All Services

Computes numeric distribution and secondary-measure weighted mean for savings ledger records (deposit_amount, withdrawal_amount) across up to 200 rows, returning two analytical reports.

Filters savings ledger rows by a numeric range on deposit or withdrawal amounts, and computes adjacent-row changes, returning two analytical reports for up to 200 supplied rows.

Filters savings ledger rows by a numeric interval on deposit or withdrawal amounts, and compares two datasets row-by-row using shared keys, returning up to 2 analytical reports for up to 200 rows.

Filters savings ledger rows by a numeric interval on deposit or withdrawal amounts, and computes a trailing moving-average series over the same field, returning both reports in one call.

Analyzes up to 200 savings ledger rows (deposit_amount, withdrawal_amount) producing two reports: numerically ordered rows and a date-by-category pivot table.

Sorts savings ledger rows by a chosen numeric field and computes an equal-width histogram over deposit or withdrawal amounts for up to 200 rows.

Sorts savings ledger rows numerically and fills missing deposit_amount or withdrawal_amount values using zero, mean, or median imputation — returns two analytical reports for up to 200 rows.

Sorts savings ledger rows by a numeric field and compares two keyed datasets of savings ledger records, returning two analytical reports per call.

Computes numeric row ordering (rank) and secondary-measure weighted mean on savings ledger records (deposit_amount, withdrawal_amount) for up to 200 rows, returning two analytical reports.

Computes numeric row ordering and a trailing mean series for savings ledger records (deposit_amount or withdrawal_amount) across up to 200 rows, returning two analytical reports.

Audits data quality and produces grouped numeric summaries for savings ledger records containing deposit and withdrawal amounts (up to 200 rows, 2 reports per call).

Runs two local analytical reports on savings ledger rows: a data quality audit and a keyed comparison between two supplied datasets, covering deposit and withdrawal amounts.

Runs two local analytical reports on savings ledger rows: a record quality audit and a numeric distribution analysis for deposit_amount or withdrawal_amount fields (up to 200 rows).

Audits data quality and filters savings ledger rows (deposit_amount, withdrawal_amount) by a numeric interval, returning two analytical reports for up to 200 rows.

Audits data quality of savings ledger records and computes a weighted mean on a chosen numeric field (deposit_amount or withdrawal_amount) across up to 200 rows.

Runs three analytical reports on savings ledger rows: a record quality audit, string normalisation, and a base-100 indexed series for deposit or withdrawal amounts.

Audits record quality, normalises strings, and computes daily sum series for savings ledger rows (deposit_amount or withdrawal_amount) across up to 200 rows, producing 3 independent analytical reports.

Audits data quality, normalises strings, and filters by numeric interval for savings ledger records with deposit and withdrawal amounts — up to 200 rows, 3 reports in one call.

Audits record quality, normalises strings, and numerically orders rows in savings ledger data (deposit_amount, withdrawal_amount) for up to 200 rows, returning 3 independent analytical reports.

Runs three bundled analytical reports on savings ledger rows (deposit_amount, withdrawal_amount): record quality audit, string normalisation, and two-measure correlation — all locally, no external calls.

Computes a secondary-measure weighted mean and a date-by-category pivot table for savings ledger records (deposit_amount, withdrawal_amount) — two local analytical reports in one call.

Computes a secondary-measure weighted mean and fills missing values in savings ledger records (deposit_amount, withdrawal_amount) for up to 200 rows, returning 2 analytical reports.

Runs two local analytical reports on savings ledger rows: string normalisation and category frequency counts for instrument groups, deposits, and withdrawals.

Runs string normalisation and daily sum series analysis on up to 200 savings ledger rows (deposit_amount, withdrawal_amount) using local analytical engines.

Performs string normalisation and a date-by-category pivot analysis on up to 200 savings ledger rows (deposit_amount or withdrawal_amount), returning two analytical reports.

Normalises strings and fills missing values (zero, mean, or median) in savings ledger records containing deposit and withdrawal amounts, returning two analytical reports for up to 200 rows.

Runs two local analytical reports on savings ledger rows: string normalisation of text fields and a grouped numeric summary of deposit/withdrawal amounts, for up to 200 rows.

Normalises strings and performs keyed dataset comparison on two sets of savings ledger records (deposit_amount, withdrawal_amount), returning two independent analytical reports for up to 200 rows each.

Computes string normalisation and secondary-measure weighted mean analytics on savings ledger rows (deposit_amount, withdrawal_amount) — up to 200 rows, two reports per call.

Runs two local analytical reports on savings ledger rows: string normalisation of categorical fields and a trailing moving-average series for deposit or withdrawal amounts.

Computes a trailing moving average series and a Pearson correlation between deposit_amount and withdrawal_amount for up to 200 savings ledger rows, returning two analytical reports.

Runs two local analytical reports on savings ledger data: a Pearson/rank correlation between deposit_amount and withdrawal_amount, and a date-by-instrument-group pivot table, for up to 200 rows.

Returns a structured accessibility remediation guide covering web and domain accessibility best practices and fixes

Returns a knowledge base article explaining how to map a new custom URL in Google Sites under Web & Domains settings

Retrieves a structured knowledge-base article on AI agent observability best practices and patterns

Returns a troubleshooting guide for diagnosing and resolving NVIDIA GPU no-signal display issues on Linux systems

Returns a knowledge base article explaining how to resolve issues when adding a domain on Google (e.g., Google Workspace or Google Search Console)

Returns a knowledge-base article covering security and operational security (OpSec) best practices for AI agents handling secrets

Retrieves a knowledge base article about AI agent sandboxing and untrusted code execution concepts and practices

Retrieves a knowledge-base article on AI agent memory and state integrity best practices from the Saylor Innovations guide library.

Retrieves the agent capability registry and discovery guide for AI agents and agentic workflows from Saylor Innovations' knowledge base.

Returns a knowledge-base article describing the scope and pricing of productized business and operations services

Retrieves AI agent evaluation and test case content from a curated knowledge base library

Returns a knowledge base article explaining how to customize a custom web address for Google Workspace domains

Returns AI agent and automation guidance content on data cleanup techniques and schema mapping strategies

Retrieves a knowledge base guide article on AI-driven entity resolution and deduplication techniques for AI agents

Retrieves verified research evidence entries related to AI and agents from a curated knowledge base library

Returns a knowledge base article covering backup and restore drill procedures for self-hosting and infrastructure management.

Returns a guide for auditing and improving the quality of lead lists for content and growth purposes

Validates on-chain and DeFi whale signals by retrieving curated knowledge base guidance on interpreting large-wallet activity

Scrapes a target HTTPS URL and returns clean LLM-ready Markdown or plain text content with bot-protection detection

Registers a completed Solana deposit transaction to create an authenticated session with credits for code security scanning

Purchases a pack of 5 hints/undos for the Rum Bottle Sort mobile puzzle game via x402 micropayment on Base.

Sends a tip of any USDC amount to the Kitten Boarding Party game via x402 micropayment on Base.

Grants the player one extra life (continue) in the SCDO Rocket game for 1 USDC, processed via x402 payment on Base.

Purchases a pack of 5 hints/undos for the Paw Crate Clear puzzle game, charged at 1 USDC via x402 on Base.

Sends a tip of any USDC amount to the Treasure Trio game on scdoscan.io, processed via x402 payment protocol on Base.

Send a 2 USDC tip to Capt. Whiskers, the pirate cat character on scdoscan.io, via the x402 payment protocol on Base.

Computes adjacent row-over-row changes and a Base-100 index series for scene geometry metrics (object_count, triangle_count) across up to 200 supplied rows.

Runs two analytical reports on scene geometry data (object_count, triangle_count): adjacent row change detection and a date-by-category pivot table, for up to 200 rows.

Analyzes scene geometry records (object_count, triangle_count) by computing adjacent row changes and comparing two keyed datasets, returning two analytical reports for up to 200 rows.

Computes adjacent row changes and secondary-measure weighted mean statistics for scene geometry records (object_count, triangle_count) supplied by the caller.

Analyzes scene geometry records (object_count, triangle_count) to compute adjacent row changes and two-measure correlation across up to 200 rows.

Computes a Base-100 indexed time series and an equal-width histogram for scene geometry metrics (object_count or triangle_count) across up to 200 supplied rows.

Computes a base-100 index series and a secondary-measure weighted mean for supplied scene geometry records (object_count, triangle_count) across up to 200 rows.

Computes category frequencies and a base-100 index series for supplied scene geometry records (object_count, triangle_count) — up to 200 rows, two analytical reports per call.

Runs two analytical reports on scene geometry records: category frequency distribution and keyed dataset comparison between two supplied datasets, covering up to 200 rows each.

Analyzes scene geometry records (up to 200 rows) to produce category frequency counts by asset group and a numeric interval filter report for object_count or triangle_count fields.

Computes category-frequency distributions and a secondary-measure weighted mean for up to 200 scene geometry records containing object_count and triangle_count fields.

Computes category-frequency distributions and Pearson/rank correlation between object_count and triangle_count for supplied scene geometry records, returning two analytical reports for up to 200 rows.

Computes daily sum time series and adjacent row changes for scene geometry metrics (object_count, triangle_count) across up to 200 supplied records.

Computes daily sum time series and a date-by-category pivot table for scene geometry records (object_count or triangle_count) from up to 200 supplied rows.

Computes daily sum time series and secondary-measure weighted mean analytics for scene geometry data (object_count, triangle_count) from up to 200 supplied rows.

Computes daily sum time series and Pearson/two-measure correlation for scene geometry data (object_count and triangle_count) supplied by the caller, up to 200 rows.

Analyzes supplied scene geometry records (object_count, triangle_count) to produce a duplicate key report and an adjacent row changes report for up to 200 rows.

Runs two local analytical reports on scene geometry records: a duplicate key report and a base-100 index series for object_count or triangle_count across up to 200 rows.

Analyzes up to 200 scene geometry records to produce a duplicate key report and category frequency breakdown for object_count and triangle_count fields.

Analyzes scene geometry records (object_count, triangle_count) to produce a duplicate key report and an equal-width histogram for up to 200 rows.

Analyzes supplied scene geometry records (object_count, triangle_count) to produce a duplicate key report and a grouped numeric summary, up to 200 rows.

Runs a duplicate key report and a keyed dataset comparison on two supplied sets of scene geometry records (object_count, triangle_count) for up to 200 rows each.

Generates equal-width histogram bins and fills missing values for scene geometry data (object_count, triangle_count) across up to 200 rows.

Deduplicates scene geometry rows and generates a Base-100 index series for object_count or triangle_count across up to 200 supplied records.

Deduplicates scene geometry records and fills missing object_count or triangle_count values using zero, mean, or median imputation, producing two analytical reports for up to 200 rows.

Deduplicates scene geometry rows exactly and produces a grouped numeric summary for object_count or triangle_count fields across up to 200 records.

Deduplicates exact rows and flags IQR-based outliers in scene geometry records containing object_count and triangle_count fields, returning two analytical reports for up to 200 rows.

Deduplicates scene geometry rows and computes numeric distribution statistics for object_count or triangle_count fields across up to 200 records.

Deduplicates scene geometry rows and filters records by a numeric interval on object_count or triangle_count, returning up to 2 analytical reports for up to 200 rows.

Deduplicates exact rows and computes a trailing mean time series for scene geometry records containing object_count and triangle_count fields.

Deduplicates scene geometry rows and computes correlation between object_count and triangle_count across up to 200 supplied records.

Analyzes scene geometry records by computing a grouped numeric summary and adjacent row changes for object_count or triangle_count fields across up to 200 rows.

Computes a grouped numeric summary and a base-100 indexed series for scene geometry records (object_count, triangle_count) across up to 200 rows.

Computes grouped numeric summaries and a two-measure correlation report for scene geometry data (object_count and triangle_count) across up to 200 supplied rows.

Runs two local statistical reports on scene geometry rows: IQR-based outlier detection and a secondary-measure weighted mean, for object_count and triangle_count data.

Compares two keyed scene geometry datasets (object_count, triangle_count) row-by-row and fills explicit missing values, producing two analytical reports for up to 200 rows.

Computes numeric distribution statistics and row ordering reports for scene geometry data (object_count, triangle_count) across up to 200 supplied rows, producing two independent analytical reports per call.

Computes numeric distribution statistics and a secondary-measure weighted mean for scene geometry records (object_count, triangle_count) across up to 200 supplied rows.

Computes numeric distribution statistics and two-measure correlation between object_count and triangle_count for up to 200 scene geometry records.

Filters scene geometry rows (object_count, triangle_count) by a numeric interval and reports adjacent row changes across up to 200 supplied rows in two combined analytical reports.

Filters scene geometry rows (object_count, triangle_count) by a numeric interval and pivots dates by asset_group category, producing 2 analytical reports from supplied data.

Filters scene geometry records (object_count, triangle_count) by a numeric interval and generates an equal-width histogram, returning two analytical reports for up to 200 rows.