All Services

Extracts structured content from documents via a paid x402 endpoint, returning JSON-formatted results logged as machine delivery records

Purchases a downloadable offline quote calculator tool (ZIP) that checks fixed-price jobs against cash costs, percentage fees, and target labor allocations, with no subscription required.

Purchases $5 USDC worth of TEST9999 tokens (0x73e564323F7e05e7ca7781946A0707F4Cc296b07) via an x402 payment-gated API call

Computes adjacent row changes and secondary-measure weighted mean analytics for test coverage records (covered_lines, total_lines) across up to 200 rows.

Analyzes test coverage records to produce a duplicate key report and adjacent row change detection report for up to 200 rows.

Generates two analytical reports from test coverage data: a duplicate key report and a date-by-category pivot, for up to 200 rows of covered/total lines data.

Analyzes test coverage records (covered_lines, total_lines) to produce a duplicate key report and IQR-based outlier flags for up to 200 rows.

Analyzes up to 200 test coverage records to produce a duplicate key report and a keyed dataset comparison between two supplied datasets.

Analyzes up to 200 test coverage records to produce a duplicate key report and a trailing mean series for covered_lines or total_lines.

Deduplicates up to 200 test coverage records and computes category-level frequency counts for component and date fields in a single $0.01 USDC call.

Performs exact row deduplication and a date-by-category pivot on supplied test coverage records (covered_lines, total_lines) for up to 200 rows, returning two analytical reports.

Deduplicates exact duplicate rows and flags IQR-based outliers in test coverage records (covered_lines, total_lines) for up to 200 rows, returning 2 independent analytical reports.

Deduplicates test coverage rows and filters by a numeric interval (covered_lines or total_lines) on up to 200 supplied records, returning 2 analytical reports.

Analyzes test coverage records (covered_lines or total_lines) to produce a grouped numeric summary and adjacent row change report for up to 200 rows.

Computes grouped numeric summary statistics and category frequency distributions for test coverage records (covered_lines, total_lines) across up to 200 rows.

Compares two keyed test coverage datasets (covered_lines or total_lines) row-by-row and fills in explicit missing values, returning two analytical reports for up to 200 rows.

Computes numeric distribution statistics and fills missing values for test coverage records (covered_lines, total_lines) across up to 200 rows, returning two analytical reports.

Filters test coverage records by numeric interval and compares two keyed datasets (covered_lines or total_lines) across up to 200 rows using local analytical engines.

Filters test coverage records by a numeric interval on a chosen field and computes a weighted mean of a secondary measure, returning two analytical reports for up to 200 rows.

Analyzes test coverage records by computing numeric row ordering and adjacent row changes for covered_lines or total_lines across up to 200 rows.

Computes numeric row ordering and secondary-measure weighted mean analytics on supplied software test coverage records (covered_lines, total_lines) for up to 200 rows.

Runs two local analytical reports on test coverage records: a record quality audit and a duplicate key detection report, for up to 200 rows of covered_lines/total_lines data.

Runs three analytical reports on test coverage data: a record quality audit, exact row deduplication, and grouped numeric summary of covered/total lines, for up to 200 rows.

Runs three local analytical reports on test coverage data (covered_lines, total_lines): record quality audit, string normalisation, and category frequency analysis — no external lookups or predictions.

Runs three analytical reports on test coverage data (covered_lines, total_lines): a record quality audit, string normalisation, and two-measure correlation — all offline with no external lookups.

Computes a secondary-measure weighted mean and a date-by-category pivot table for supplied test coverage records (covered_lines, total_lines) — two analytical reports in one call.

Analyzes test coverage records by performing string normalization and detecting adjacent row changes across up to 200 rows of covered/total line data.

Normalises component/date strings and computes a Base-100 index series for up to 200 supplied software test coverage records (covered_lines or total_lines).

Normalises string fields and fills missing values for test coverage records (covered_lines, total_lines) across up to 200 rows using local analytical engines.

Applies string normalisation and IQR-based outlier flagging to up to 200 test coverage records (covered_lines or total_lines), returning two independent analytical reports.

Computes two-measure correlation and fills missing values for supplied test coverage records (covered_lines, total_lines) across up to 200 rows.

Validates a CSV of test run import data and reports which rows are blank or empty, up to 1000 rows.

Validates that all record keys in a CSV of test run import data are unique, returning a uniqueness report for up to 1000 rows.

Extracts adjacent word-pair (bigram) frequencies from textarea elements on a web page or supplied HTML, filtered by a specific term and textarea attribute.

Extracts a specific HTML attribute value from textarea elements on a public webpage or supplied HTML, filtered by a search term.

Checks whether a specific HTML attribute (optionally with a given value) is present on textarea elements matching a search term in a web page or supplied HTML.

Scans a webpage or HTML snippet for textarea elements and reports duplicate default values, filtered by a search term and a specific attribute/value pair.

Statically parses an HTML page or supplied HTML string to report which textarea elements have empty default values, filtered by attribute and search term.

Finds textarea elements on a webpage whose specified HTML attribute exactly matches a given value and term, returning bounded match results via static HTML parsing.

Extracts textarea default values from a web page and compares them against a provided set of previously seen texts, filtered by a specific attribute and search term.

Extracts context excerpts surrounding a search term from textarea elements on a given web page, optionally filtered by a specific HTML attribute and value.

Ranks textarea element text by length from a web page or supplied HTML, filtered by a specific attribute and search term.

Extracts and returns text length statistics for textarea elements found in a webpage or supplied HTML, filtered by element attribute and optional search term.

Checks whether an artifact or content is compatible with a recipient's accepted context types by cross-matching a profile against recipient preferences

Performs a web search query and returns results including URLs, titles, and content snippets

Performs a web search and returns the top result pages' titles, URLs, and extracted text content

Analyzes texture baking records by computing adjacent row changes and an equal-width histogram for either bake_seconds or texture_pixels, returning two analytical reports for up to 200 rows.

Computes adjacent row-to-row changes and secondary-measure weighted mean statistics for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.

Computes a Base-100 indexed time series and a date-by-category pivot table for supplied texture baking records (bake_seconds or texture_pixels), returning two analytical reports for up to 200 rows.

Computes a base-100 indexed time series and fills missing values for texture baking records (bake_seconds and texture_pixels) using local analytical engines — no external lookups.

Runs two local analytical reports on texture baking data: a Base-100 indexed time series and a keyed dataset comparison for up to 200 rows of bake_seconds or texture_pixels metrics.

Computes a Base-100 index series and a secondary-measure weighted mean for up to 200 texture baking records (bake_seconds, texture_pixels) using local analytical engines.

Computes category frequency distributions and a base-100 indexed series for supplied texture baking records (bake_seconds or texture_pixels), returning two analytical reports for up to 200 rows.

Analyzes texture baking records to produce category frequency distributions and daily sum time-series reports for bake_seconds or texture_pixels fields.

Computes category frequency distribution and an equal-width histogram for texture baking records (bake_seconds or texture_pixels) across up to 200 rows.

Computes category frequency distributions and IQR-based outlier flags for texture baking records (bake_seconds or texture_pixels) across up to 200 rows.

Computes category frequency distributions and performs keyed row-by-row dataset comparison for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.

Analyzes texture baking records to produce category frequency counts for asset groups and a numeric interval filter report for bake_seconds or texture_pixels, using up to 200 supplied rows.

Computes two analytical reports — a daily sum series and a base-100 index series — over supplied texture baking records (bake_seconds, texture_pixels) for up to 200 rows.

Computes daily sum time series and fills missing values for texture baking records (bake_seconds, texture_pixels) across up to 200 rows, returning two analytical reports.

Computes daily sum time series and performs keyed dataset comparison for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.

Pivots texture baking records by date and asset group category, then fills missing values using a chosen method (zero, mean, or median), returning two analytical reports for up to 200 rows.

Runs two local analytical reports on texture baking data: a date-by-category pivot table and a keyed comparison between two datasets, for up to 200 rows each.

Runs two local analytical reports on texture baking records: a duplicate key detection report and a daily sum time series for a chosen numeric field.

Analyzes supplied texture baking records to produce a duplicate key report and a date-by-category pivot table, up to 200 rows.

Analyzes up to 200 texture baking records to produce a duplicate key report and a numeric distribution report for bake_seconds or texture_pixels fields.

Analyzes supplied texture baking records to produce a duplicate key report and a numeric interval filter report for bake_seconds or texture_pixels fields, up to 200 rows.

Generates a duplicate key report and numeric row ordering analysis for supplied texture baking records (bake_seconds, texture_pixels) — up to 200 rows, two analytical reports per call.

Analyzes supplied texture baking records to produce a duplicate key report and a trailing mean time series for bake_seconds or texture_pixels fields.

Analyzes up to 200 texture baking records to produce a duplicate key report and a Pearson correlation between bake_seconds and texture_pixels using local analytical engines.

Generates two analytical reports for texture baking data: an equal-width histogram for a selected numeric field and a date-by-category pivot table, for up to 200 rows.

Computes an equal-width histogram and a secondary-measure weighted mean for texture baking records (bake_seconds, texture_pixels) over up to 200 rows, returning two analytical reports.

Computes an equal-width histogram and a two-measure correlation report for texture baking records (bake_seconds, texture_pixels) over up to 200 rows.

Deduplicates texture baking records and generates a Base-100 index series for bake_seconds or texture_pixels metrics across up to 200 rows.

Deduplicates exact rows and computes category frequencies for texture baking records (bake_seconds, texture_pixels) — two local analytical reports in one call.

Deduplicates exact duplicate rows and fills missing values in texture baking records (bake_seconds, texture_pixels) for up to 200 rows, returning two analytical reports.

Deduplicates exact rows and performs keyed dataset comparison on supplied texture baking records (bake_seconds, texture_pixels) across two datasets of up to 200 rows each.

Performs exact row deduplication and numeric distribution analysis on up to 200 texture baking records (bake_seconds, texture_pixels) using local analytical engines.

Deduplicates texture baking records and computes a trailing mean time series for bake_seconds or texture_pixels data, returning two analytical reports for up to 200 rows.

Deduplicates texture baking records and computes Pearson correlation between bake_seconds and texture_pixels for up to 200 supplied rows, returning two analytical reports.

Computes grouped numeric summary statistics and adjacent row changes for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.

Computes a grouped numeric summary and a base-100 index series for user-supplied texture baking records (bake_seconds, texture_pixels) using local analytical engines.

Runs two local analytical reports on texture baking records: a grouped numeric summary and a date-by-category pivot for bake_seconds or texture_pixels fields.

Computes grouped numeric statistics and fills missing values for texture baking records (bake_seconds, texture_pixels) across up to 200 rows, returning two analytical reports.

Computes grouped numeric summaries and keyed dataset comparisons for texture baking records (bake_seconds, texture_pixels) across up to 200 rows, returning two analytical reports.

Computes a grouped numeric summary and a secondary-measure weighted mean for texture baking records (bake_seconds, texture_pixels) across up to 200 rows.

Computes a grouped numeric summary and a trailing mean time series for supplied texture baking records (bake_seconds, texture_pixels) across up to 200 rows.

Analyzes supplied texture baking records to produce IQR-based outlier flags and a date-by-category pivot table, delivered as two independent analytical reports.

Analyzes texture baking records to flag IQR-based outliers and compute a secondary-measure weighted mean, delivering two statistical reports for up to 200 rows.

Runs IQR-based outlier detection and Pearson/Spearman correlation analysis on texture baking records (bake_seconds, texture_pixels) for up to 200 rows, returning two independent analytical reports.

Computes a numeric distribution report and a base-100 indexed series for supplied texture baking data (bake_seconds or texture_pixels), up to 200 rows.

Computes numeric distribution statistics and category frequency breakdowns for texture baking records (bake_seconds and texture_pixels fields) from up to 200 supplied rows.

Computes a numeric distribution report and a daily sum time series for texture baking records (bake_seconds or texture_pixels) from up to 200 supplied rows.

Computes a numeric distribution report and a date-by-category pivot table for up to 200 texture baking records (bake_seconds or texture_pixels fields).

Computes numeric distribution statistics and an equal-width histogram for texture baking records (bake_seconds or texture_pixels) across up to 200 rows.

Computes a numeric distribution report and a grouped numeric summary for texture baking records (bake_seconds or texture_pixels) across up to 200 rows.

Computes numeric distribution statistics and IQR-based outlier flags for texture baking records (bake_seconds or texture_pixels) over up to 200 rows, returning two analytical reports.

Analyzes texture baking records by computing numeric distribution statistics and comparing two keyed datasets for bake_seconds or texture_pixels fields, up to 200 rows each.

Computes numeric distribution statistics and two-measure correlation analysis for texture baking records (bake_seconds and texture_pixels) on up to 200 supplied rows.

Filters texture baking records by a numeric interval on a chosen field and computes a weighted mean of a secondary measure, delivering two analytical reports for up to 200 rows.