All Services

Computes a benchmark correlation report for token assessment evidence coverage, comparing observed vs requested fields against provided benchmark values using a deterministic calculation.

Generates a distribution histogram (with configurable bins) summarizing evidence coverage ratios across multiple token assessment observations.

Compares named alternative scenarios against a baseline for token assessment evidence coverage, calculating how many observed fields cover requested fields across up to 20 labeled scenarios.

Generates a one-input sensitivity table showing how token assessment evidence coverage scores vary as a single input field changes across a supplied range of values.

Ranks token assessment evidence coverage records by computing a deterministic coverage ratio (observed fields vs. requested fields) for each supplied row, returning ordered ranking results.

Computes a rolling mean of token assessment evidence coverage ratios (observed vs. requested fields) over a sliding window across a series of token observations.

Calculates the evidence coverage ratio for a token assessment by comparing observed fields to requested fields, returning a deterministic coverage score or verdict.

Classifies token assessment evidence coverage ratios against caller-defined lower/upper thresholds across multiple rows of observed vs. requested field counts.

Computes a weighted mean of token assessment evidence coverage ratios from multiple observations, where each row compares observed fields to requested fields.

Computes adjacent period-over-period changes in the average reported trade notional (volume_usd / trades) for a token across a supplied sequence of observation rows.

Computes the local finite-change elasticity of a token's average reported trade notional with respect to a small percentage step in volume or trade count.

Analyzes ordered trend direction of average reported trade notional (volume_usd / trades) across a supplied time-series of token trade observations.

Ranks token average reported trade notional (volume_usd / trades) across a set of supplied token observations and returns a deterministic record ranking report.

Computes a rolling mean of average reported trade notional (volume_usd / trades) over a sliding window across a supplied sequence of token trade observations.

Computes a sequential input-change (waterfall) attribution for the average reported trade notional of a token, comparing before and after trade/volume states.

Calculates the gap between a supplied target value and the computed average reported trade notional for a token, given trade count and USD volume inputs.

Computes a weighted arithmetic mean of token average reported trade notional (volume_usd / trades) across multiple data rows using caller-supplied weights.

Computes the correlation between a series of token bid-ask spread observations and a provided benchmark series, returning a bounded deterministic report.

Calculates the target gap for a token's bid-ask spread given observed bid/ask prices and a target value, returning a deterministic report.

Computes adjacent-period changes in token buy receipt shortfall (expected vs actual tokens received) across a supplied sequence of observations.

Calculates the token quantity shortfall between expected and actual tokens received for up to 200 token purchase rows in a single batch call.

Compares named scenarios of token buy receipt shortfall (expected vs actual tokens received) against a baseline, returning a deterministic verdict for each scenario.

Calculates the gap between expected and actual tokens received in a buy transaction, determining whether a configurable target threshold is met

Generates a two-dimensional scenario grid showing token buy receipt shortfall outcomes across combinations of expected and actual token values.

Computes a weighted mean of token buy receipt shortfall values (expected minus actual tokens received) across multiple observations.

Computes the local finite-change elasticity of the token buy-to-sell activity ratio given a baseline buy/sell count and a percentage step size.

Calculates a Base-100 rebased index of token buy volume fraction (buy volume as a share of total volume) across a time series of up to 200 observations.

Calculates the local finite-change elasticity of the token buy volume fraction given baseline buy/sell volumes and a percentage step size.

Computes a token's buy volume fraction across a two-dimensional grid of buy/sell volume scenarios using deterministic calculation.

Computes a Base-100 rebased index series for token circulating market capitalization (price × circulating supply) across a supplied sequence of observations, anchored to a chosen base period.

Computes a sequential input-change attribution (waterfall) report for the token circulating supply fraction metric, given before and after token supply observations.

Calculates the gap between a token's circulating supply fraction and a specified target value, returning a deterministic report based on supplied token observations.

Computes the local finite-change elasticity of a token's circulating market cap relative to its fully diluted valuation (FDV), given baseline figures and a step percentage.

Calculates the gap between a token's circulating market cap and its fully diluted valuation (FDV) relative to a caller-specified target threshold

Computes the local finite-change elasticity of token price drawdown from a supplied peak, given a baseline peak price, current price, and a percentage step size.

Computes period-over-period changes in token execution fee as a ratio of notional value for a sequence of observations

Computes a base-100 rebased index of token execution fee as a fraction of notional value across a series of trade observations, anchored to a chosen baseline row.

Computes the local finite-change elasticity of a token's execution fee relative to its notional value, quantifying how sensitively the fee-to-notional ratio responds to small percentage changes in either fee or notional.

Calculates the execution fee as a percentage of notional value for a token trade, returning a deterministic fee-burden ratio from supplied fee and notional USD inputs.

Geocodes a place name or address query into geographic coordinates (latitude, longitude) with country metadata

Returns SSL/TLS certificate history and subdomain enumeration data for a given domain name

Returns public holidays for a given country and year, including dates, English names, and local-language names

Fetches GitHub repository metadata including stars, forks, language, and latest release for a given repo via the tokenguard crypto/DeFi API platform.

Fetches dYdX decentralized exchange data including market stats, order books, trading activity, and protocol analytics via POST request

Returns detailed on-chain and market data for a specific DeFi protocol, including analytics, safety metrics, and ecosystem intelligence.

Retrieves cryptocurrency futures market data and analytics via the TokenGuard DeFi intelligence platform

Retrieves order book data (bids/asks) for a specified cryptocurrency trading pair or token via the TokenGuard DeFi analytics platform

Retrieves GMX decentralized perpetuals exchange data including trading metrics, liquidity, and market analytics via the TokenGuard DeFi intelligence API

Returns x402 API marketplace analytics including pricing distributions, supply/demand metrics, coverage statistics, and demand ranked by tag across x402-monetized web resources.

Fetches Chainlink oracle price feed data for crypto/DeFi assets via a micropayment-gated POST API

Returns geolocation and ISP information for the caller's public IP address including city, country, coordinates, and timezone

Fetches Raydium DEX market data, pool analytics, and liquidity information for DeFi analysis on the Solana ecosystem

Searches academic papers on crypto, DeFi, and agent payment protocols via OpenAlex, returning titles, DOIs, years, and citation counts

Performs a web search query using DuckDuckGo and returns ranked results with titles, URLs, and snippets

Retrieves trading volume data for cryptocurrency exchanges via the TokenGuard DeFi analytics platform

Returns structured country information including name, capital, languages, currencies, population, and calling code for a given country code.

Retrieves centralized exchange (CEX) market data for crypto tokens via the TokenGuard DeFi analytics API

Retrieves funding-related DeFi/crypto data (e.g. funding rates, project funding rounds, or protocol treasury info) via a micropayment-gated POST call on the TokenGuard platform

Retrieves Lido protocol analytics and staking data including stETH metrics, validator info, and DeFi intelligence for AI agents

Computes a sequential input-change (waterfall) attribution report showing how changes in token holder count and market cap affect the holders-per-million metric between two states.

Validates a CSV of token holder observations and identifies blank/empty rows in the dataset, up to 1000 rows.

Validates date fields in a CSV table of token holder observations, checking that calendar date values conform to expected formats and constraints.

Validates cell length constraints in a CSV of token holder observations, flagging cells that exceed a specified maximum character length across up to 1000 rows.

Validates a CSV table of token holder observations (up to 1000 rows) against a declared contract, checking structure, cell lengths, numeric ranges, and category values.

Validates a CSV file of token holder observations by checking declared column projections against up to 1000 rows of data.

Validates the CSV header contract (column names, types, and value constraints) for token holder observation data, supporting up to 1000 rows.

Validates that record keys in a token holder observations CSV are unique, checking up to 1000 rows for duplicate primary keys.

Calculates local finite-change elasticity for a token's net supply flow (issued minus burned), quantifying how small percentage changes in one token supply variable affect the net flow.

Computes a sequential input-change attribution waterfall for token net supply (issued minus burned), comparing before and after token states to explain how each input change contributed to the net supply shift.

Classifies whether a token's net supply flow (issued minus burned) falls within caller-defined lower and upper thresholds across a sequence of observations.

Calculates how adjacent-period changes in position size, daily volume, and participation rate affect token liquidation timelines across a batch of observations.

Computes a base-100 rebased index for token liquidation participation scenarios given position size, daily volume, and participation percentage inputs.

Computes benchmark correlation statistics for token liquidation participation scenarios given position size, daily volume, and participation rate observations.

Generates a distribution histogram showing how token liquidation times are distributed across a set of supplied position, volume, and participation-rate observations.

Computes IQR-based outlier flags for token liquidation participation metrics across a supplied set of observations, returning a deterministic statistical report.

Performs ordered trend analysis on a sequence of token liquidation participation observations (position size, daily volume, participation percent) and returns a deterministic trend verdict.

Computes a rolling mean of token liquidation participation metrics (position size, daily volume, participation percent) over a specified window of observations.

Classifies token liquidation participation scenarios against user-defined lower and upper thresholds, given position size, daily volume, and participation percentage inputs.

Computes the local finite-change elasticity of a token's liquidity relative change given current and previous liquidity values and a step size.

Computes a sequential input-change attribution (waterfall) report showing how changes in token liquidity inputs drive the relative change between two observations.

Calculates the gap between a token's current liquidity-to-market-cap ratio and a specified target ratio, returning a deterministic report.

Classifies whether a token's liquidity-to-market-cap ratio falls within caller-defined threshold bounds, returning a deterministic verdict for each supplied token observation.

Computes a base-100 rebased index of token net buy-count balance from a series of buy/sell count observations, anchored to a caller-specified base row.

Computes the local finite-change elasticity of a token's net buy-count balance given baseline buy/sell counts and a percentage step size.

Ranks a set of token observations by their net buy-count balance (buy_count minus sell_count) and returns a deterministic record ranking report.

Calculates the gap between a token's net buy-count balance and a user-specified target value, returning a deterministic numeric report.

Computes a weighted mean of the net buy-count balance (buy_count vs sell_count ratio) across multiple token observations using caller-supplied weights.

Compares multiple named price-change scenarios for a token against a baseline, returning a deterministic percentage-change report for each labeled scenario.

Validates a CSV of token pool observations and reports any blank rows found within the data.

Validates cell length constraints in a CSV table of token pool observations, checking up to 1000 rows for compliance with a declared contract.

Validates a declared CSV table contract for token pool observation data, checking column structure and projecting up to 1000 rows with configurable constraints.

Validates a CSV of token pool observation data and exports a report identifying rows that fail defined constraints (value ranges, category allowlists, etc.)

Validates numeric values in a token pool observations CSV table against declared minimum/maximum bounds and allowed category lists, returning a range-check report.

Validates a CSV table of token pool observations and flags spreadsheet formula issues, checking up to 1000 rows against declared contract rules.

Validates and normalizes a CSV table of token pool observations (up to 1000 rows) by trimming whitespace, inferring types, and enforcing declared column contracts.

Computes a base-100 rebased index of the relative price difference between a token pool quote and a reference price across a series of observations.

Computes the relative difference (gap) between a token pool price and a reference price, comparing a 'before' snapshot and an 'after' snapshot to show how the price gap changed.

Computes the correlation between token pool price-gap (relative difference between pool price and reference price) observations and a set of benchmark values, returning a deterministic correlation report.

Computes a one-input sensitivity table for the relative price gap between a token pool quote price and a reference price, sweeping a single variable across user-supplied values.

Computes the relative price difference between a token pool price and a reference price, then evaluates whether that gap meets a caller-specified target threshold.