All Services

Analyzes a set of search results to evaluate how diverse the underlying sources are, returning a diversity assessment with supporting evidence.

Normalizes and standardizes a JSON-encoded prompt section structure into a canonical, schema-valid format

Audits and analyzes caller-supplied AI search result synthesis data, returning structured analysis with warnings and evidence scope metadata.

Aggregates and summarizes evaluation results from LLM outputs, returning structured analysis JSON with warnings and evidence scope metadata.

Ranks and analyzes metadata for search results using caller-supplied JSON data, returning structured analysis and evidence scope

Normalizes and validates agent execution trace data provided as JSON, returning a structured analysis with warnings and evidence scope.

Ranks search results by recency, analyzing caller-supplied result data to order items from most to least recent.

Compares two or more versions of an LLM prompt to analyze differences, regressions, or improvements across prompt iterations

Returns domain intelligence metadata (SPF, age, registrar, nameservers, resolution status) for a given domain name

Returns the current USD price and 24-hour trading volume for a given token symbol (e.g. USDC).

Returns current prediction market questions, trading volumes, and outcome probabilities for financial and macro events

Returns current foreign exchange rates for multiple currencies relative to a base currency (e.g. USD)

Retrieves decentralized exchange metrics and trading data for tokens or pairs on Base chain

Fetches current gas price data for blockchain transactions, likely on Base or EVM-compatible chains

Discovers available AI agent capabilities and endpoints on the Silverback DeFi platform

Looks up or scores the on-chain reputation of a DeFi agent or wallet address on the Base chain

Proxies the X (Twitter) API v2 endpoint to retrieve public user profile data for the username 'samrags_' via x402 micropayment.

Computes adjacent row-over-row changes and a base-100 indexed series for user-supplied simulation cache records (cache_gb, simulation_seconds) — two analytical reports for up to 200 rows.

Computes adjacent row changes and secondary-measure weighted mean analytics on up to 200 simulation cache records (cache_gb, simulation_seconds) using local analytical engines.

Analyzes simulation cache records by computing adjacent row changes and two-measure correlation between cache_gb and simulation_seconds for up to 200 rows.

Runs two analytical reports on supplied simulation cache records: a Base-100 index series and a keyed dataset comparison, for up to 200 rows across cache_gb and simulation_seconds fields.

Computes a Base-100 index series and a secondary-measure weighted mean for supplied simulation cache records (cache_gb, simulation_seconds) across up to 200 rows.

Computes category frequency distributions and fills missing values (cache_gb or simulation_seconds) using zero, mean, or median imputation for up to 200 simulation cache records.

Computes category frequency distributions and IQR-based outlier flags for simulation cache records (cache_gb and simulation_seconds fields) on up to 200 supplied rows.

Analyzes simulation cache records to produce category frequency counts and numeric row ordering reports for up to 200 rows across asset groups.

Computes a daily sum time series and a two-measure correlation report for supplied simulation cache records (cache_gb, simulation_seconds) — up to 200 rows, two bundled analytical reports.

Pivots simulation cache records (cache_gb, simulation_seconds) by date and asset group category, then fills missing values using zero, mean, or median imputation — returns two analytical reports per call.

Performs two analytical reports on simulation cache data: a date-by-category pivot table and a keyed comparison between two supplied datasets, covering cache_gb and simulation_seconds metrics.

Generates a duplicate key report and a base-100 index series for up to 200 rows of simulation cache data (cache_gb, simulation_seconds).

Analyzes supplied simulation cache records to produce a duplicate key report and category frequency distribution across asset groups.

Analyzes supplied simulation cache records to produce a duplicate key report and a date-by-category pivot table, up to 200 rows, with no external lookups.

Runs two local analytical reports on simulation cache records: a duplicate key report and an equal-width histogram for cache_gb or simulation_seconds fields.

Analyzes supplied simulation cache records to produce a duplicate key report and IQR-based outlier flags for cache_gb or simulation_seconds fields, up to 200 rows.

Analyzes up to 200 rows of simulation cache records (cache_gb, simulation_seconds) to produce two reports: a duplicate key report and a keyed comparison between two supplied datasets.

Analyzes up to 200 simulation cache records to produce a duplicate key report and a numeric distribution report for either cache_gb or simulation_seconds fields.

Analyzes up to 200 simulation cache records to produce a duplicate key report and a numeric interval filter report for cache_gb or simulation_seconds fields.

Analyzes up to 200 simulation cache records to produce two local reports: a duplicate key report and a secondary-measure weighted mean for cache_gb or simulation_seconds fields.

Generates two local analytical reports for simulation cache data: a duplicate key report and a trailing mean series for cache_gb or simulation_seconds fields.

Analyzes up to 200 simulation cache records to produce a duplicate key report and a two-measure Pearson/rank correlation between cache_gb and simulation_seconds.

Computes an equal-width histogram for one field and a secondary-measure weighted mean for simulation cache records (cache_gb, simulation_seconds), returning two analytical reports from supplied data.

Analyzes simulation cache records to identify exact duplicate rows and detect adjacent row changes across cache_gb and simulation_seconds fields, returning two independent analytical reports.

Deduplicates rows and generates a Base-100 indexed time series for simulation cache records (cache_gb, simulation_seconds), producing two analytical reports from supplied data.

Performs exact row deduplication and category frequency analysis on simulation cache records (cache_gb, simulation_seconds) for up to 200 rows, returning two analytical reports.

Deduplicates exact duplicate rows and computes daily sum time series for simulation cache records (cache_gb, simulation_seconds) across up to 200 rows.

Deduplicates simulation cache records by exact row match and produces a date-by-category pivot table for cache_gb or simulation_seconds metrics, across up to 200 supplied rows.

Deduplicates rows and fills missing values (cache_gb or simulation_seconds) in simulation cache datasets using zero, mean, or median imputation — returns two analytical reports for up to 200 rows.

Deduplicates simulation cache records and flags IQR-based outliers across cache_gb and simulation_seconds fields for up to 200 rows.

Deduplicates simulation cache records and compares two keyed datasets of cache_gb and simulation_seconds values, returning two independent analytical reports for up to 200 rows.

Deduplicates simulation cache records and computes numeric distribution statistics for cache_gb or simulation_seconds fields across up to 200 rows.

Deduplicates simulation cache records exactly and filters them by a numeric interval (cache_gb or simulation_seconds), returning two analytical reports for up to 200 rows.

Performs exact row deduplication and trailing mean series analysis on simulation cache records (cache_gb, simulation_seconds) for up to 200 rows.

Deduplicates exact rows and computes correlation between cache_gb and simulation_seconds across up to 200 simulation cache records, returning two analytical reports.

Computes a grouped numeric summary and adjacent row changes report for simulation cache records (cache_gb, simulation_seconds) across up to 200 rows.

Generates two analytical reports — a grouped numeric summary and a daily sum time series — for supplied simulation cache records (cache_gb, simulation_seconds) across up to 200 rows.

Generates a grouped numeric summary report and a numeric interval filter report for simulation cache records (cache_gb, simulation_seconds) across up to 200 rows.

Computes grouped numeric summary statistics and a secondary-measure weighted mean for simulation cache records (cache_gb and simulation_seconds) across up to 200 rows.

Computes a grouped numeric summary and a two-measure correlation report (cache_gb vs simulation_seconds) for up to 200 supplied simulation cache records.

Runs two local analytical reports on simulation cache records: IQR-based outlier detection and explicit missing-value imputation for cache_gb and simulation_seconds fields.

Runs two statistical analyses on simulation cache records: IQR-based outlier detection and keyed dataset comparison, for up to 200 rows of cache_gb and simulation_seconds data.

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

Analyzes simulation cache records to flag IQR-based outliers and compute two-measure correlation between cache_gb and simulation_seconds for up to 200 rows.

Compares two keyed simulation cache datasets (cache_gb, simulation_seconds) side-by-side and fills in missing values, producing two analytical reports for up to 200 rows.

Analyzes simulation cache records by computing numeric distribution statistics and adjacent-row change deltas for cache_gb or simulation_seconds fields across up to 200 supplied rows.

Analyzes user-supplied simulation cache records to produce numeric distribution statistics for cache_gb or simulation_seconds and category frequency counts for asset_group, across up to 200 rows.

Generates two analytical reports (numeric distribution and date-by-category pivot) for user-supplied simulation cache records covering cache_gb and simulation_seconds fields.

Computes numeric distribution statistics and IQR-based outlier flags for simulation cache records (cache_gb and simulation_seconds) across up to 200 supplied rows.

Computes a numeric distribution report and a secondary-measure weighted mean for up to 200 simulation cache records, using cache_gb as the primary field and simulation_seconds as the weighting measure.

Computes numeric distribution statistics and a trailing mean series for cache_gb and simulation_seconds fields across up to 200 simulation cache records.

Filters simulation cache rows by a numeric interval on cache_gb or simulation_seconds, and computes adjacent row changes, returning two analytical reports for up to 200 supplied rows.

Filters simulation cache records by a numeric interval on cache_gb or simulation_seconds, then produces a daily sum time series for up to 200 supplied rows.

Filters simulation cache records by a numeric interval and fills missing values in cache_gb or simulation_seconds using zero, mean, or median imputation, returning up to 2 analytical reports for up to 200 rows.

Applies a numeric interval filter and keyed dataset comparison to simulation cache records (cache_gb, simulation_seconds) for up to 200 rows across two independent analytical reports.

Applies a numeric interval filter and computes a trailing mean series on simulation cache records (cache_gb, simulation_seconds) for up to 200 rows, returning 2 analytical reports.

Filters simulation cache records by a numeric interval on one field and computes the correlation between cache_gb and simulation_seconds across up to 200 supplied rows, returning two analytical reports.

Ranks simulation cache records by a chosen numeric field and computes a base-100 index series for up to 200 supplied rows across cache_gb and simulation_seconds metrics.

Computes numeric row ordering and daily sum series for simulation cache records (cache_gb, simulation_seconds) across up to 200 rows.

Generates two analytical reports on supplied simulation cache data: numeric row ordering and a date-by-category pivot table, for up to 200 rows.

Sorts simulation cache records numerically by row and fills missing cache_gb or simulation_seconds values using zero, mean, or median imputation, delivering two analytical reports for up to 200 rows.

Computes numeric row ordering and trailing mean series for simulation cache records (cache_gb, simulation_seconds) across up to 200 supplied rows.

Runs a record quality audit and category frequency analysis on simulation cache data (cache_gb, simulation_seconds) for up to 200 rows, returning two independent analytical reports.

Runs a record quality audit and daily sum series report on simulation cache data (cache_gb, simulation_seconds) for up to 200 rows, returning two independent analytical reports.

Runs two local analytical reports on simulation cache records: a record quality audit and a date-by-category pivot, for up to 200 rows of cache_gb and simulation_seconds data.

Runs two analytical reports on simulation cache records: a record quality audit and a duplicate key detection report, for up to 200 rows of cache_gb and simulation_seconds data.

Audits record quality and generates an equal-width histogram for simulation cache data (cache_gb and simulation_seconds fields) across up to 200 rows.

Audits data quality and removes exact duplicate rows from supplied simulation cache records (cache_gb, simulation_seconds), producing two independent analytical reports for up to 200 rows.

Runs three local analytical reports on simulation cache data: a record quality audit, exact row deduplication, and a daily sum time series — all from supplied rows, no external lookups.

Runs three local analytical reports on simulation cache records: a record quality audit, exact row deduplication, and numeric distribution analysis for cache_gb and simulation_seconds fields.

Audits record quality, deduplicates exact rows, and filters by numeric interval for simulation cache data (cache_gb, simulation_seconds), returning 3 independent analytical reports for up to 200 rows.

Runs three independent analytical reports on simulation cache records: a data quality audit, exact duplicate detection, and numeric ordering — all against user-supplied rows, with no external data access.

Runs three analytical reports on simulation cache records: a data quality audit, exact row deduplication, and a trailing moving average series for a chosen numeric field.

Runs two analytical reports on simulation cache records: a data quality audit and a grouped numeric summary, for up to 200 rows of cache_gb and simulation_seconds data.

Runs a data quality audit and numeric distribution analysis on simulation cache records (cache_gb, simulation_seconds) for up to 200 rows, returning two independent analytical reports.

Audits data quality and filters by numeric interval for simulation cache records (cache_gb, simulation_seconds) across up to 200 rows, returning two analytical reports.

Audits data quality and computes a weighted mean for a secondary measure across supplied simulation cache records (cache_gb, simulation_seconds) in up to 200 rows.

Runs three analytical reports on simulation cache records: a data quality audit, string normalisation, and a base-100 indexed series for cache_gb or simulation_seconds fields.

Runs three local analytical reports on simulation cache data: a record quality audit, string normalisation, and a date-by-category pivot — all on user-supplied rows, no external lookups.

Audits record quality, normalises strings, and fills missing values for simulation cache datasets (cache_gb, simulation_seconds) — returning 3 independent analytical reports for up to 200 rows.

Runs three local analytical reports on simulation cache records: a data quality audit, string normalisation, and grouped numeric summary — all in one call for up to 200 rows.

Runs three local analytical reports on simulation cache records: a record quality audit, string normalisation, and a keyed comparison between two datasets, for up to 200 rows of cache_gb and simulation_seconds data.

Analyzes simulation cache records (cache_gb, simulation_seconds) with three reports: record quality audit, string normalisation, and numeric distribution — all processed locally on supplied data up to 200 rows.