All Services

Computes how changes in repeat customers and total purchasing customers each contribute to a shift in repeat purchasing customer share, using sequential (waterfall) attribution.

Calculates the weighted mean of repeat purchasing customer share (repeat customers / purchasing customers) across multiple supplied retail data rows using custom weights.

Computes period-over-period changes in the burned token fraction (burned/issued ratio) across a supplied sequence of token supply observations.

Calculates the fraction of burned tokens relative to issued tokens for up to 200 token observations in a single batch request.

Computes and compares the burned token fraction (burned/issued) for two token supply snapshots, returning a before-and-after delta report.

Computes the correlation between the reported burned token fraction (burned/issued ratio) across a series of observations and a set of benchmark values.

Computes a distribution histogram of the burned-token-to-issued-token fraction across a set of supplied token observations.

Computes a statistical distribution summary of the burned-token fraction (burned/issued ratio) across multiple token supply observations.

Computes IQR-based outlier flags for the reported burned token fraction (burned/issued ratio) across a set of token observations

Computes a one-input sensitivity table showing how the reported burned token fraction changes across a range of values for either burned_tokens or issued_tokens, given a baseline token supply snapshot.

Performs ordered trend analysis on reported burned token fraction (burned/issued tokens) across a sequence of supplied observations.

Ranks a batch of token observations by their burned-to-issued fraction (burn rate), using deterministic calculation against caller-supplied data.

Computes a rolling mean of the burned-token fraction (burned_tokens / issued_tokens) over a sliding window across a supplied series of token observations.

Computes how a change in burned or issued token counts affects the reported burned token fraction, using sequential input-change attribution (waterfall analysis).

Calculates the fraction of a token supply that has been reported as burned, given burned and issued token counts.

Calculates the gap between a token project's reported burned-token fraction and a user-specified target fraction, given issued and burned token counts.

Classifies whether a token's burned-to-issued fraction falls within a caller-defined threshold range across a batch of token supply observations.

Generates a deterministic 2D scenario grid showing the reported burned token fraction across varying combinations of burned_tokens and issued_tokens values.

Calculates period-over-period changes in a wallet's reported share of a liquidity pool across consecutive observation rows.

Computes a base-100 rebase index report for one or more liquidity-pool token ownership observations, expressing each row's LP share relative to a selected baseline row.

Calculates each LP holder's reported ownership share (owned_lp_units / total_lp_units) for up to 200 token observations in a single batch call.

Computes a benchmark correlation score for supplied liquidity-token (LP) ownership share observations against provided benchmark values using a deterministic calculation.

Computes a distribution histogram of reported LP token ownership shares from supplied observations, bucketed into configurable bins.

Computes a statistical distribution summary of reported liquidity-token (LP) ownership share across a batch of token observations

Calculates IQR-based outlier flags for a set of liquidity-pool token ownership observations (owned LP units vs. total LP units).

Computes and compares liquidity-pool ownership share percentages across multiple named scenarios against a baseline, returning deterministic results for each labeled scenario.

Computes a one-input sensitivity table showing how reported liquidity-token ownership share varies across a range of input values for either owned_lp_units or total_lp_units.

Ranks a set of liquidity-token ownership observations by computing and ordering LP share percentages from caller-supplied owned and total LP unit counts.

Computes a before-and-after attribution report showing how changes in owned and total LP units shift a liquidity-token ownership share.

Calculates a wallet's proportional ownership share of a liquidity pool given its LP token holdings versus total LP token supply.

Calculates the gap between current LP token ownership share and a specified target threshold, returning a deterministic verdict based on supplied token observations.

Classifies reported liquidity-token (LP) ownership share as below, within, or above caller-defined thresholds, using supplied LP unit observations.

Computes period-over-period changes in the locked LP-token fraction from a sequence of supplied locked and total LP-token observations.

Calculates the fraction of locked LP tokens relative to total LP tokens for multiple token observations in a single batch request.

Computes and compares the locked LP-token fraction for a liquidity pool before and after a change, returning a deterministic ratio report for both snapshots.

Computes a distribution histogram of locked LP-token fractions across a batch of token observations, bucketed into configurable bins.

Computes a rolling mean of the locked LP-token fraction (locked_lp / total_lp) over a sliding window of observations.

Calculates the fraction of LP tokens that are locked given total and locked LP token amounts

Classifies a batch of locked LP-token fraction observations against caller-supplied lower and upper thresholds, returning a deterministic verdict for each row.

Calculates adjacent period-over-period changes in reported locked token supply given a sequence of token supply observations.

Calculates the reported locked token supply percentage for up to 200 token observations in a single batch request.

Computes the Pearson or rank correlation between a time series of reported locked token supply observations and a user-supplied benchmark series.

Computes a statistical distribution summary of reported locked token supply ratios across a batch of token observations.

Detects IQR-based statistical outliers in reported locked token supply observations across a set of token data rows.

Ranks a list of token observations by their locked supply proportion, returning a deterministic record-level ranking report.

Performs sequential input-change attribution (waterfall analysis) on reported locked token supply figures, comparing before/after snapshots to isolate what drove a change.

Calculates the reported locked token supply as a proportion of total tokens given locked and total token counts

Generates a two-dimensional scenario grid computing locked token supply ratios across combinations of locked_tokens and total_tokens values

Computes a weighted arithmetic mean of reported locked token supply observations across multiple token data points.

Calculates period-over-period changes in reported token holder counts across multiple consecutive observation pairs.

Converts a series of current/previous token holder counts into a Base-100 rebased index showing relative holder growth over time

Compares token holder growth rates between two time periods (before and after), computing growth metrics for each period and contrasting them deterministically.

Computes a distribution histogram of token holder growth rates across multiple token observations, binned into configurable intervals.

Computes a statistical distribution summary of reported token holder growth rates across multiple time-period observations

Detects IQR-based statistical outliers in token holder growth data across a batch of supplied observations

Compares multiple named scenarios of token holder growth rates against a baseline using deterministic calculation

Analyzes an ordered series of token holder growth observations to identify trends in holder count changes over time.

Ranks a batch of token holder growth observations by growth rate and returns a deterministic record ranking report.

Computes a sequential input-change attribution (waterfall) report for reported token holder growth, comparing before and after holder count snapshots.

Classifies reported token holder growth values as within or outside a caller-defined threshold range, using a deterministic calculation on supplied observations.

Generates a two-input scenario grid showing token holder growth across combinations of current and previous holder count values

Calculates the weighted arithmetic mean of token holder growth rates across multiple observation rows, using caller-supplied weights.

Calculates period-over-period changes in a token's treasury share ratio across a sequence of supplied observations

Computes a distribution summary of the ratio of treasury tokens to total tokens across a series of token observations, using a deterministic preset calculation.

Detects IQR-based statistical outliers in reported token treasury share ratios across a batch of token observations.

Compares a baseline token treasury share percentage against one or more named override scenarios, returning a deterministic verdict for each labeled scenario.

Computes a one-input sensitivity table for a token's reported treasury share ratio across a range of input values

Analyzes an ordered time series of token treasury share observations to identify trends, returning a deterministic trend analysis report for the supplied data points.

Computes a rolling mean of reported token treasury share (treasury_tokens / total_tokens) over a sliding window across a supplied time series of token observations.

Calculates the treasury share percentage of a token's total supply given treasury token count and total token count

Calculates the gap between a token project's current treasury share percentage and a specified target value using supplied token supply figures.

Computes a grid of token treasury share values across two varying input dimensions (treasury_tokens and total_tokens) for scenario analysis.

Calculates the reported top-holder group share (percentage of circulating supply held by a token group) for multiple token observations in a single batch request.

Computes a statistical benchmark correlation between reported top-holder group share percentages and a set of user-supplied benchmark values across multiple token observations.

Computes a distribution summary report showing the share of circulating supply held by a top-holder group, given supplied token observation rows.

Compares named scenarios for top-holder group share concentration, computing how a token group's ownership percentage shifts under different supply or holding configurations.

Ranks a batch of token observations by the reported top-holder group share (group tokens / circulating tokens), returning a deterministic record ranking for each row.

Generates a reproducible research handoff manifest from supplied public or synthetic artifact contents, dependencies, algorithm version, random seed, and run parameters.

Returns OSV advisory fixed-version boundaries for a given version of the PyPI package 'requests', indicating which versions contain security fixes.

Returns the latest release summary for the 'requests' Python package (or any specified package) from PyPI via a paid x402 endpoint.

Fetches the live recent release history of the 'requests' Python package (or any specified package) from PyPI

Analyzes a zero-revenue AI/API/MCP project URL and returns a sharpened value offer, first paid path, channel plan, checkout script, and 24-hour proof loop to start generating revenue.

Returns three composite AI readiness index scores with historical data for tracking AI adoption and preparedness trends

Generates a concise research report on a given topic via a paid HTTP GET request

Converts comma-separated CSV text into structured JSON records, optimized for research workflows.

Removes duplicate string values from an array while preserving the original order, optimized for research workflows.

Flattens nested JSON objects into dot-separated key paths, optimized for research data workflows.

Converts an array of JSON objects into CSV-formatted text, optimized for research workflows.

Searches the current web for research methodology sources and links tailored specifically for product teams.

Extracts action-marker lines (e.g. TODO items with dates) from a research note document supplied as Markdown or plain text.

Splits a research note (Markdown or plain text) into bounded text chunks of a specified maximum character length using deterministic processing.

Scans a research note document (Markdown or plain text) for duplicate or repeated paragraphs and returns a bounded audit report.

Masks email addresses and phone numbers in research note documents using deterministic pattern matching

Converts Markdown or plain text research note content (up to 20,000 characters) into an escaped HTML preview string using deterministic document templates.

Audits the heading hierarchy of a research note document supplied as Markdown or plain text, returning a structured analysis of heading structure and organization.

Generates a structured heading outline from a research note document supplied as Markdown or plain text, up to 20,000 characters.

Extracts and inventories all HTTP links found in a research note supplied as Markdown or plain text, up to 20,000 characters.

Scans a research note document and inventories all ISO-date patterns found within it, returning a structured list of detected dates.

Analyzes a research note document to produce a length and paragraph profile, including structural metrics on word count, paragraph count, and document layout.

Reorders the recognised sections of a research note document into a canonical sequence using deterministic processing.