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

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

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.

Computes the weighted mean of relative price differences between pool quotes and reference prices across multiple token observations.

Computes benchmark correlation for token position price stress, comparing observed price-change outcomes against user-supplied benchmark thresholds using a deterministic calculation.

Computes a Base-100 rebase index comparing a token position's USD value against its fully diluted valuation (FDV) across multiple observations, using deterministic calculation.

Computes a statistical distribution summary of token position size relative to fully-diluted valuation (FDV) across a batch of observations.

Computes the local finite-change elasticity of a token position relative to its fully diluted valuation (FDV), given a baseline position and FDV in USD and a percentage step size.

Performs ordered trend analysis on a time-series of token position size versus fully diluted valuation (FDV) observations to identify directional patterns.

Ranks a batch of token position-to-FDV observations by their ratio, producing a deterministic record-level ranking report for supplied data only.

Computes a rolling mean of the ratio between a token position's USD value and its fully diluted valuation (FDV) across a supplied time series of observations.

Computes a weighted arithmetic mean of token position-to-FDV ratios from a supplied set of observations

Calculates the marginal change in token dilution fraction caused by an unlock event, using sequential before/after input attribution to isolate each input's contribution.

Computes a base-100 rebased index comparing quoted token amounts against actually received token amounts across a batch of observations, flagging shortfall magnitude deterministically.

Calculates the local finite-change elasticity between a token quote amount and the received amount, measuring how sensitive the shortfall ratio is to small percentage changes in one of those values.

Compares quoted token amounts against received token amounts across named scenarios to compute shortfall metrics deterministically.

Computes a rolling mean of token quote shortfall (quoted minus received token amounts) over a sliding window across a series of observations.

Computes a sequential input-change attribution (waterfall) report comparing before/after token quote and received amounts to explain shortfall changes.

Classifies whether the shortfall between quoted and received token amounts falls within or outside a caller-defined threshold range, using deterministic calculation.

Generates a deterministic two-dimensional scenario grid comparing quoted token amounts versus received token amounts across user-specified value ranges to compute shortfall stress metrics.

Computes a weighted mean of token quote shortfall (quoted tokens minus received tokens) across multiple trade observations

Checks whether a given token or credential is safe, valid, or compromised

Provides AI-powered NFT analysis by combining CoinGecko and DexScreener data with MiMo LLM intelligence to deliver crypto NFT insights

Fetches AI-powered cryptocurrency market data and analysis using CoinGecko, DexScreener, and MiMo LLM, comparing a token against a specified quote currency or asset.

Returns a list of supported cryptocurrencies with optional currency conversion context via AI-powered crypto intelligence

AI-powered NFT intelligence combining on-chain data and LLM analysis to provide insights on NFT collections and tokens

AI-powered DeFi analysis endpoint combining CoinGecko and DexScreener data with MiMo LLM to deliver crypto market intelligence

Calculates local finite-change elasticity of token sell proceeds shortfall, measuring how proportionally a sell proceeds gap changes relative to small percentage-point shifts in a given input field.

Compares named scenarios for token sell proceeds shortfall, calculating how much actual USD sale proceeds fall short of expected proceeds across up to 20 labelled scenario overrides.

Computes a one-input sensitivity table showing how token sell proceeds shortfall varies as a single input (expected or actual USD) changes across a range of values.

Analyzes a sequence of token sell transactions to identify ordered trends in the shortfall between expected and actual USD proceeds.

Calculates the gap between expected and actual USD proceeds from a token sell, determining how far short the outcome fell from a target threshold.

Classifies whether token sell proceeds shortfall (expected vs actual USD received) falls within a caller-defined threshold range, using a deterministic calculation on supplied rows.

Computes a weighted mean of token sell proceeds shortfall values (expected vs actual USD) across multiple trade observations.

Computes a distribution histogram of the rule-flag fraction (flagged_rules / evaluated_rules) across a batch of token observations, bucketed into configurable bins.

Computes a statistical distribution summary (min, max, mean, percentiles, etc.) of the rule-flag fraction (flagged_rules / evaluated_rules) across a batch of supplied token observations.

Computes IQR-based outlier flags for the fraction of flagged rules among supplied token observations, returning a deterministic statistical verdict per row.

Computes and compares the fraction of flagged rules to evaluated rules for a token across named what-if scenarios against a baseline, returning deterministic verdicts.

Computes a rolling mean of the fraction of flagged rules out of evaluated rules across a sequence of token-supplied observations

Calculates the fraction of evaluated token supply rules that have been flagged, returning a deterministic ratio from flagged_rules and evaluated_rules inputs.

Classifies whether the fraction of flagged rules out of evaluated rules for token observations falls within a specified threshold range, returning a bounded verdict for each row.

Computes the weighted mean of the flagged-rules fraction (flagged_rules / evaluated_rules) across multiple token observations supplied by the caller.

Computes the local finite-change elasticity of token supply relative change given a baseline old/new supply and a step percentage.

Validates a CSV of token swap records and identifies blank rows, up to 1000 rows.

Validates a CSV of token swap records by checking that a specified column's values fall within an allowed category list, returning a pass/fail report.

Validates cell length constraints in a CSV table of token swap records, auditing up to 1000 rows for compliance with declared length limits.

Validates a token swap CSV and returns per-column statistics (count, min, max, mean, categories) for up to 1000 rows.

Validates a CSV file of token swap records against a declared column schema contract, returning a column projection report for up to 1000 rows.

Validates numeric columns in a token swap CSV dataset, checking that values fall within allowed types, ranges, and category constraints — up to 1000 rows.

Validates a CSV table of token swap records (up to 1000 rows) and flags cells containing spreadsheet formula injection patterns.

Validates a CSV file of token swap records for whitespace anomalies, checking up to 1000 rows with support for quoted cells and configurable delimiters.

Computes period-over-period changes in the token transfer receipt fraction (received/sent ratio) across a sequence of token transfer observations.

Computes a base-100 rebased index of the ratio between received and sent tokens across a batch of transfer observations, with a configurable base row.

Computes and compares the token transfer receipt fraction (received/sent ratio) across multiple named scenarios against a baseline, returning a deterministic verdict for each scenario.

Ranks a batch of token transfer records by their receipt fraction (received_tokens / sent_tokens) using deterministic computation.

Classifies whether the ratio of received-to-sent tokens in transfer rows falls within a user-defined threshold range, using deterministic calculation.

Computes a grid of token transfer receipt fraction values across two variable dimensions (sent_tokens and received_tokens) for scenario analysis

Ranks a batch of token observations by their turnover-to-liquidity ratio (period volume divided by liquidity), returning a deterministic record-level ranking report.

Calculates the gap between a token's current turnover-to-liquidity ratio and a user-specified target value, returning a deterministic verdict report.

Computes period-over-period changes in token unlock notional value (tokens × spot price) across a supplied sequence of unlock observations.

Ranks a set of token unlock observations by notional value (unlock_tokens × price_usd) and returns a deterministic record-level ranking report.

Validates a CSV file of token unlock schedule data and reports blank or empty rows, up to 1000 rows.

Validates a token unlock schedule CSV for cell length violations, checking up to 1000 rows with configurable max cell length and allowed category filters.

Validates a CSV of token unlock schedule data against a declared column contract, projecting and checking up to 1000 rows for structural and value correctness.

Validates a CSV table of token unlock schedule data and flags cells containing spreadsheet formulas, up to 1000 rows.

Calculates the relative (percentage) change in token trading volume between adjacent time periods for a batch of token observations.

Computes a base-100 rebased index of token trading volume relative to market capitalization across a supplied series of token observations.

Computes the correlation between a token's volume-to-market-cap ratio observations and a set of benchmark values, returning a deterministic statistical report.

Computes local finite-change elasticity of token trading volume relative to market capitalization for a given baseline and step size

Computes and compares token trading volume relative to market capitalization across multiple named scenarios using supplied token observations.

Computes a one-input sensitivity table for the token volume-to-market-cap ratio, varying either volume or market cap across a supplied range of values against a baseline.

Computes a weighted mean of the volume-to-market-cap ratio across multiple token observations using caller-supplied weights.

Acts as a unified pay-per-call gateway aggregating 2,000+ AI-agent tools and x402 services, paid per call in USDC via HTTP 402 with no signup or API key required.

Aggregated pay-per-call gateway that routes AI-agent tool requests across 2,000+ capabilities, paid per call in USDC via x402 with no signup or API key required

Acts as a unified gateway aggregating 2,000+ x402 services and built-in tools, callable per-use in USDC with no signup or API key required.

Looks up geolocation and metadata for a given IPv4 or IPv6 address, payable per-call via x402 in USDC with no account or API key required.

Returns psychological effects data and analysis for a given query, paid per-call via x402 micropayment with no account required.

Returns data and analysis on psychological biases, with payment handled inline per call via x402 protocol

Returns data and analysis about psychological heuristics, paid per-call via x402 with no account required

Downloads a ZIP file binary via a pay-per-call GET request using x402 USDC micropayments on Base, no API key required.

Evaluates an API endpoint's agent card and assesses its readiness for agent-to-agent (A2A) protocol compatibility

Marks or features a specific service listing in the ToolVet vetted API/MCP directory

Returns a prepaid M2M session desk pack for high-volume autonomous agent callers, providing session status and desk-level context at 40 calls per 24-hour window.

Retrieves a snapshot of Pearl L1 network telemetry including RPC node status, community node map, and poll history

Sorts up to 200 training attendance records numerically by a chosen field (attendees or completions) and returns the ordered rows.