The most important tool — ask any question in natural language and get verified intelligence.

WHEN TO USE: This should be your DEFAULT tool for any financial, market, or economic question. It automatically detects 41 intents (price, technicals, earnings, sentiment, screener, backtest, competitors, insider, filings, analysts, congress, crypto, forex, economy, and more) and routes to the right data sources. Use this FIRST before reaching for specialized tools.

RETURNS: Structured data from all matched endpoints + LLM-generated natural language summary + composite trade signal (0-100) + confidence level (high/medium/low) + follow-up suggestions.

COST: 1-5 credits depending on endpoints hit. Responses cached 60s for ticker queries, 30s for general. Use fast=true to skip LLM summary and save ~2 seconds.

EXAMPLES: "What's happening with NVDA?" → full cross-reference (price, technicals, earnings, sentiment, news, insider, analysts) "Compare AAPL vs MSFT" → side-by-side comparison with correlation "Oversold semiconductor stocks" → NLP screener with results "How is the market doing?" → indices, movers, yields "Bitcoin price and DeFi overview" → crypto data "Verify: Tesla beat Q4 earnings" → fact-check with evidence chain

CONSTRAINTS: 1,061+ tickers with auto-discovery. Falls back to web search for non-financial queries.

Fact-check any claim with full evidence chain, confidence breakdown, and source reliability scores.

WHEN TO USE: After any agent (including yourself) makes a factual claim about earnings, revenue, market movements, mergers, acquisitions, or any financial data. Also use proactively to verify assumptions before making recommendations. This is the TRUST tool — it proves claims with evidence.

RETURNS: • verdict: supported | contradicted | partially_supported | unverifiable • confidence: 0-1 with 4-factor breakdown (source_agreement, source_quality, recency, corroboration_depth) • evidence_chain: array of {source, snippet, url, position, reliability} — actual quotes from real sources • receipt: hashable verification proof (id, claim_hash, verdict_hash, sources_hash) • Checks 200+ verified sources first, falls back to live web search — NOTHING returns "unverifiable" for newsworthy claims

COST: 3 credits. Results cached 1 hour (corpus) or 15 min (web fallback).

EXAMPLES: "NVIDIA reported record Q4 2025 earnings" → SUPPORTED (85%) with Reuters, Bloomberg evidence "The Federal Reserve cut rates in March 2026" → CONTRADICTED (92%) — they held rates steady "Apple is partnering with OpenAI" → SUPPORTED with 5 source evidence chain

CONSTRAINTS: Claim must be 10-1000 characters. Be specific — include names, numbers, dates for best results.

Search verified intelligence briefs by keyword or topic.

WHEN TO USE: When looking for specific news, events, or coverage on a topic. Use veroq_ask for natural-language questions instead. RETURNS: Array of briefs with headline, confidence score, category, summary, and brief ID. COST: 1 credit. EXAMPLE: { "query": "NVIDIA earnings", "category": "Technology", "limit": 5 }

Get the latest verified intelligence briefs in reverse-chronological order.

WHEN TO USE: For browsing recent news without a specific search query. Use veroq_search when you have a topic in mind. RETURNS: Array of briefs with headline, confidence score, category, and summary. COST: 1 credit. EXAMPLE: { "category": "Markets", "limit": 10 }

Get full details for a specific intelligence brief by its ID.

WHEN TO USE: After finding a brief via search/feed, use this to read the full body, sources, entities, and counter-argument. RETURNS: Full brief with body text, sources (with trust levels), entities, counter-argument, and provenance (confidence, bias, AI/human split). COST: 1 credit. EXAMPLE: { "brief_id": "PR-2026-0305-001" }

Extract article content from one or more URLs into clean text.

WHEN TO USE: When you need the full text of a news article or web page for analysis. Handles paywalls where possible. RETURNS: Per-URL results with title, domain, word count, and extracted text (truncated at 2000 chars). COST: 3 credits. EXAMPLE: { "urls": "https://reuters.com/article/123,https://bloomberg.com/news/456" } CONSTRAINTS: Max 5 URLs per request.

Get all intelligence briefs mentioning a specific entity (person, company, location, etc.).

WHEN TO USE: When tracking coverage of a specific person, organization, or place across all briefs. RETURNS: Array of briefs mentioning the entity, with headline, confidence, category, and summary. COST: 1 credit. EXAMPLE: { "name": "Elon Musk" }

Get trending entities — people, orgs, and topics with the most mentions in the last 24 hours.

WHEN TO USE: To discover what's dominating the news cycle right now. Good starting point for research. RETURNS: Array of entities with name, type, ticker (if applicable), and 24h mention count. COST: 1 credit. EXAMPLE: { "limit": 10 }

Compare how different news sources cover the same topic, with per-source bias analysis and synthesis.

WHEN TO USE: When you need to understand media bias or see how coverage of an event differs across outlets. RETURNS: Topic headline, VEROQ confidence/bias scores, per-source analysis, and overall synthesis. COST: 2 credits. EXAMPLE: { "topic": "Federal Reserve rate decision" }

Run deep multi-source research on a topic. Produces a structured report with key findings, entity map, and information gaps.

WHEN TO USE: For thorough investigation of a topic requiring analysis across many sources. Use veroq_search for quick lookups instead. RETURNS: Summary, key findings, analysis, confidence assessment, entity map (with co-occurrences), information gaps, and sources used. COST: 3 credits. EXAMPLE: { "query": "impact of AI regulation on semiconductor stocks", "max_sources": 20 }

Get the story evolution timeline for a living brief — versioned updates, confidence changes, and new sources over time.

WHEN TO USE: To see how a story developed over time. Requires a brief ID from search/feed. RETURNS: Array of timeline entries with version number, timestamp, summary, confidence score, changes, and new sources. COST: 2 credits. EXAMPLE: { "brief_id": "PR-2026-0305-001" }

Generate a forward-looking forecast for a topic based on intelligence trends, momentum, and historical patterns.

WHEN TO USE: When you need predictive analysis — likely outcomes, scenarios, and risk factors for a topic. RETURNS: Outlook, confidence, time horizon, key drivers, risks, probability-weighted scenarios, and supporting briefs. COST: 2 credits. EXAMPLE: { "topic": "US inflation trajectory", "depth": "deep" }

Find contradictions across intelligence briefs — stories where sources disagree on facts, framing, or conclusions.

WHEN TO USE: To identify conflicting narratives and disputed claims in the news. Useful for risk assessment and due diligence. RETURNS: Array of contradictions with severity, topic, summary, and opposing brief positions (Side A vs Side B). COST: 2 credits. EXAMPLE: { "severity": "high" }

Get notable events detected across intelligence briefs — significant developments, announcements, and inflection points.

WHEN TO USE: To discover major events like product launches, policy changes, or market-moving announcements. Filter by type or subject. RETURNS: Array of events with type, subject, headline, summary, impact score, detected timestamp, and related brief IDs. COST: 2 credits. EXAMPLE: { "type": "earnings", "subject": "NVDA" }

Get a diff of changes to a living brief since a given time — additions, removals, and modifications between versions.

WHEN TO USE: To see exactly what changed in a brief since a specific timestamp. Requires a brief ID. RETURNS: Version range, confidence change, field-level changes (old/new values), and newly added sources. COST: 2 credits. EXAMPLE: { "brief_id": "PR-2026-0305-001", "since": "2026-03-18T00:00:00Z" }

Search the live web with optional VEROQ trust scoring on results.

WHEN TO USE: When intelligence briefs don't cover a topic and you need live web results. Enable verify=true for trust scoring. RETURNS: Web search results with titles, URLs, snippets, relevance scores, and optional verification scores. COST: 3 credits. EXAMPLE: { "query": "TSLA cybertruck delivery numbers 2026", "freshness": "week", "verify": true }

Crawl a URL and extract structured content with optional link following.

WHEN TO USE: When you need to extract and analyze content from a specific webpage, or crawl a site's link structure. RETURNS: Page content, metadata, and discovered links per page crawled. COST: 3 credits. EXAMPLE: { "url": "https://sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=AAPL", "depth": 1 } CONSTRAINTS: Max depth 3, max 10 pages per crawl.

Get the live market price for a stock or crypto ticker.

WHEN TO USE: For a quick price check on any ticker. This is free — use it freely. For full analysis, use veroq_full instead. RETURNS: Current price, change, change percent, volume, currency, and market state (open/closed). COST: Free (0 credits). EXAMPLE: { "symbol": "AAPL" }

Get a composite trading signal score for a ticker based on sentiment, momentum, coverage volume, and event proximity.

WHEN TO USE: For a quick bull/bear signal on a ticker. Use veroq_ticker_analysis for deeper context behind the signal. RETURNS: Composite score, signal (strong_bullish to strong_bearish), and component breakdown (sentiment, momentum, volume, events with weights). COST: 2 credits. EXAMPLE: { "symbol": "NVDA" }

Get intelligence briefs ranked by relevance to your portfolio holdings.

WHEN TO USE: When monitoring news for a specific portfolio. Pass ticker/weight pairs to get impact-ranked coverage. RETURNS: Holdings summary (briefs count, sentiment per ticker), portfolio-relevant briefs ranked by relevance score. COST: 2 credits. EXAMPLE: { "holdings": [{ "ticker": "AAPL", "weight": 0.3 }, { "ticker": "NVDA", "weight": 0.2 }], "days": 7 }

Get a sector overview with aggregate sentiment scores and brief counts across all market sectors.

WHEN TO USE: For a macro view of which sectors have the most bullish or bearish news coverage. Good for sector rotation analysis. RETURNS: Per-sector data: ticker count, brief count, average sentiment, and top tickers with individual sentiment. COST: 1 credit. EXAMPLE: { "days": 7 }

Get OHLCV candlestick data for a stock ticker — open, high, low, close, and volume.

WHEN TO USE: For price chart analysis, pattern recognition, or feeding data into technical analysis. Use veroq_technicals for pre-computed indicators. RETURNS: Array of candles with date, open, high, low, close, volume. Latest candle highlighted. COST: 2 credits. EXAMPLE: { "symbol": "AAPL", "interval": "1d", "range": "3mo" }

Get all major technical indicators for a ticker: RSI, MACD, Bollinger Bands, moving averages, and overall signal summary.

WHEN TO USE: For pre-computed technical analysis. Returns a bullish/bearish/neutral signal. Use veroq_candles for raw price data instead. RETURNS: Signal summary (signal + bullish/bearish/neutral counts) and full indicator values (RSI, MACD, BBands, SMA, EMA). COST: 2 credits. EXAMPLE: { "symbol": "TSLA", "range": "6mo" }

Get next earnings date, EPS estimates, and revenue estimates for a stock ticker.

WHEN TO USE: To check when a company reports earnings and what the Street expects. Useful before earnings season. RETURNS: Next earnings date, fiscal quarter, EPS estimate, and revenue estimate. COST: 2 credits. EXAMPLE: { "symbol": "NVDA" }

Get today's top market movers: biggest gainers, losers, and most actively traded stocks.

WHEN TO USE: For a quick snapshot of what's moving the market today. No parameters needed. RETURNS: Top gainers (symbol, price, change%), top losers, and most active by volume. COST: 1 credit. EXAMPLE: {}

Get current values for major market indices: S&P 500, Nasdaq, Dow Jones, and VIX.

WHEN TO USE: For a quick check on how the overall market is doing. No parameters needed. RETURNS: Each index with price, change, and change percent. COST: 1 credit. EXAMPLE: {}

Get macroeconomic indicators from FRED. No arguments returns a summary of all key indicators; pass a slug for detailed history.

WHEN TO USE: For macro data like GDP, CPI, unemployment, fed funds rate. Use veroq_economy_indicator for a single indicator with history. RETURNS: Summary mode: all indicators with latest values. Detail mode: series info, latest value, and historical observations. COST: 2 credits. EXAMPLE: { "indicator": "cpi", "limit": 12 }

Get current foreign exchange rates. No arguments returns all major pairs; pass a pair code for a single rate.

WHEN TO USE: For currency exchange rates and FX market data. RETURNS: Rate, change, change percent per pair. Single pair mode includes label and timestamp. COST: 2 credits. EXAMPLE: { "pair": "EURUSD" }

Get commodity prices (gold, silver, oil, natural gas, etc.). No arguments returns all; pass a slug for one commodity.

WHEN TO USE: For commodity market data. Covers precious metals, energy, and industrial commodities. RETURNS: Price, change, change percent, and unit per commodity. COST: 2 credits. EXAMPLE: { "symbol": "gold" }

Get cryptocurrency data. No arguments returns market overview; pass a symbol for detailed token data.

WHEN TO USE: For crypto market cap overview or individual token data (price, supply, ATH). Use veroq_crypto_chart for price history. RETURNS: Overview: total market cap, BTC dominance, 24h volume. Token: price, 24h/7d change, market cap, supply, ATH. COST: 2 credits. EXAMPLE: { "symbol": "ETH" }

Get historical price chart data for a crypto token — timestamped prices for trend analysis.

WHEN TO USE: For crypto price history and charting. Use veroq_crypto for current snapshot, this for historical trend. RETURNS: Sampled price history with timestamp, price, volume, and market cap per data point. Includes period change %. COST: 2 credits. EXAMPLE: { "symbol": "BTC", "days": 90 } CONSTRAINTS: Max 365 days of history.

Get DeFi data. No arguments returns TVL overview with top protocols and chain breakdown; pass a slug for one protocol.

WHEN TO USE: For DeFi TVL data across protocols and chains. Use veroq_defi_protocol for a single protocol deep dive. RETURNS: Overview: total TVL, top protocols, chain TVL. Protocol: TVL, 1d/7d/30d changes, category, chains. COST: 2 credits. EXAMPLE: { "protocol": "aave" }

Screen stocks or crypto by combining technical indicators, sentiment, and fundamental filters.

WHEN TO USE: To find assets matching specific criteria (e.g. oversold tech stocks, high-volume bearish crypto). Use veroq_screener_presets for pre-built strategies. RETURNS: Matching assets with symbol, price, change%, RSI, MACD signal, sentiment, and volume. COST: 5 credits. EXAMPLE: { "sector": "Technology", "rsi_below": 30, "sentiment": "bearish", "limit": 10 }

List pre-built screening strategies or run a specific preset by ID.

WHEN TO USE: For quick screening without building filters manually. Omit preset_id to list all 12 presets; pass one to run it. RETURNS: List mode: preset names, descriptions, and filters. Run mode: matching assets with price, RSI, sentiment, volume. COST: 1 credit. EXAMPLE: { "preset_id": "oversold_tech" }

Create, list, or check triggered price/sentiment alerts.

WHEN TO USE: To set up automated monitoring. Actions: "create" a new alert, "list" existing alerts, or view "triggered" alerts. RETURNS: Create: alert ID and details. List: all alerts with status. Triggered: fired alerts with current values. COST: 3 credits. EXAMPLE: { "action": "create", "ticker": "AAPL", "alert_type": "price_below", "threshold": 150 } CONSTRAINTS: 6 alert types: price_above, price_below, rsi_above, rsi_below, sentiment_flip, volume_spike.

Get social media sentiment for a stock or crypto ticker from Reddit, Twitter/X, and other platforms.

WHEN TO USE: To gauge retail investor sentiment and social buzz around a specific ticker. RETURNS: Overall sentiment score, mention count, per-platform breakdown, trending topics, and top posts with URLs. COST: 30 credits. EXAMPLE: { "symbol": "TSLA" }

Get tickers and topics currently trending on social media across Reddit, Twitter/X, and other platforms.

WHEN TO USE: To discover what retail investors are buzzing about right now. No parameters needed. RETURNS: Trending symbols with name, mention count, sentiment score, and 1-hour change in mentions. COST: 20 credits. EXAMPLE: {}

Get upcoming and recent IPOs from SEC EDGAR S-1 filings.

WHEN TO USE: To track the IPO pipeline and recent public offerings. RETURNS: IPO filings with company name, ticker (if assigned), filing date, form type, and location. COST: 2 credits. EXAMPLE: { "days": 30, "limit": 20 } CONSTRAINTS: Max 90 days lookback, max 100 results.

Get recent news headlines and briefs for a specific stock or crypto ticker.

WHEN TO USE: For ticker-specific news. Use veroq_search for topic-based search, or veroq_feed for general news. RETURNS: Array of briefs with headline, confidence, category, and summary. Includes total brief count. COST: 1 credit. EXAMPLE: { "symbol": "AAPL", "limit": 5 }

Get a comprehensive analysis for a ticker combining news sentiment, technicals, events, and overall outlook.

WHEN TO USE: For a detailed single-ticker analysis with outlook, catalysts, and risks. Use veroq_full for raw data, this for interpreted analysis. RETURNS: Outlook (bullish/bearish/neutral), summary, sentiment score, key factors, catalysts, risks, technicals, and recent coverage. COST: 2 credits. EXAMPLE: { "symbol": "NVDA" }

Get search autocomplete suggestions — matching headlines and entities for a partial query.

WHEN TO USE: To find the right search terms before running veroq_search. Helps discover entities and headlines. RETURNS: Headline suggestions (with category and brief ID) and entity suggestions (with type and mention count). COST: 1 credit. EXAMPLE: { "query": "fed rate" } CONSTRAINTS: Minimum 2 characters.

Get detailed DeFi protocol data including TVL, chain deployment, and performance changes.

WHEN TO USE: For a deep dive into a single DeFi protocol. Use veroq_defi (no args) for the full DeFi market overview. RETURNS: Protocol TVL, 1d/7d/30d change percentages, category, and deployed chains. COST: 2 credits. EXAMPLE: { "protocol": "uniswap" }

Get a specific FRED economic indicator with historical observations.

WHEN TO USE: For detailed history of one indicator. Use veroq_economy (no args) for a summary of all indicators. RETURNS: Series info (ID, frequency, units), latest value, and historical observations array. COST: 2 credits. EXAMPLE: { "indicator": "fed_funds", "limit": 24 } CONSTRAINTS: Max 100 observations.

Generate an AI-powered research report for a ticker. Kicks off async generation — use veroq_get_report to retrieve the result.

WHEN TO USE: For a polished, shareable research report. Use veroq_ticker_analysis for instant inline analysis instead. RETURNS: Report ID, ticker, tier, and status message. Use the report_id with veroq_get_report to fetch the full report. COST: 5 credits (quick tier). Deep tier requires a paid plan. EXAMPLE: { "ticker": "AAPL", "tier": "quick" }

Retrieve a previously generated report by its ID.

WHEN TO USE: After calling veroq_generate_report, use this to fetch the completed report content. RETURNS: Full report with title, ticker, tier, creation date, and markdown content (or structured sections). COST: 1 credit. EXAMPLE: { "report_id": "rpt_abc123" }

Get the full profile for a ticker — price, fundamentals, technicals, sentiment, and recent news in one call.

WHEN TO USE: For a complete data dump on a single ticker. 9 sources in parallel. Use veroq_ticker_analysis for an interpreted analysis instead. RETURNS: Price data, fundamentals, technical indicators, sentiment scores, and recent news briefs. COST: 2 credits. EXAMPLE: { "ticker": "NVDA" }

Get insider trading activity for a stock — executive and director buys/sells from SEC Form 4 filings.

WHEN TO USE: To check if insiders are buying or selling a stock. Key signal for institutional-grade analysis. RETURNS: Transaction list with insider name, title, type (buy/sell), shares, price, value, and date. Plus summary stats. COST: 2 credits. EXAMPLE: { "ticker": "AAPL" }

Get recent SEC filings for a stock — 10-K, 10-Q, 8-K, and other regulatory filings with source links.

WHEN TO USE: For regulatory filing history and due diligence. Links directly to SEC EDGAR source documents. RETURNS: Filing list with form type, title, filing date, reporting period, and URL. COST: 2 credits. EXAMPLE: { "ticker": "TSLA" }

Get Wall Street analyst ratings and price targets for a stock.

WHEN TO USE: To see consensus analyst opinion and price target range for a stock. RETURNS: Consensus rating, mean/high/low price targets, analyst count, and individual ratings with firm, target, and date. COST: 2 credits. EXAMPLE: { "ticker": "NVDA" }

Get recent stock trades by members of U.S. Congress from public disclosure filings.

WHEN TO USE: To track congressional trading activity — politically-informed trading signals. Filter by ticker for specific stocks. RETURNS: Trades with member name, party, state, chamber, ticker, transaction type, amount range, and date. COST: 2 credits. EXAMPLE: { "symbol": "NVDA" }

Get institutional ownership data for a stock — top holders and ownership changes from 13F filings.

WHEN TO USE: To see which institutions own a stock and whether they're increasing or decreasing positions. RETURNS: Total institutional ownership %, summary stats, and top holders with shares, value, percent held, change, and filing date. COST: 2 credits. EXAMPLE: { "ticker": "AAPL" }

Run a VEROQ AI agent by its slug — pre-built workflows combining multiple data sources and analysis steps.

WHEN TO USE: For complex multi-step analysis tasks like portfolio reviews, due diligence, or market scans. Agents automate what would take many individual tool calls. RETURNS: Agent name, execution steps (with status/summary per step), final output or structured result, and credits used. COST: 5-100 credits (varies by agent complexity). EXAMPLE: { "slug": "due-diligence", "inputs": { "ticker": "AAPL" } }

Pre-computed buy/sell signals across 78 tickers — refreshed every cycle.

WHEN TO USE: For a quick overview of all active signals without running individual ticker analyses. Good for scanning opportunities. RETURNS: Array of tickers with signal direction (buy/sell/hold), score, and contributing factors. COST: 1 credit. EXAMPLE: {}

Macro dashboard: yields, CFTC positioning, jobs, energy — all pre-computed.

WHEN TO USE: For a single-call macro snapshot combining treasury yields, CFTC Commitment of Traders, employment data, and energy prices. RETURNS: Structured macro data across multiple categories. COST: 1 credit. EXAMPLE: {}

Pre-computed signal for one ticker — fast lookup without running full analysis.

WHEN TO USE: When you need the signal for a specific ticker quickly. Faster than veroq_ticker_score because it reads pre-computed data. RETURNS: Ticker signal with score, direction, and factors. COST: 1 credit. EXAMPLE: { "ticker": "NVDA" }

Biggest signal changes in the last cycle — tickers where the signal moved most.

WHEN TO USE: To identify which tickers had the biggest change in buy/sell signals recently. Good for momentum or reversal detection. RETURNS: Array of tickers with previous and current signal scores and the delta. COST: 1 credit. EXAMPLE: {}

All 78 tickers with signal scores — heatmap-style overview.

WHEN TO USE: For a complete view of all tracked tickers and their current signal scores. Good for building visual dashboards or scanning all at once. RETURNS: Array of all tickers with signal scores. COST: 1 credit. EXAMPLE: {}

Travel disruption score combining TSA volumes, FAA delays, and border wait times.

WHEN TO USE: For a quick snapshot of US travel conditions — airport delays, passenger throughput, and border crossing waits. RETURNS: Composite disruption score, TSA passenger counts, FAA ground stops, and border wait times. COST: 1 credit. EXAMPLE: {}

TSA daily passenger volumes — throughput data from US airport checkpoints.

WHEN TO USE: To track airport passenger volumes and compare to historical levels. Useful for travel industry analysis and consumer spending indicators. RETURNS: Daily passenger counts, year-over-year comparison, and trend data. COST: 1 credit. EXAMPLE: {}

FAA ground stops and airport delays — live data from the FAA.

WHEN TO USE: To check for current airport delays, ground stops, or airspace disruptions in the US. RETURNS: Active ground stops, ground delay programs, airport closures, and general delay information. COST: 1 credit. EXAMPLE: {}

Recent SEC filings (10-K, 10-Q, 8-K) for a company from EDGAR.

WHEN TO USE: To see a company's recent regulatory filings — annual reports, quarterly reports, and current event disclosures. RETURNS: List of filings with type, date, description, and EDGAR URL. COST: 1 credit. EXAMPLE: { "ticker": "AAPL" }

Form 4 insider trades for a company from SEC EDGAR.

WHEN TO USE: To see insider buying and selling activity — who traded, how many shares, and at what price. Complements veroq_insider which uses a different data source. RETURNS: List of insider transactions with name, title, date, shares, price, and transaction type. COST: 1 credit. EXAMPLE: { "ticker": "TSLA" }

XBRL financial data for a company from SEC EDGAR.

WHEN TO USE: To get structured financial statements (income statement, balance sheet, cash flow) directly from SEC filings. RETURNS: Financial data extracted from XBRL filings including revenue, net income, assets, liabilities, and cash flows. COST: 1 credit. EXAMPLE: { "ticker": "MSFT" }

Oil prices, petroleum inventory, and natural gas data.

WHEN TO USE: For a snapshot of the energy market — crude oil (WTI/Brent) prices, EIA petroleum inventories, and natural gas spot prices. RETURNS: Current prices, inventory levels, and recent changes. COST: 1 credit. EXAMPLE: {}

Treasury yield curve with inversion detection.

WHEN TO USE: To check the current US Treasury yield curve across maturities (1M, 3M, 6M, 1Y, 2Y, 5Y, 10Y, 30Y) and detect inversions that may signal recession. RETURNS: Yield values per maturity, spread calculations, and inversion flags. COST: 1 credit. EXAMPLE: {}

CFTC Commitment of Traders positioning for a commodity.

WHEN TO USE: To see how commercial hedgers, large speculators, and small traders are positioned in futures markets. A contrarian indicator — extreme positioning often precedes reversals. RETURNS: Net positions by trader category, open interest, and changes from prior week. COST: 1 credit. EXAMPLE: { "commodity": "gold" }

Wikipedia attention score for an entity — pageview-based interest signal.

WHEN TO USE: To gauge public interest in a company, person, or topic based on Wikipedia traffic. Spikes in attention often precede or accompany market moves. RETURNS: Pageview counts, trend direction, and percentile ranking. COST: 1 credit. EXAMPLE: { "entity": "NVIDIA" }

Latest arXiv AI/ML research papers.

WHEN TO USE: To discover recent academic research in artificial intelligence and machine learning. Good for tracking cutting-edge developments. RETURNS: List of papers with title, authors, abstract, categories, and arXiv URL. COST: 1 credit. EXAMPLE: {}

Trending GitHub repos with AI detection — what developers are building now.

WHEN TO USE: To see which GitHub repositories are trending, with automatic detection of AI/ML-related projects. Good for tech trend analysis. RETURNS: List of trending repos with stars, forks, language, description, and AI classification. COST: 1 credit. EXAMPLE: {}

FDA drug approvals and recalls — recent regulatory actions.

WHEN TO USE: To track FDA drug approvals, rejections, and recalls. Important for biotech/pharma stock analysis. RETURNS: List of recent FDA actions with drug name, company, action type, date, and details. COST: 1 credit. EXAMPLE: {}

Recent Congressional bills — legislation that may affect markets.

WHEN TO USE: To track new legislation in the US Congress that could impact industries or markets. Good for policy risk analysis. RETURNS: List of bills with title, sponsor, status, introduced date, and summary. COST: 1 credit. EXAMPLE: {}

New Federal Register regulations — proposed and final rules.

WHEN TO USE: To track new federal regulations that could affect specific industries. Good for compliance and regulatory risk analysis. RETURNS: List of regulations with title, agency, type (proposed/final), publication date, and summary. COST: 1 credit. EXAMPLE: {}

Hacker News top stories — what the tech community is discussing.

WHEN TO USE: To see what's trending on Hacker News. Good for tracking tech industry sentiment and emerging topics. RETURNS: List of top stories with title, score, comment count, author, and URL. COST: 1 credit. EXAMPLE: {}

BLS employment data — nonfarm payrolls, unemployment rate, and labor market indicators.

WHEN TO USE: For US employment data from the Bureau of Labor Statistics. Key economic indicator for market analysis and Fed policy expectations. RETURNS: Latest employment figures, historical comparison, and labor market metrics. COST: 1 credit. EXAMPLE: {}

US GDP data from the World Bank — gross domestic product and growth rates.

WHEN TO USE: For GDP data and economic growth analysis. Useful for macro context and long-term trend analysis. RETURNS: GDP values, growth rates, and historical comparison. COST: 1 credit. EXAMPLE: {}

Full background research on a topic — aggregates briefs, entities, timeline, and related data.

WHEN TO USE: When you need comprehensive background on a topic before answering a complex question. Broader than veroq_ask — returns raw context rather than a synthesized answer. RETURNS: Aggregated briefs, entity profiles, timeline of events, and related topics. COST: 3 credits. EXAMPLE: { "topic": "semiconductor export controls" }

Cross-category impact analysis — how a topic affects multiple sectors and asset classes.

WHEN TO USE: For understanding second-order effects of events. E.g., how a Fed rate decision impacts tech stocks, bonds, crypto, and real estate simultaneously. RETURNS: Impact scores across categories, affected tickers, transmission channels, and risk assessment. COST: 5 credits. EXAMPLE: { "topic": "Fed rate cut" }

List available vertical agent packs — pre-built agent configurations for specific domains.

WHEN TO USE: To discover which agent packs are available before calling veroq_run_agent. Each pack is a curated workflow for a specific use case. RETURNS: List of agent packs with slug, name, description, required inputs, and credit cost. COST: 1 credit. EXAMPLE: {}