: include last N prior signal states per sector (0-3)

Response fields

Field	Type	Description
sector	string	Sector name
signal	string	LEADING / STRONG / NEUTRAL / WEAK / LAGGING
cycle_stage	string	Sector cycle phase (e.g. MARKUP, MARKDOWN, ACCUMULATION, DISTRIBUTION)
rotation_signal	string	Money-flow read (e.g. ACCUMULATE, DISTRIBUTE, HOLD)
sector_score	number \| null	0-100. The REAL, continuous number `signal` buckets into 5 categories (LEADING/STRONG/NEUTRAL/WEAK/LAGGING) - a blend of arithmetic inputs (RSI/perf percentiles, top-5 concentration, SMA200 breadth) and the AI's own `strength_score` read. Comparable across all 11 sectors on one absolute scale. Null on an assessment from before this field existed (2026-08-26).
strength_score	number \| null	1-10. The AI's own read of sector strength - one of the two inputs blended into `sector_score` above.
sector_score_trend	object	Single-sector call only. `{change_7d, change_30d, direction}` - whether `sector_score` is improving/deteriorating/stable over the trailing 7/30 days, computed automatically. 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 moving in opposite directions; this tells them apart. Either leg is `null` without enough history yet.
confidence	number	AI confidence 1-10
drivers	string	AI narrative of sector drivers
alert	string	Notable condition if applicable (breadth divergence, extreme RSI, etc.)
stats.avg_rsi	number	Sector-average RSI
stats.sma200_breadth_pct	number	% of stocks above their 200-day MA
stats.oversold_pct / overbought_pct	number	RSI distribution extremes
stats.avg_perf_1w_pct / avg_perf_1m_pct	number	Average sector performance 1W / 1M
updated_at	string	ISO 8601 when the assessment was made
history[]	array	Present when history_count > 0 (all-sectors call) - prior {signal, confidence, sector_score, at}
sectors[] / count	array / integer	Present when sector param is omitted - all sectors assessed

Example - single sector

{
  "sector": "Technology", "signal": "STRONG", "sector_score": 68, "strength_score": 7,
  "sector_score_trend": { "change_7d": -28, "change_30d": -10, "direction": "deteriorating" },
  "confidence": 7,
  "drivers": "AI capex cycle, earnings momentum. Mega-caps leading with broad participation.",
  "alert": "19.5% overbought, breadth only 53% - narrow leadership suggests froth in pockets",
  "stats": { "avg_rsi": 56.5, "sma200_breadth_pct": 53.1,
    "oversold_pct": 4.1, "overbought_pct": 19.5,
    "avg_perf_1w_pct": 1.1, "avg_perf_1m_pct": 11.0 },
  "updated_at": "2026-05-12T10:19:48+00:00"
}

Example - all sectors, sort_by_strength=true (rotation view)

{
  "count": 11,
  "sectors": [
    { "sector": "Technology", "signal": "STRONG", "sector_score": 68, "strength_score": 7, "confidence": 7,
      "stats": { "avg_rsi": 56.5, "sma200_breadth_pct": 53.1, "avg_perf_1w_pct": 1.1 },
      "alert": "19.5% overbought - narrow leadership",
      "updated_at": "2026-05-12T10:19:48+00:00" },
    { "sector": "Energy", "signal": "WEAK", "sector_score": 31, "strength_score": 3, "confidence": 6,
      "stats": { "avg_rsi": 42.3, "sma200_breadth_pct": 35.8, "avg_perf_1w_pct": -2.1 }, "alert": null,
      "updated_at": "2026-05-12T10:19:48+00:00" }
  ]
}

get_earnings_intelligence pro AI

Upcoming earnings with AI context per stock - combines the earnings calendar with AI pipeline data to surface which events are worth monitoring. Sorted by earnings date ascending (soonest first).

Parameters

Name	Type	Default	Description
days_ahead	integer	14	Look-ahead window in days (max 30)
sector	string	-	Filter to one sector (optional)
min_ai_score	integer	-	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 `ai_score` field returned below. Applied before limit truncates the result.
limit	integer	25	Max results to return (max 25). Each returned stock counts as one call toward your daily limit.

Response fields (per result)

Field	Type	Description
symbol, name, sector	string	Stock identity
earnings_date	string	ISO UTC timestamp of expected earnings release
is_estimate	boolean	Whether the date is estimated
price, rsi, market_cap	number	Current technicals
eps_trailing, eps_forward	number	Earnings expectations context
ai_verdict	string	positive / neutral / negative (from nightly AI pipeline)
ai_score	number \| null	0-100 AI research composite score, same scale/band convention as get_signals' signal_score but a distinct field/pipeline. Null if no ai_summary doc exists yet.
ai_score_band	string \| null	Weak / Moderate / Strong / Very Strong, or null
ai_risks	string[]	Top 2 AI-identified risk factors
analyst_rating, analyst_target	string / number	Wall Street consensus

Example

{
  "count": 22, "days_ahead": 14,
  "results": [
    { "symbol": "ORCL", "name": "Oracle Corporation", "sector": "Technology",
      "earnings_date": "2026-06-10T20:00:00+00:00", "is_estimate": false,
      "price": 192.40, "rsi": 68.9, "eps_forward": 7.20,
      "ai_verdict": "positive",
      "ai_score": 81, "ai_score_band": "Very Strong",
      "ai_risks": ["Elevated valuation at 28x forward earnings", "Cloud margin pressure from AI infra spend"],
      "analyst_rating": "buy", "analyst_target": 210.0 }
  ]
}

get_watchlist pro AI

The caller's Stocklake watchlist - the symbols starred on the web dashboard at /dashboard - enriched with live price, technicals, and AI verdict. No parameters; resolves your account automatically from your API key or OAuth session.

Parameters

None.

Response fields

Field	Type	Description
count	integer	Number of symbols on the watchlist
items[].symbol, name, sector	string	Stock identity
items[].price, change_pct, rsi, market_cap	number	Live snapshot
items[].analyst_rating	string \| null	strong_buy / buy / hold / sell / strong_sell
items[].atr_pct	number	Average True Range as % of price (volatility). Omitted if the underlying indicator reading is missing or corrupted.
items[].ai_verdict	string	positive / neutral / negative (from nightly AI pipeline)
items[].ai_headline	string	One-line "why" behind the verdict
items[].ai_score	number \| null	0-100 AI research composite score - same 0-100 scale/band convention as get_signals' signal_score but a distinct field/pipeline. Null if no ai_summary doc exists yet.
items[].ai_score_band	string \| null	Weak / Moderate / Strong / Very Strong, or null
items[].added_at	string	ISO UTC timestamp - when the symbol was starred
items[].price_at_add	number	Price at the moment it was starred, for a "since added" delta

Read-only - starring/unstarring a symbol is web-only for now (no add_to_watchlist/remove_from_watchlist tool yet). Returns count: 0, items: [] if nothing is starred.

Example

{
  "count": 2,
  "items": [
    { "symbol": "AAPL", "name": "Apple Inc.", "sector": "Technology",
      "price": 231.02, "change_pct": 1.14, "rsi": 58.3, "market_cap": 3480000000000, "analyst_rating": "buy", "atr_pct": 2.41,
      "ai_verdict": "positive",
      "ai_headline": "Services revenue growth reaccelerating",
      "ai_score": 64, "ai_score_band": "Strong",
      "added_at": "2026-07-20T09:14:02+00:00", "price_at_add": 224.87 }
  ]
}