All Services

Runs two local analytical reports on sampling observation rows: a record quality audit and a Base-100 index series, for up to 200 rows of sample_value/sample_weight data.

Runs two local analytical reports on up to 200 sampling observation rows: a record quality audit and a date-by-category pivot table, for sample_value or sample_weight.

Runs two independent analytical reports (record quality audit and duplicate key detection) on up to 200 sampling observation rows containing sample_value and sample_weight fields.

Runs two local analytical reports on up to 200 sampling observation rows: a data quality audit and a numeric row ordering, covering sample_value and sample_weight fields.

Runs two local analytical reports on user-supplied sampling observation rows: a data quality audit and a sample_weight-based weighted mean calculation.

Audits data quality and normalises strings in sampling observation records (sample_value, sample_weight) for up to 200 rows, producing two independent analytical reports.

Runs three local analytical reports on supplied sampling observation rows: a record quality audit, string normalisation, and a secondary-measure weighted mean calculation.

Runs three local analytical reports on sampling observation records — a data quality audit, string normalisation, and correlation between sample_value and sample_weight — for up to 200 rows in a single call.

Runs two analytical reports on up to 200 sampling observation rows: a record quality audit and a trailing mean series computation over sample_value or sample_weight.

Runs a record quality audit and a two-measure correlation analysis on up to 200 sampling observation rows (sample_value, sample_weight), returning two independent analytical reports.

Computes a secondary-measure weighted mean and a date-by-category pivot table from supplied sampling observation records in a single paid call.

Performs string normalisation and category frequency analysis on up to 200 sampling observation records (sample_value, sample_weight) in a single call.

Runs two local analytical reports on sampling observation records: string normalisation of text fields and duplicate key detection, for up to 200 rows.

Performs string normalisation and grouped numeric summary analysis on up to 200 sampling observation records (sample_value, sample_weight) in two independent analytical reports.

Runs string normalisation and keyed dataset comparison analytics on up to 200 sampling observation rows (sample_value, sample_weight) across two supplied datasets, returning 2 local reports.

Normalises string fields and filters sampling observation rows (sample_value or sample_weight) within a specified numeric interval, producing 2 analytical reports for up to 200 rows.

Computes string normalisation and trailing mean series analytics on up to 200 rows of weighted sampling observation records, returning 2 reports per call.

Performs string normalisation and two-measure correlation analysis on up to 200 sampling observation rows (sample_value, sample_weight), returning two independent analytical reports.

Computes Pearson correlation between two measures and the weighted mean of a secondary measure for up to 200 supplied sampling observation rows.

Generates a versioned localStorage save validation and bounded input replay ES module for a preset maze game configuration (balanced-15-d2), with configurable title, seed, and accent color.

Generates a versioned localStorage save validation and bounded input replay ES module for the braided-19-d2 game preset, with configurable title, seed, and accent color.

Generates a versioned localStorage save validation and bounded input replay ES module with preset braided-19-d4 configuration, customizable title, seed, and accent color.

Generates a reusable versioned localStorage save validation and bounded input replay ES module for the braided-23-d3 maze preset, with configurable title, seed, and accent color.

Generates a versioned localStorage save validation and bounded input replay ES module with preset braided-27-d1 configuration for game development.

Generates a reusable, versioned localStorage save-validation and bounded-input replay ES module for a preset horizontal game configuration (horizontal-11-d1), configurable by title, seed, and accent color.

Generates a versioned localStorage save validation and bounded input replay ES module for the horizontal-11-d4 maze preset, with configurable title, seed, and accent color.

Returns a versioned localStorage save-validation and bounded-input replay ES module with preset horizontal-19-d1 configuration for a browser maze game.

Generates a versioned localStorage save validation and bounded input replay ES module with preset horizontal-19-d3 configuration, customizable by title, seed, and accent color.

Generates a versioned localStorage save validation and bounded input replay ES module with a preset initial save for the open-15-d1 maze preset, configurable by title, seed, and accent color.

Returns a versioned, preset-configured localStorage save validation and bounded input replay ES module for the open-15-d4 maze game preset.

Returns a versioned localStorage save validation and bounded input replay ES module with the vertical-11-d3 preset configuration, customizable title, seed, and accent color.

Returns a versioned localStorage save validation and bounded input replay ES module with preset vertical-15-d3 configuration, customizable by title, seed, and accent color.

Returns a versioned localStorage save-validation and bounded input replay ES module for the vertical-23-d4 preset game configuration, customizable by title, seed, and accent color.

Generates a versioned localStorage save validation and bounded input replay ES module for preset vertical-27-d2, with configurable title, seed, and accent color.

Computes daily sum time series and IQR-based outlier flags for save file metrics (save_kb, write_ms) from supplied records

Deduplicates save file records and produces numeric distribution statistics for save_kb and write_ms fields across up to 200 rows.

Runs two local analytical reports on save-file metrics (save_kb, write_ms): a record quality audit and a daily sum time series, for up to 200 rows.

Normalises string fields and fills missing numeric values (save_kb or write_ms) in up to 200 save-file records, 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.

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.

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.

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

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

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

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

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

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

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.

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

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

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 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

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

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

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

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

Purchases a pack of 5 hints/undos for the Rum Bottle Sort mobile puzzle 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.

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