All Services

Returns the current local time and time zone details for Bordeaux, including IANA zone name, UTC offset, DST status, and next DST transition.

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Cape Town, South Africa.

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Chennai, India.

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Cologne, Germany

Returns the current local time and full timezone details for Cork, Ireland, including IANA zone name, UTC offset, DST status, and next DST transition.

Returns the current local time, IANA time zone name, UTC offset, DST status, and next DST transition for Delhi, India.

Returns the current local time, IANA time zone name, UTC offset, DST status, and next DST transition for Geneva, Switzerland.

Returns the current local time and time zone details for Hamburg, including IANA zone name, UTC offset, DST status, next DST change, and current local date-time.

Returns the current local time and time zone details for Lagos, including IANA zone name, UTC offset, DST status, and next DST change.

Returns the current local time, IANA time zone name, UTC offset, DST status, and next DST transition for Madrid, Spain.

Returns the current local time and time zone details for Munich, including IANA zone name, UTC offset, DST status, and next DST transition.

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Naples, Italy

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST change for Nice, France.

Returns current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Oslo, Norway.

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Paris.

Returns the current local time, IANA time zone name, UTC offset, DST status, and next DST transition for Porto, Portugal

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Prague.

Returns the current local time, IANA time zone name, UTC offset, DST status, and next DST transition for Seville, Spain.

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Shanghai

Returns current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Stuttgart, Germany

Returns the current local date-time, IANA zone name, UTC offset, DST status, and next DST transition for Tokyo

Returns the current local time, IANA timezone name, UTC offset, DST status, and next DST transition for Warsaw, Poland.

Finalizes a resume build session on Tiny CV, completing the paid workflow to publish a clean CV link or export a PDF from markdown content.

Returns registry metadata for the .info top-level domain including operator, type, IANA/RDAP details, WHOIS server, creation date, DNSSEC status, and nameservers.

Returns registry metadata for the .media top-level domain including operator, type, IANA/RDAP details, WHOIS server, creation date, DNSSEC status, and nameservers.

Returns registry metadata for the .to top-level domain, including operator, type, IANA/RDAP details, WHOIS server, creation date, DNSSEC status, and nameservers.

Returns registry metadata for the .travel top-level domain, including operator, type, IANA/RDAP details, WHOIS server, creation date, DNSSEC status, and nameservers.

Computes period-over-period changes in annualised simple token issuance rate across multiple consecutive observation windows.

Calculates a base-100 rebased index of a token's annualised simple issuance rate across multiple supplied observation periods.

Calculates and compares the annualised simple token issuance rate between two time periods (before and after), returning a deterministic before/after comparison report.

Computes the benchmark correlation of annualised simple token issuance rates across multiple observations against a set of benchmark values.

Calculates annualised simple issuance rates from token supply observations and flags statistical outliers using interquartile range (IQR) analysis.

Computes the local finite-change elasticity of a token's annualised simple issuance rate with respect to a specified input field, given baseline token observations and a step size.

Ranks multiple token observations by their annualised simple issuance rate, returning a deterministic record ranking report for the supplied set.

Classifies whether a token's annualised simple issuance rate falls within caller-defined lower and upper thresholds across multiple observation periods.

Retrieves EVM token transfer history for a given wallet address on a specified chain, paginated by limit

Computes IQR-based outlier flags for token assessment evidence coverage ratios given observed vs. requested field counts across multiple rows.

Calculates the gap between observed and requested evidence fields for a token assessment, comparing actual coverage against a numeric target threshold.

Calculates the average reported trade notional (volume per trade) for one or more token trading pairs given volume and trade count inputs, returning deterministic per-row results in a single batch call.

Computes and compares the average reported trade notional (volume per trade) for a token across two time periods or states, returning a deterministic before/after delta report.

Computes the Pearson or similar correlation between a token's average reported trade notional (volume/trades per row) and a supplied benchmark series, returning a bounded correlation report.

Computes a distribution histogram of average reported trade notional (volume_usd / trades) across supplied token observations, bucketed into a configurable number of bins.

Computes IQR-based outlier flags for average reported trade notional values across a set of token trading observations.

Calculates the average reported trade notional (mean trade size) for a token given total volume and trade count inputs.

Computes period-over-period changes in bid-ask spread for a supplied sequence of token quote observations

Computes a Base-100 rebased index of token bid-ask spread observations, normalizing all values relative to a selected base row.

Computes a distribution histogram of bid-ask spread values across a supplied set of token quote observations, returning binned frequency data.

Computes local finite-change elasticity for a token's bid-ask spread given supplied baseline quote observations and a step percentage.

Compares named market spread scenarios against a baseline bid-ask pair to compute deterministic spread metrics for each labelled scenario.

Computes a one-input sensitivity table for token bid-ask spread by varying either the ask or bid price across a set of values against a baseline quote pair.

Analyzes ordered temporal trends in token bid-ask spread data across a sequence of observations

Ranks a supplied list of token bid-ask spread observations deterministically, identifying record (extreme) values within the set.

Calculates the bid-ask spread for a token given a single pair of bid and ask price observations.

Computes a weighted mean of bid-ask spread observations for a token, given an array of bid/ask price pairs and corresponding weights.

Calculates a base-100 rebase report for token buy receipt shortfalls, indexing actual vs expected token observations relative to a chosen base row.

Computes a deterministic before-and-after comparison of token buy receipt shortfall, reporting how actual tokens received differed from expected tokens across two observations.

Computes the Pearson or similar correlation between token buy receipt shortfall ratios and a set of caller-supplied benchmark values across multiple observations.

Computes a statistical distribution summary of token buy receipt shortfalls (expected vs actual tokens received) across a batch of observations.

Computes the local finite-change elasticity of a token buy receipt shortfall, measuring how sensitive the shortfall is to small percentage-point changes in a chosen input variable.

Computes a one-input sensitivity table for token buy receipt shortfall, showing how shortfall varies as either expected_tokens or actual_tokens changes across a range of values.

Analyzes ordered trend patterns in token buy receipt shortfalls (expected vs. actual tokens received) across a sequence of observations and returns a deterministic computation report.

Ranks up to 200 token buy receipt records by their shortfall (difference between expected and actual tokens received), returning a deterministic ordered ranking report.

Computes a rolling mean of token buy receipt shortfall (expected minus actual tokens received) across a sliding window over supplied transaction rows.

Calculates the shortfall between expected and actual tokens received in a token purchase, returning a deterministic difference or threshold verdict.

Classifies whether token buy receipt shortfall values fall within caller-defined lower and upper thresholds across a batch of expected vs. actual token observations.

Computes the adjacent period-over-period changes in the buy-to-sell activity ratio for a token, given sequences of buy and sell counts.

Computes a Base-100 rebased index of token buy-to-sell activity ratios across a series of observations, anchored to a chosen baseline period.

Calculates the buy-to-sell activity ratio for up to 200 token observation rows in a single batch, returning a deterministic ratio or threshold-based verdict per row.

Compares token buy-to-sell activity ratios across two time periods (before and after), computing the ratio change deterministically from supplied buy/sell counts.

Computes the correlation between a token's buy-to-sell activity ratio time series and a supplied benchmark series, returning a deterministic bounded report.

Computes a statistical distribution summary of buy-to-sell count ratios across a supplied series of token trading observations.

Compares a baseline token buy/sell count ratio against one or more named alternative scenarios to deterministically assess how ratio changes across each scenario.

Performs ordered trend analysis on a time-series of token buy/sell count observations to compute and evaluate the directional trend of the buy-to-sell ratio.

Computes a rolling mean of the buy-to-sell activity ratio across a supplied sequence of token trade observations using a configurable window size.

Calculates the buy-to-sell activity ratio for a token given a buy count and sell count, returning a deterministic numeric result or threshold verdict.

Calculates the gap between a token's buy-to-sell activity ratio and a specified target value, returning a deterministic threshold verdict report.

Computes a two-dimensional scenario grid of token buy-to-sell activity ratios across combinations of buy_count and sell_count values supplied by the caller.

Computes the weighted mean of token buy-to-sell activity ratios across multiple supplied observations using caller-provided weights.

Computes period-over-period changes in the buy volume fraction (buy volume as a share of total volume) for a token across a sequence of time periods.

Computes a statistical distribution summary of the buy volume fraction (buy volume as a share of total volume) across a supplied set of token trading observations.

Calculates IQR-based outlier flags for the buy volume fraction (buy_volume / total_volume) across a supplied set of token trading observations.

Compares token buy volume fraction across named scenarios against a baseline, returning deterministic verdicts for each labeled scenario.

Analyzes the ordered trend of buy volume fraction (buy volume as a share of total volume) across a sequence of token trading observations.

Ranks a set of token observations by their buy volume fraction (buy volume as a share of total volume) and returns a deterministic record ranking report.

Calculates the buy volume fraction (buy volume share) of a token given buy and sell volume figures, returning a deterministic ratio or threshold verdict.

Calculates the gap between a token's current buy volume fraction and a specified target value, given buy and sell volume inputs.

Classifies whether the buy volume fraction (buy volume share) of a token falls within a specified lower/upper threshold range, using deterministic calculation on supplied observations.

Computes the weighted mean of the buy volume fraction (buy volume / total volume) across multiple token trading observations.

Calculates token circulating market capitalization for up to 200 token observations in a single batch, returning deterministic results per row.

Computes and compares token circulating market capitalization between two points in time (before and after) using supplied price and supply data.

Computes a distribution histogram of token circulating market capitalization values from a supplied set of price and circulating-supply observations.

Computes a statistical distribution summary of token circulating market capitalization from a set of price and circulating supply observations.

Flags outlier observations in token circulating market cap data using interquartile range (IQR) statistical analysis.

Computes the local finite-change elasticity of a token's circulating market capitalization with respect to a specified input field (price or circulating supply), given a baseline and a small percentage step.

Compares a baseline token circulating market cap against up to 20 named scenarios with different price and/or supply overrides, returning deterministic verdicts.

Ranks a list of token observations by circulating market capitalization (price × supply), returning a deterministic record ranking report.

Computes a rolling mean of token circulating market capitalization over a sliding window of supplied price and circulating supply observations.

Performs sequential input-change (waterfall) attribution on token circulating market capitalization, decomposing how changes in price and circulating supply drive overall market cap change.

Calculates the circulating market capitalization of a token given its USD price and number of circulating tokens

Classifies token circulating market capitalization observations against caller-defined lower and upper thresholds, returning a deterministic verdict for each row.