End-to-end agent
workflows.
Real examples of AI agents using TickerAPI to scan markets, pull context, and make decisions. Each workflow shows the prompt, the API calls, and the reasoning.
Scan → Events Lookback → Decision
Agent scans for oversold stocks, picks an interesting result, pulls its event history, and makes a judgment call.
Find deeply oversold stocks and check if any of them have a history of bouncing back. Skip value traps.
Agent scans for deep_oversold stocks with at least small-cap market cap.
{ "ticker": "SVC", "rsi_zone": "deep_oversold", "days_in_oversold": 2, "condition_rarity": "extremely_rare", "condition_percentile": 1, "volume_context": "spike", "trend_context": "strong_downtrend", "accumulation_state": "strong_distribution", "sector": "Real Estate", "valuation_zone": "fair_value" }
Agent checks how many times SVC has been deep_oversold before and what happened after.
{ "ticker": "SVC", "field": "rsi_zone", "total_occurrences": 1, "query_range": "5y", "events": [ { "date": "2026-03-31", "band": "deep_oversold", "prev_band": "neutral_low", "aftermath": { // no aftermath yet } } ] }
SVC entered deep_oversold for the first time in 5 years. The condition_percentile of 1 means this is the most extreme oversold reading in the asset's history. But there's no recovery precedent because it has literally never been here before.
Combined with strong_distribution (institutions selling) and a volume spike confirming the selloff, there's no evidence to support a bounce thesis. This is uncharted territory for SVC with active selling pressure.
Verdict: skip. No historical bounce data to work with. Strong distribution and volume confirmation suggest this sell is being driven by institutional exits, not retail panic. Watch for accumulation_state to shift before reconsidering.
Watchlist Changes → Alert Loop
Agent monitors a portfolio via watchlist. When state changes fire, it pulls context and sends a structured alert.
Monitor my watchlist. When anything important changes, pull the full summary and tell me what's going on.
Agent checks for day-over-day state changes across all 15 watchlist tickers.
{ "tickers_checked": 15, "tickers_changed": 6, "changes": { "AMD": [ { "field": "valuation_zone", "from": "fair_value", "to": "overvalued" } ], "AMZN": [ { "field": "valuation_zone", "from": "undervalued", "to": "fair_value" } ], "INTC": [ { "field": "trend_direction", "from": "neutral", "to": "uptrend" } ], "RIVN": [ { "field": "trend_direction", "from": "neutral", "to": "strong_downtrend" } ], "ETHUSD": [ { "field": "trend_direction", "from": "strong_downtrend", "to": "neutral" } ] } }
Agent pulls the full summary to understand what's driving the trend change.
{ "ticker": "RIVN", "trend": { "direction": "strong_downtrend", "duration_days": 1 }, "momentum": { "macd_state": "expanding_negative" }, "volatility": { "regime": "high", "squeeze_active": true }, "volume": { "accumulation_state": "strong_distribution" }, "support_level": { "distance_band": "near", "status": "intact" }, "growth_zone": "slowing", "insider_activity": { "zone": "moderate_buying" } }
RIVN entered strong_downtrend as of today. MACD is expanding negative with high volatility and a Bollinger squeeze active for 13 days. Volume shows strong distribution (institutional selling).
However: support is near and intact, and insiders have been moderate buyers this quarter. The squeeze could resolve in either direction.
Action: watch the support level. If the squeeze resolves downward through support, the strong_distribution suggests further downside. If support holds with a squeeze break upward, the insider buying becomes relevant. No action until the squeeze resolves.
Compare → Relative Value Decision
Agent compares two competitors side-by-side and evaluates which one has better positioning across trend, momentum, valuation, and growth.
Compare AMD and INTC. Which one is better positioned right now?
One call returns individual summaries plus a side-by-side comparison with divergence analysis.
{ "performances": { "AMD": "moderate_gain", "INTC": "sharp_gain" }, "trend_directions": { "AMD": "uptrend", "INTC": "uptrend" }, "rsi_zones": { "AMD": "neutral", "INTC": "neutral" }, "valuation_zones": { "AMD": "overvalued", "INTC": "fair_value" }, "growth_zones": { "AMD": "high_growth", "INTC": "shrinking" }, "range_positions": { "AMD": "upper_third", "INTC": "mid_range" } }
Both are in uptrends with neutral RSI, but the fundamental picture diverges sharply.
AMD has high_growth and strong execution but just entered overvalued territory. It's in the upper_third of its range with a squeeze active for 20 days. Insiders are net sellers. The growth justifies a premium, but the valuation is stretched.
INTC has fair_value pricing but shrinking revenue and deteriorating EPS. It posted a sharp_gain today and is sitting at mid_range with more room to run technically. Its condition_percentile of 3 means the current neutral state is very rare, historically resolving quickly.
Verdict: INTC has better near-term risk/reward on a technical basis (fair_value, mid_range, rare condition). AMD has better fundamentals long-term (high_growth) but is priced for it. For a swing trade, INTC. For a hold, AMD, but wait for a pullback from overvalued.
Volatility Lookback → Risk Assessment
Agent checks the current volatility regime, pulls historical extreme volatility events, and assesses whether the current environment historically led to gains or losses.
RIVN volatility seems high. Should I be worried? What usually happens after periods like this?
Agent pulls all historical instances where RIVN entered extreme volatility and checks what happened afterward.
{ "total_occurrences": 20, "events": [ { "date": "2026-03-25", "duration_days": 6, "aftermath": { "5d": "slight_decline" } }, { "date": "2026-03-20", "duration_days": 4, "aftermath": { "5d": "flat" } }, { "date": "2026-03-12", "duration_days": 4, "aftermath": { "5d": "slight_gain", "10d": "flat" } }, { "date": "2026-02-13", "duration_days": 13, "aftermath": { "5d": "moderate_decline", "10d": "moderate_decline" } }, { "date": "2026-01-14", "duration_days": 7, "aftermath": { "5d": "slight_decline", "10d": "moderate_decline" } } ] }
RIVN has entered extreme volatility 20 times in 5 years. The recent cluster is notable: 3 times in the last 2 weeks alone, suggesting persistent instability rather than a one-off spike.
The aftermath pattern is consistently negative. Of the 5 most recent events, 3 resulted in declines at the 5-day mark, 1 was flat, and only 1 showed a slight gain. At the 10-day mark, the picture gets worse: moderate declines dominate.
The longest recent episode (13 days in February) led to moderate declines at both 5d and 10d, suggesting that extended extreme volatility for RIVN specifically tends to resolve to the downside.
Assessment: elevated risk. RIVN's extreme volatility events historically lead to flat or negative returns across all measured timeframes. The current clustering of events suggests this isn't noise. Reduce position size or wait for volatility_regime to drop back to above_normal before adding exposure.
The pattern is the same every time.
Scan or monitor. Pull context. Reason. Decide. Every workflow above follows this loop, and every response is compact enough that your agent can do it without burning its context window.
Pre-computed, not raw
Every response is categorical. Your agent reads "deep_oversold" and "strong_distribution," not a wall of numbers to interpret.
1-2 calls per workflow
No chaining 10 endpoints together. Scan, summarize, compare, and check history all return complete context in a single response.
Token-efficient
Full agent workflows in a few hundred tokens. No OHLCV dumps, no indicator math, no prompt engineering to explain what RSI means.