All Services

Runs three analytical reports on supplied business website inventory records: a record quality audit, exact row deduplication, and numeric distribution analysis for page_count and verified_pages fields.

Runs three analytical reports on business website inventory records: a record quality audit, exact row deduplication, and a trailing mean time series, all computed locally without external lookups.

Runs a record quality audit and a grouped numeric summary on up to 200 rows of business website inventory data (page_count, verified_pages), producing two analytical reports without any live lookup or external action.

Runs two local analytical reports on supplied business website inventory records: a record quality audit and IQR-based outlier detection on page_count or verified_pages fields.

Runs two local analytical reports (record quality audit and numeric distribution) on up to 200 business website inventory rows, covering page_count and verified_pages fields.

Runs a record quality audit and computes a secondary-measure weighted mean on up to 200 rows of business website inventory data (page_count, verified_pages), returning two analytical reports.

Runs three local analytical reports (record quality audit, string normalisation, and base-100 index series) on up to 200 rows of business website inventory data containing page_count and verified_pages fields.

Runs three analytical reports (record quality audit, string normalisation, and category frequencies) on up to 200 business website inventory rows containing page_count and verified_pages fields.

Runs three local analytical reports on supplied business website inventory records: a record quality audit, string normalisation, and a date-by-category pivot, for up to 200 rows of page_count and verified_pages data.

Runs three local analytical reports (record quality audit, string normalisation, and duplicate key detection) on up to 200 rows of business website inventory data containing page_count and verified_pages fields.

Runs three local analytical reports (record quality audit, string normalisation, and equal-width histogram) on up to 200 rows of business website inventory data (page_count, verified_pages) for $0.01 USDC.

Audits record quality, normalises strings, and identifies exact duplicate rows in business website inventory data (page_count, verified_pages) for up to 200 rows, producing 3 independent analytical reports.

Audits record quality, normalises strings, and fills missing values for business website inventory data (page_count, verified_pages) across up to 200 rows, returning 3 independent analytical reports.

Runs three local analytical reports on up to 200 business website inventory rows: a record quality audit, string normalisation, and grouped numeric summary for page_count or verified_pages.

Runs three local analytical reports on supplied business website inventory records (page_count, verified_pages): a record quality audit, string normalisation, and keyed dataset comparison against a second dataset — up to 200 rows, no external lookups.

Runs three analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of business website inventory data containing page_count and verified_pages fields.

Audits record quality, normalises strings, and filters by numeric interval for business website inventory data (page_count, verified_pages) across up to 200 rows, returning 3 independent analytical reports.

Computes a secondary-measure weighted mean and a date-by-category pivot table for up to 200 business website inventory records (page_count, verified_pages).

Normalises company group strings and computes daily sum series for business website inventory metrics (page_count, verified_pages) across up to 200 supplied rows.

Normalises string fields and pivots a numeric field by date and company category for up to 200 business website inventory rows, returning two analytical reports.

Runs two local analytical reports (string normalisation and duplicate key detection) on supplied business website inventory records containing page_count and verified_pages fields, for up to 200 rows.

Runs string normalisation and equal-width histogram analysis on up to 200 business website inventory records, producing two analytical reports for page_count or verified_pages fields.

Normalises string fields and flags IQR-based outliers for business website inventory records (page_count, verified_pages) across up to 200 rows, producing two analytical reports.

Computes trailing moving-average series and adjacent row-to-row changes for business website inventory metrics (page_count, verified_pages) on up to 200 supplied records.

Computes trailing mean time series and base-100 index series for business website inventory metrics (page_count, verified_pages) from supplied row data.

Computes a trailing mean time series and fills missing values in business website inventory data (page_count, verified_pages) for up to 200 rows, returning 2 analytical reports.

Computes trailing mean time series and keyed dataset comparison reports for business website inventory records (page_count, verified_pages) across up to 200 rows.

Computes Pearson/rank correlation between page_count and verified_pages, and performs a keyed comparison between two supplied business website inventory datasets, returning two analytical reports for up to 200 rows.

Analyzes a webpage or HTML snippet to compute the frequency of adjacent word pairs (bigrams) found in button labels.

Scans a webpage or HTML snippet to find button elements that share a duplicate value for a specified attribute, filtered by a search term and a reference value.

Scans a web page or HTML snippet for button elements and reports duplicate values found in a specified attribute, optionally comparing against previously known values.

Statically parses a webpage or HTML snippet to report button elements whose specified attribute has an empty value.

Detects invisible Unicode characters in button label text on a webpage or supplied HTML, flagged by element attribute matching.

Finds button elements on a webpage whose specified HTML attribute value literally matches a given search term, returning matched button labels.

Extracts button labels from a webpage or HTML snippet and compares them against a supplied set of previous text values to identify changes

Extracts context excerpts surrounding a specified term from button labels on a given web page or HTML document.

Ranks button label texts by character length from a webpage or supplied HTML, optionally filtered by a search term and element attribute.

Counts word frequency within button label text on a given webpage or HTML snippet, optionally filtered by a specific term and button attribute.

Continuously monitors a token for security changes over 24 hours and alerts on suspicious or dangerous state transitions in real time

Executes a pre-defined automated trading strategy on behalf of the user

Returns a paid AI-generated decision procedure brief helping agents determine whether a credit pricing offer in an x402 marketplace is honest and worth accepting

Returns an LLM-generated decision procedure covering buyer-side x402 trust composites: withdrawal-latency indexing, telco-rail dispute resolution, and refund-oracle verification for agent payments.

Computes a Base-100 rebased price index for buy-X-get-Y-free retail promotion scenarios across up to 200 merchandise rows, normalizing all values relative to a chosen baseline record.

Computes and compares the effective merchandise total under a Buy-X-get-Y-free promotion for two scenarios (before and after), showing the impact of changed pricing or basket parameters.

Computes a distribution histogram of Buy-X-get-Y-free promotional merchandise totals across up to 200 retail basket records, grouped into configurable bins.

Detects IQR-based statistical outliers in Buy-X-get-Y-free promotional merchandise totals across up to 200 retail records.

Compares named retail pricing scenarios for buy-X-get-Y-free promotions, calculating merchandise totals across a baseline and up to 20 labeled override scenarios.

Generates a one-input sensitivity table showing how a Buy-X-get-Y-free deal's merchandise total changes as one pricing variable is varied across supplied values.

Computes and attributes the change in Buy-X-Get-Y-Free promotional merchandise totals between two sets of retail parameters, showing which input changes drove the difference.

Calculates the gap between a target revenue figure and the actual merchandise total under a buy-X-get-Y-free promotional pricing structure.

Classifies buy-X-get-Y-free retail basket totals against a numeric threshold range, returning a bounded classification report for up to 200 records.

Generates a two-dimensional scenario grid showing effective merchandise totals under buy-X-get-Y-free pricing across combinations of two variable inputs

Parses a list of CAA DNS record strings and extracts the authorized certificate authority hostnames from them.

Computes adjacent (period-over-period) row changes for cache hit/miss observation data, returning a bounded descriptive analytics report for up to 200 records.

Computes a base-100 indexed series for cache hit or miss observations across up to 200 dated records, enabling normalized trend comparison anchored to a chosen baseline row.

Computes category-frequency counts across cache observation records (hits/misses by cache group and date) for up to 200 rows of typed input data.

Computes daily sum totals (hits or misses) across cache observation records, grouped by date, for up to 200 input rows.

Pivots up to 200 cache observation records (hits/misses) by date and cache category, returning a local descriptive analytics summary table.

Computes an equal-width histogram over cache hit or miss counts from up to 200 typed cache observation records, returning a local descriptive analytics report.

Removes duplicate rows from a batch of cache observation records (hits/misses by date and cache group) and returns a deduplication report.

Fills missing numeric values (hits or misses) in up to 200 cache observation records using zero, mean, or median imputation, returning a local descriptive analytics report.

Computes grouped descriptive statistics (numeric summary) for cache hit/miss observations, grouped by cache name, from up to 200 supplied records.

Compares two keyed datasets of cache hit/miss observations (up to 200 rows each) and returns local descriptive analytics highlighting differences between the two groups.

Filters cache observation records (hits/misses) to only those rows where a specified numeric field falls within a given minimum-maximum range, returning local descriptive analytics on up to 200 records.

Audits the data quality of up to 200 cache observation records (hits, misses, date, cache group) and returns a local descriptive analytics report.

Finds available calendar time slots for scheduling meetings or appointments given scheduling constraints

Maps a probability value to a discrete bucket index given a specified number of bins, useful for histogram-style binning in agent pipelines.

Computes period-over-period adjacent row changes for call centre metrics (calls or wait_seconds) across up to 200 input records

Converts up to 200 call centre records (calls volume or wait time) into a base-100 indexed time series, normalised against a chosen reference row, computed entirely on-device with no external enrichment.

Computes category frequencies (counts per team/date group) for up to 200 call centre records supplied by the caller

Compares two keyed datasets of call centre records (calls and wait times) row-by-row and returns numeric difference and data-quality analysis.

Computes a numeric distribution (e.g. histogram/frequency breakdown) over call centre data fields such as call counts or wait seconds, for up to 200 records.

Filters call centre records (calls or wait_seconds) to only return rows whose numeric field value falls within a specified minimum–maximum interval.

Sorts up to 200 call centre records by a specified numeric field (calls or wait_seconds) and returns them in ordered sequence.

Validates and audits data quality of up to 200 call centre records (team, date, calls, wait_seconds) using local numeric and data-quality checks

Computes a secondary-measure weighted mean for call centre records, weighting one numeric field (e.g. wait_seconds) by another (e.g. calls) across up to 200 supplied rows.

Returns trending momentum social data for tokens or topics, delivered pay-per-use via x402 blockchain micropayment.

Returns a list of EVM liquidity pool clone data (v3) for blockchain analytics and autonomous agent consumption.

Fetches data about Alien V3 liquidity pools on EVM-compatible blockchains, payable per-call in USDC via x402.

Computes adjacent row changes and a base-100 index series for camera coverage data (shot_count or coverage_seconds) across up to 200 rows.

Analyzes camera coverage records (shot_count, coverage_seconds) by computing adjacent row changes and flagging IQR-based outliers, returning two independent analytical reports for up to 200 rows.

Runs two analytical reports on camera coverage data — a Base-100 indexed time series and a date-by-category pivot table — for up to 200 supplied rows of shot_count or coverage_seconds data.

Generates a Base-100 index series and an equal-width histogram for supplied camera coverage records (shot_count or coverage_seconds) across up to 200 rows.

Computes a base-100 index series and fills missing values for camera coverage records (shot_count or coverage_seconds) across up to 200 rows.

Computes Base-100 indexed time series and IQR-based outlier flags for camera coverage records (shot_count or coverage_seconds) across up to 200 rows, producing two analytical reports.

Computes a Base-100 index series and a two-measure correlation report for supplied camera coverage data (shot_count and coverage_seconds) over up to 200 rows.

Analyzes up to 200 camera coverage records to produce two local analytical reports: category frequency distribution by asset group and adjacent row changes for shot_count or coverage_seconds.

Computes category frequency distributions and a base-100 indexed series for camera coverage records (shot_count or coverage_seconds) from up to 200 supplied rows.

Computes category frequency distributions and daily sum time series for camera coverage records (shot_count or coverage_seconds) from up to 200 supplied rows.

Analyzes supplied camera coverage records to produce two reports: category frequency counts by asset group and a date-by-category pivot table for shot_count or coverage_seconds metrics.

Analyzes camera coverage records (shot_count and coverage_seconds) by generating category frequency counts per asset group and an equal-width histogram distribution — two statistical reports in a single call.

Analyzes camera coverage records by computing category frequencies for asset groups and filtering numeric fields (shot_count or coverage_seconds) by a specified numeric interval, returning two analytical reports for up to 200 rows.

Computes category frequencies and a secondary-measure weighted mean for camera coverage records (shot_count, coverage_seconds) across up to 200 rows, returning two independent analytical reports.

Computes category-frequency distributions and trailing moving-average series for camera coverage records (shot_count or coverage_seconds) over up to 200 rows using local analytical engines.

Computes daily sum time series and adjacent row-over-row changes for camera coverage data (shot_count or coverage_seconds) across up to 200 supplied rows.

Computes two analytical reports — a daily sum series and a base-100 indexed series — from supplied camera coverage data (shot counts and coverage seconds).

Computes two analytical reports on camera coverage data: a daily sum time series and a date-by-category pivot table, for up to 200 rows of shot_count or coverage_seconds data.

Computes a daily sum time series and an equal-width histogram for camera coverage metrics (shot_count or coverage_seconds) from user-supplied records.

Computes daily sum time series for camera coverage metrics (shot_count or coverage_seconds) and explicitly fills missing values using a chosen strategy (zero, mean, or median)

Computes daily sum time series and IQR-based outlier flags for camera coverage records (shot_count or coverage_seconds) across asset groups.