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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.

Audits a research note document to verify all required sections are present, using deterministic template-based processing.

Extracts and identifies named sections from a research note document supplied as Markdown or plain text

Applies a structured section template to supplied Markdown or plain text content for a research note document

Scans a supplied research note document and returns coverage analysis for specified terms across the document's sections.

Computes word frequencies from a supplied research note in Markdown or plain text format, up to 20,000 characters.

Searches for public research papers and institutional summaries relevant to the consulting domain using live DuckDuckGo results

Searches and retrieves public research papers and institutional summaries focused on procurement topics using live DuckDuckGo results

Searches DuckDuckGo live results to find public research papers and institutional summaries tailored for research teams.

Searches for public research papers and institutional summaries focused on small business topics using live DuckDuckGo results

Computes category-frequency counts for research sample recovery records, breaking down specimen groups across up to 200 input rows with no enrichment or forecasting.

Aggregates up to 200 research sample recovery records into a daily sum time series for either input mass or recovered mass, returning local descriptive analytics with no enrichment or forecast.

Generates a date-by-category pivot report for research sample recovery data, summarizing input and recovered mass across specimen types and dates.

Identifies duplicate row keys in a batch of up to 200 research sample recovery records, returning a local descriptive analytics report with no enrichment or forecasting.

Generates a bounded equal-width histogram report for research sample recovery data (input mass vs recovered mass) across up to 200 typed records.

Removes exact duplicate rows from research sample recovery datasets (up to 200 typed records) and returns a local deduplication report with descriptive analytics.

Fills missing numeric values (input_mass_g or recovered_mass_g) in up to 200 research sample recovery records using zero, mean, or median imputation.

Computes a grouped descriptive statistics summary (count, mean, min, max, etc.) for research sample recovery mass data, grouped by specimen type.

Applies interquartile range (IQR) outlier detection to research sample recovery mass data, flagging anomalous records among up to 200 supplied specimen rows.

Compares two keyed datasets of research sample recovery records (input mass vs. recovered mass) and returns local descriptive analytics highlighting differences between them.

Computes a local descriptive numeric distribution report for up to 200 research sample recovery records, analyzing either input mass or recovered mass values.

Filters up to 200 research sample recovery records to only those where a chosen numeric field (input_mass_g or recovered_mass_g) falls within a specified minimum–maximum interval, returning local descriptive analytics on the filtered set.

Audits up to 200 research sample recovery records for data quality issues, producing local descriptive analytics without enrichment or forecasting.

Computes a rolling/trailing mean time series for research sample recovery metrics (input mass or recovered mass) over a user-defined window across up to 200 typed records.

Computes adjacent row-over-row changes and a base-100 indexed series for up to 200 research task completion records (completed_tasks and assigned_tasks) using local analytical engines.

Analyzes research task completion records to produce two reports: adjacent row-to-row change analysis and a date-by-category pivot table, for up to 200 rows.

Runs two local analytical reports on research task completion data: adjacent row change detection and equal-width histogram distribution, for up to 200 rows.

Analyzes research task completion data by computing adjacent row changes and flagging IQR-based outliers across completed_tasks and assigned_tasks fields for up to 200 rows.

Analyzes up to 200 rows of research task completion data, producing two reports: adjacent row changes and keyed dataset comparison between two supplied datasets.

Computes adjacent row changes and secondary-measure weighted mean for research task completion data (completed_tasks, assigned_tasks) across up to 200 rows, returning two analytical reports.

Generates two analytical reports (Base-100 index series and a date-by-category pivot) from supplied research task completion data (completed_tasks and assigned_tasks) for up to 200 rows.

Analyzes up to 200 rows of research task completion records (completed_tasks, assigned_tasks) producing two local analytical reports: a Base-100 index series and a keyed dataset comparison.

Computes a Base-100 index series and a secondary-measure weighted mean for research task completion records (completed_tasks, assigned_tasks) from up to 200 supplied rows.

Analyzes research task completion records to produce two reports: category frequency counts by company group and adjacent-row delta changes for completed_tasks or assigned_tasks, for up to 200 rows.

Generates two analytical reports on research task completion data: category-level frequency counts and a base-100 indexed time series, for up to 200 rows.

Generates two analytical reports (category frequencies and date-by-category pivot) from supplied research task completion records, for up to 200 rows.

Generates two local analytical reports — category frequency counts and an equal-width histogram — for research task completion records (completed_tasks and assigned_tasks) supplied by the caller.

Computes category frequency distributions and fills missing values in research task completion data (completed_tasks, assigned_tasks) for up to 200 rows, returning two analytical reports.

Analyzes research task completion records (completed_tasks, assigned_tasks) to produce two reports: category frequency distribution and a keyed row-by-row comparison between two supplied datasets.

Analyzes supplied research task completion records to produce category frequency counts and a numeric interval filter report, processing up to 200 rows in two independent reports.

Analyzes research task completion data by computing category frequencies and a trailing moving-average series for completed_tasks or assigned_tasks across up to 200 rows.

Analyzes research task completion records to produce two reports: category frequency counts by company group and a correlation analysis between completed_tasks and assigned_tasks.

Generates two analytical reports (daily sum time series and adjacent row delta changes) from supplied research task completion data (completed_tasks, assigned_tasks) for up to 200 rows.

Computes a daily sum time series and a base-100 indexed series for supplied research task completion data (completed_tasks and assigned_tasks), producing two analytical reports for up to 200 rows.

Generates two analytical reports from supplied research task completion data: a daily sum time series and a date-by-category pivot table, for up to 200 rows.

Generates a daily sum time series and an equal-width histogram for up to 200 research task completion records (completed_tasks or assigned_tasks), returning two analytical reports per call.

Computes daily sum time series and fills missing values (zero, mean, or median) for research task completion data (completed_tasks, assigned_tasks) across company groups, returning up to 2 analytical reports for up to 200 rows.

Analyzes research task completion records by computing a daily sum time series and comparing two keyed datasets side-by-side, returning two analytical reports for up to 200 rows.

Computes a daily sum time series and a trailing moving average series for supplied research task completion records (completed_tasks or assigned_tasks), up to 200 rows.

Generates two analytical reports on research task completion data: a date-by-category pivot table and a keyed dataset comparison, for up to 200 rows.

Analyzes up to 200 rows of research task completion data to produce two reports: a duplicate key detection report and a base-100 indexed time series for completed_tasks or assigned_tasks.

Analyzes up to 200 research task completion records to produce a duplicate key report and an equal-width histogram for completed_tasks or assigned_tasks fields.

Analyzes up to 200 research task completion records to identify duplicate keys and fill missing values using zero, mean, or median imputation, returning two independent analytical reports.

Analyzes up to 200 research task completion records to produce a duplicate key report and a grouped numeric summary for completed_tasks or assigned_tasks.

Analyzes up to 200 research task completion records to produce a duplicate key report and IQR-based outlier flags for completed_tasks or assigned_tasks fields.

Analyzes up to 200 research task completion records to produce two reports: a duplicate key detection report and a keyed comparison between two supplied datasets.

Generates two local analytical reports on research task completion data: a duplicate key detection report and a numeric interval filter for completed_tasks or assigned_tasks values.

Analyzes up to 200 research task completion records to produce a duplicate key report and a numeric row ordering report for completed_tasks or assigned_tasks fields.

Generates two analytical reports from research task completion data: a duplicate key report and a secondary-measure weighted mean, for up to 200 rows.

Analyzes up to 200 research task completion records to produce a duplicate key report and a trailing mean series for a chosen metric field.

Analyzes up to 200 rows of research task completion records to produce two reports: a duplicate key report and a Pearson/Spearman correlation between completed_tasks and assigned_tasks.