All Services

Counts and inventories all number tokens (numeric values) found in a meeting notes document supplied as Markdown or plain text.

Generates a paragraph-level change report comparing two versions of meeting notes documents

Extracts and inventories all quoted passages from meeting notes supplied as Markdown or plain text

Checks meeting notes documents (Markdown or plain text) to verify that all required sections are present and accounted for.

Extracts and returns structured sections (e.g. Attendees, Decisions, Actions) from meeting notes provided as Markdown or plain text

Formats supplied meeting notes text into a structured section template with Attendees, Decisions, and Actions sections.

Checks a meeting notes document for coverage of user-supplied terms, returning a deterministic analysis without generative prose.

Normalises whitespace in meeting notes supplied as Markdown or plain text, up to 20,000 characters, using deterministic text processing rules.

Computes word frequency counts from meeting notes provided as Markdown or plain text (up to 20,000 characters)

Compares role-level meeting review requirements against approved, rejected, or unknown declarations to produce a checklist coverage map.

Counts joint absences of decision digest, source-segment, and nonpersonal owner-role labels across meeting records to surface missing metadata patterns.

Compares two sets of meeting segment sequences by matching shared segments and computing content digest differences while preserving relative order, using only offline typed non-personal metadata.

Audits declared decision-parent links in meeting records for missing decisions, cycles, and cross-meeting references.

Compares closed decision metadata between two revisions of meeting records, reporting changes in digest, agenda, source-segment, and owner-role fields.

Computes confidence calibration bins for a meeting topic classifier (planning/progress/decision/review) given up to 200 labelled records with predicted probabilities.

Computes a confusion matrix for meeting topic classification (planning/progress/decision/review) from up to 200 labelled text records

Generates a fixed-holdout learning curve for meeting topic classification (planning/progress/decision/review) using a naive-Bayes baseline on up to 200 labelled text records.

Splits a labelled meeting-topic dataset into grouped train/test partitions using naive-Bayes baseline tooling for the four meeting topic classes.

Runs a grouped three-fold baseline cross-validation on up to 200 labelled meeting-topic text records using a naive-Bayes classifier to estimate classification accuracy.

Audits classification labels and predictions for meeting topic text records across four categories (planning, progress, decision, review), returning evaluation metrics and diagnostics.

Computes macro, micro, and weighted precision/recall/F1 evaluation scores for a meeting-topic text classifier across planning, progress, decision, and review categories.

Computes the multiclass Brier score for a meeting-topic classifier across up to 200 labeled text records with four categories: planning, progress, decision, and review.

Computes multiclass log loss for a meeting topic classifier across up to 200 labelled text records with four topic categories.

Evaluates a supplied set of labelled meeting-topic text records (planning/progress/decision/review) broken down by group, computing classification metrics and naive-Bayes baselines per segment.

Computes top-k label coverage metrics for a naive-Bayes meeting topic classifier across up to 200 labelled text records with 4 categories: planning, progress, decision, review.

Buys 1 USDC worth of MGA (Megaeth) tokens on behalf of the caller, returning transaction details and token amounts received.

Computes row-over-row changes in membership metrics (members or renewals) across up to 200 typed records, locally, with no external enrichment.

Converts raw membership activity records (members, renewals) into a base-100 indexed time series, normalized relative to a chosen baseline row.

Computes category-level frequency distributions across membership activity records (tiers, dates, members, renewals) for up to 200 rows of input data.

Computes daily sum series for membership activity (members or renewals) across typed records, grouped by tier and date, with local data-quality processing.

Pivots membership activity records (members and renewals) by date and tier category, returning a cross-tabulated summary of up to 200 input rows.

Detects duplicate row keys within up to 200 membership activity records (tier, date, members, renewals) and returns a data-quality report.

Removes exact duplicate rows from membership activity datasets containing tier, date, members, and renewals fields — up to 200 records per call.

Computes IQR-based statistical outlier flags on membership activity records (members or renewals fields) for up to 200 typed rows.

Compares two keyed datasets of membership activity records (members and renewals by tier and date) and returns row-level differences and data-quality metrics.

Sorts up to 200 membership activity records by a chosen numeric field (members or renewals) and returns them in ordered sequence.

Audits up to 200 membership activity records (by tier and date) for data quality issues such as missing, null, or out-of-range values in member counts and renewals.

Computes a secondary-measure weighted mean (e.g. members weighted by renewals) across up to 200 membership activity records, grouped by tier and date.

Airdrops Solana tokens to specified wallet addresses via an AI agent

Searches trending topics by keyword and returns ranked results to help identify the best trend for timely content creation.

Returns a paid LLM-generated or deterministic decision procedure (prose brief) for how an agent should gate and price merchant crawler traffic via the x402 protocol

Returns a paid AI-generated decision procedure brief for agents evaluating merchant credential issuance and revocation workflows in x402 autonomous commerce contexts.

Returns a paid AI-generated decision procedure brief explaining the standard process an autonomous agent merchant should follow when issuing delivery receipts

Returns a paid LLM-generated or deterministic decision procedure brief explaining how an autonomous agent should verify a merchant's discovery surface (the agent-facing catalog, metadata, and advertisement layer) for correctness and trustworthiness.

Returns a blunt, paid AI-generated decision brief for merchants evaluating whether to adopt card-network-backed crypto settlement standards (Visa/Mastercard/Google/Stripe) vs. x402 or traditional card rails.

Performs a trust and identity verification check on an agent or entity for use in agent handoffs, delegation, and provenance triage

Computes adjacent row-over-row changes and base-100 indexed series for triangle_count and vertex_count columns in supplied mesh budget records.

Computes adjacent row changes and an equal-width histogram for mesh budget data (triangle_count, vertex_count) across up to 200 supplied rows, returning two local analytical reports.

Analyzes supplied mesh budget records (triangle_count, vertex_count) to detect adjacent row changes and flag IQR-based outliers across up to 200 rows.

Computes adjacent row changes and secondary-measure weighted mean analytics for mesh budget data (triangle_count and vertex_count) across up to 200 rows, returning two reports per call.

Computes adjacent row changes and two-measure correlation analysis on mesh budget records (triangle_count and vertex_count) for up to 200 supplied rows.

Runs two local analytical reports on mesh budget data (triangle_count or vertex_count): a Base-100 indexed time series and a date-by-category pivot table, for up to 200 rows.

Computes a Base-100 index series and an equal-width histogram for supplied mesh budget records (triangle_count or vertex_count) using local analytical engines, returning two reports for up to 200 rows.

Computes Base-100 indexed time series and IQR-based outlier flags for mesh budget data (triangle_count and vertex_count) across up to 200 rows, producing 2 analytical reports.

Generates two analytical reports on mesh budget data (triangle_count, vertex_count): a base-100 indexed time series and a keyed dataset comparison, for up to 200 rows.

Computes a Base-100 index series and a secondary-measure weighted mean for mesh budget data (triangle_count and vertex_count) supplied by the caller, returning two analytical reports for up to 200 rows.

Analyzes mesh budget records (triangle_count, vertex_count) to produce two local analytical reports: category frequency distribution by asset_group and adjacent row change deltas, for up to 200 rows.

Analyzes mesh budget data (triangle_count or vertex_count) to produce category frequency distributions and daily sum time series reports for up to 200 rows.

Computes category frequency counts and an equal-width histogram for triangle_count or vertex_count fields across up to 200 mesh budget records.

Analyzes two datasets of mesh budget records (triangle_count, vertex_count) by computing category frequency distributions and performing keyed row-level comparison between the two datasets.

Analyzes user-supplied mesh budget records (triangle_count, vertex_count) to produce two reports: category frequency breakdown by asset_group and a numeric interval filter showing which rows fall within a specified min/max range.

Computes category-frequency distribution and secondary-measure weighted mean for mesh budget records (triangle_count, vertex_count) across up to 200 rows, returning two statistical reports.

Analyzes mesh budget records (triangle_count, vertex_count) by computing category-level frequency distributions and a trailing moving-average time series, returning two analytical reports for up to 200 rows.

Analyzes mesh budget records (triangle_count, vertex_count) to produce category frequency distributions and a two-measure correlation report for up to 200 rows.

Computes daily sum time series and base-100 indexed series for mesh budget data (triangle_count or vertex_count) across up to 200 rows, returning two analytical reports.

Generates two analytical reports — a daily sum time series and a date-by-category pivot table — for mesh budget data (triangle_count, vertex_count) across asset groups, for up to 200 rows.

Computes daily sum time series and fills explicit missing values (zero/mean/median) for mesh budget records containing triangle_count and vertex_count fields.

Computes daily sum time series and IQR-based outlier flags for triangle_count or vertex_count fields in supplied mesh budget records, returning two analytical reports for up to 200 rows.

Computes daily sum time series and Pearson correlation between triangle_count and vertex_count for supplied mesh budget records (up to 200 rows).

Pivots mesh budget data (triangle_count or vertex_count) by date and asset group category, and compares two keyed datasets — returning two analytical reports for up to 200 rows.

Analyzes up to 200 mesh budget records (triangle_count, vertex_count) to produce a duplicate key report and a base-100 indexed time series for a chosen metric.

Analyzes supplied mesh budget records (triangle_count, vertex_count) to produce a duplicate key report and category frequency breakdown for up to 200 rows.

Analyzes supplied mesh budget records (triangle_count, vertex_count) to produce a duplicate key report and a daily sum time series, using local analytical engines on up to 200 rows.

Analyzes supplied mesh budget records (triangle_count, vertex_count) to produce a duplicate key report and an equal-width histogram for a chosen numeric field, for up to 200 rows.

Analyzes up to 200 rows of mesh budget data (triangle_count or vertex_count) to produce a duplicate key report and IQR-based outlier flags using local analytical engines.

Analyzes up to 200 rows of mesh budget data (triangle_count, vertex_count) to produce a duplicate key report and a keyed dataset comparison between two supplied datasets.

Analyzes up to 200 mesh budget records to produce a duplicate key report and numeric distribution for triangle_count or vertex_count fields.

Analyzes supplied mesh budget records (triangle_count, vertex_count) to produce a duplicate key report and filter rows by a numeric interval, returning up to 200 rows across 2 analytical reports.

Generates equal-width histogram distributions and fills missing values for mesh budget records (triangle_count, vertex_count) across up to 200 rows.

Computes an equal-width histogram and a secondary-measure weighted mean for up to 200 mesh budget records (triangle_count, vertex_count) using local analytical engines.

Deduplicates mesh budget records and computes daily sum time series for triangle_count or vertex_count across up to 200 rows.

Deduplicates mesh budget records (triangle_count, vertex_count) by exact row match and generates a duplicate key report for up to 200 rows, returning two independent analytical reports.

Deduplicates mesh budget records and produces grouped numeric summaries for triangle_count and vertex_count fields across up to 200 rows.

Deduplicates mesh budget records and filters rows by a numeric interval on triangle_count or vertex_count, returning two analytical reports for up to 200 rows.

Runs two local analytical reports on mesh budget records: a grouped numeric summary and adjacent row change analysis for triangle_count or vertex_count fields.

Computes grouped numeric statistics and category frequency distributions for mesh budget records containing triangle and vertex counts.

Computes a grouped numeric summary and a daily sum time series for mesh budget data (triangle_count or vertex_count) across up to 200 rows.

Generates two local analytical reports — a grouped numeric summary and a date-by-category pivot — for supplied mesh budget records (triangle_count, vertex_count) across up to 200 rows.

Computes grouped numeric summary statistics and an equal-width histogram for mesh budget data (triangle_count, vertex_count) across up to 200 supplied rows.

Computes grouped numeric summary statistics and IQR-based outlier flags for mesh budget records containing triangle count and vertex count fields.

Computes grouped numeric summaries and applies a numeric interval filter on supplied mesh budget records (triangle_count, vertex_count) for up to 200 rows, returning two independent analytical reports.

Computes grouped numeric summary statistics and secondary-measure weighted mean for mesh budget records (triangle_count, vertex_count) across up to 200 rows in two independent reports.

Computes a grouped numeric summary and a two-measure correlation report for mesh budget records containing triangle_count and vertex_count fields.

Detects IQR-based outliers and fills missing values in mesh budget records (triangle_count, vertex_count) for up to 200 rows

Runs IQR-based outlier detection and keyed dataset comparison on up to 200 mesh budget records (triangle_count, vertex_count) using local analytics — no external lookups.

Runs two local analytical reports on mesh budget records — IQR-based outlier flagging and secondary-measure weighted mean — for up to 200 rows of triangle/vertex count data.

Runs IQR-based outlier detection and two-measure correlation analysis on supplied mesh budget records (triangle_count, vertex_count) for up to 200 rows.

Computes a numeric distribution report and a base-100 indexed series for up to 200 mesh budget rows (triangle_count or vertex_count), returning two analytical reports per call.

Computes numeric distribution statistics and category frequency counts for mesh budget records (triangle_count, vertex_count) across up to 200 supplied rows.

Generates a numeric distribution report and a daily sum time series for triangle_count or vertex_count fields from supplied mesh budget rows (up to 200 rows, 2 reports per call).