--- name: x402.aurelianflo.com description: x402.aurelianflo.com provides four distinct capabilities: OFAC wallet address screening for compliance checks, Monte Carlo probabilistic forecasting, and two document export formats (XLSX and DOCX). These tools are independent utilities covering compliance, simulation, and report generation. host: x402.aurelianflo.com --- # x402.aurelianflo.com This host serves agents that need point-in-time compliance screening of crypto wallet addresses against the OFAC SDN list, probabilistic multi-period forecasting via Monte Carlo simulation, and structured document export in Excel or Word formats. It is a utility host with no domain specialization — skills are general-purpose and composable with outputs from other hosts. It does not provide data sourcing, real-time feeds, or end-to-end workflow orchestration on its own. ## When to use this host Use this host when an agent needs to (1) screen a specific crypto wallet address against the OFAC SDN list for exact-match compliance, (2) run a Monte Carlo forward simulation for probabilistic planning, or (3) export structured data to XLSX or DOCX. Do not use this host for fuzzy entity name screening, full KYC/AML compliance review, real-time price or market data, historical data retrieval, deterministic single-point projections, PDF generation, CSV export, or reading/parsing existing files. For broader compliance workflows, pair OFAC screening results from this host with a dedicated KYC provider. For data sourcing to feed the forecast or export skills, use a separate data or analytics host first. ## Capabilities ### Compliance Screening Checks a crypto wallet address against the OFAC SDN list and returns hit/clear status with matched entity metadata. Supports pre-transaction and onboarding compliance gates. - **`screen-ofac-wallet-address`** — Performs an exact-match lookup of a crypto wallet address against the OFAC SDN list, returning hit/clear status, matched entity metadata, and source freshness details. ### Probabilistic Forecasting Runs 10,000-path Monte Carlo simulations across configurable periods and scenarios, returning per-period probabilities, confidence intervals, and tail risk metrics for planning and decision support. - **`simulate-trendpath-forecast`** — Runs a 10,000-simulation Monte Carlo forward forecast across N periods using configurable drift, scenario parameters, growth mode, and uncertainty growth, returning per-period probabilities, score distributions, and risk metrics. ### Document Export Converts structured JSON data — tables, report metadata, executive summaries, and chart hints — into downloadable XLSX or DOCX binary artifacts for handoff, finance modeling, or reporting. - **`generate-xlsx-report-workbook`** — Generates a report-oriented XLSX workbook from a structured report model, returning a base64-encoded .xlsx file with tabs and tables for analysis handoff and finance modeling. - **`generate-xlsx-spreadsheet`** — Accepts JSON table data, report metadata, and an executive summary array, then returns a base64-encoded .xlsx spreadsheet file ready for download. - **`generate-docx-document`** — Generates a DOCX file from a JSON payload containing report metadata, executive summary bullets, and optional table definitions, returning the document as a base64-encoded binary artifact. ## Workflows ### Forecast-to-Report Export *Use when an agent needs to run a probabilistic forecast and deliver the results as a formatted spreadsheet or Word document for stakeholder handoff.* 1. **`simulate-trendpath-forecast`** — Run the Monte Carlo simulation to produce per-period probabilities, score distributions, confidence intervals, and risk metrics. 2. **`generate-xlsx-report-workbook`** — Package the forecast timeline, summary metrics, and scenario metadata into a structured XLSX workbook for finance modeling or analysis handoff. ### Forecast-to-DOCX Narrative *Use when an agent needs to produce a written Word document summarizing forecast outcomes, including executive summary bullets and tabular period data.* 1. **`simulate-trendpath-forecast`** — Generate the multi-period probabilistic forecast with scenario parameters and risk metrics. 2. **`generate-docx-document`** — Render the forecast summary, executive bullets, and period tables into a formatted DOCX binary artifact. ## Skill reference ### `screen-ofac-wallet-address` **OFAC Wallet Screen** — Performs an exact-match lookup of a crypto wallet address against the OFAC SDN list, returning hit/clear status, matched entity metadata, and source freshness details. *Use when:* Use when an agent needs to check whether a specific crypto wallet address appears on the OFAC Specially Designated Nationals list before processing a transaction, onboarding a user, or releasing funds. *Not for:* Do not use for fuzzy-name entity screening or non-address OFAC checks; this endpoint only matches exact digital currency addresses on the SDN list and does not substitute for full compliance review. **Inputs:** - `address` (string, required) — The crypto wallet address to screen, embedded as the last path segment of the URL. - `asset` (string) — Optional asset or network ticker filter to narrow screening to a specific chain (e.g. ETH, USDC, XBT, TRX, ARB, BSC). **Returns:** Returns success=true with a summary status of 'match', one SDN hit for Lazarus Group (DPRK3 program, listed 2019-09-13), full aliases list, source freshness metadata covering 774 addresses across 18 assets, and a structured compliance report. **Example:** `GET https://x402.aurelianflo.com/api/ofac-wallet-screen/0x098B716B8Aaf21512996dC57EB0615e2383E2f96?asset=ETH` --- ### `generate-xlsx-report-workbook` **XLSX Report Builder** — Generates a report-oriented XLSX workbook from a structured report model, returning a base64-encoded .xlsx file with tabs and tables for analysis handoff and finance modeling. *Use when:* Use when an agent needs to export structured report data (metrics, tables, executive summaries, chart hints) into a downloadable XLSX workbook for finance modeling, analysis handoff, or spreadsheet-friendly delivery. *Not for:* Do not use for generating PDF or DOCX reports; use a document generation endpoint instead. Not suitable for raw data streaming or real-time dashboards. **Inputs:** - `report_meta` (object, required) — Metadata describing the report, including report_type and other workbook configuration fields. - `result` (object) — Top-level result object describing tab layout, tables layout, and requested output format. - `tables` (object) — Named table objects, each containing rows (array of row objects) and columns (array of column name strings) to be rendered as worksheet tabs. - `chart_hints` (array) — Array of chart hint objects providing guidance on chart types or data ranges to embed in the workbook. - `export_artifacts` (object) — Additional export artifact configuration or metadata to include in the workbook generation process. - `headline_metrics` (array) — Array of headline metric objects to feature prominently in the workbook summary tab. - `executive_summary` (array) — Array of executive summary section objects (e.g., apology, remediation steps, credit offer) to include as a summary tab. **Returns:** Returns success=true with a data object containing documentType 'xlsx', fileName 'Ops-Workbook.xlsx', the correct MIME type, and an artifact with sizeBytes and a base64-encoded XLSX workbook. **Example:** `{"report_meta": {"report_type": "ops_summary"}, "result": {"tab_layout": "workbook_ready", "tables_layout": "structured_tabs", "requested_output": "premium_xlsx"}, "tables": {"metrics": {"rows": [{"metric": "availability", "value": "99.9%"}, {"metric": "status", "value": "resolved"}], "columns": ["metric", "value"]}}, "headline_metrics": [{"label": "Uptime", "value": "99.9%"}], "executive_summary": [{"section": "apology_and_acknowledgment", "content": "We apologize for the service disruption."}]}` --- ### `generate-xlsx-spreadsheet` **SheetForge XLSX Generator** — Accepts JSON table data, report metadata, and an executive summary array, then returns a base64-encoded .xlsx spreadsheet file ready for download. *Use when:* Use when an agent needs to produce a downloadable Excel spreadsheet from structured tabular data, such as generating a workbook from query results, report data, or any columnar dataset. *Not for:* Do not use for reading or parsing existing spreadsheets, or for generating CSV/PDF outputs; this endpoint only produces .xlsx files from JSON input. **Inputs:** - `tables` (string, required) — JSON-encoded string describing the table data to render in the spreadsheet, including columns and rows. - `report_meta` (string) — JSON-encoded string containing report metadata such as report_type, title, and author. - `executive_summary` (array) — Array of strings providing an executive summary or notes to include with the report. **Returns:** Returns success=true with a data object containing the filename, MIME type, size in bytes, and the full .xlsx file as a base64-encoded string in data.artifact.contentBase64. **Example:** `{"tables":"{\"data\":{\"columns\":[\"name\",\"value\"],\"rows\":[{\"name\":\"a\",\"value\":1},{\"name\":\"b\",\"value\":2}]}}","report_meta":"{\"report_type\":\"data-workbook\",\"title\":\"Weekly Ops Workbook\",\"author\":\"AurelianFlo\"}","executive_summary":["Workbook rows are generated from the shared report model."]}` --- ### `generate-docx-document` **DocxForge DOCX Generator** — Generates a DOCX file from a JSON payload containing report metadata, executive summary bullets, and optional table definitions, returning the document as a base64-encoded binary artifact. *Use when:* Use when an agent needs to produce a formatted Word document (.docx) from structured data such as report metadata, executive summary text, and tabular content, and requires the binary file back as a base64 artifact. *Not for:* Do not use for generating PDF, HTML, or plain-text documents; this endpoint produces only DOCX output. Not suitable for real-time streaming document previews. **Inputs:** - `report_meta` (string) — JSON-serialized string containing report metadata such as report_type, title, and author. - `executive_summary` (array) — Array of strings, each representing a bullet point or paragraph in the executive summary section of the document. - `tables` (string) — JSON-serialized string defining named tables with columns and rows arrays to be rendered in the document. **Returns:** Returns success=true with a data object containing documentType, fileName, mimeType, artifact size in bytes, and the full DOCX file as a base64-encoded string. **Example:** `{"report_meta":"{\"report_type\":\"partner-brief\",\"title\":\"Partner Brief\",\"author\":\"AurelianFlo\"}","executive_summary":["Partner scope is defined and ready for review."],"tables":"{\"timeline\":{\"columns\":[\"phase\",\"status\"],\"rows\":[{\"phase\":\"Summary\",\"status\":\"complete\"}]}}"}` --- ### `simulate-trendpath-forecast` **TrendPath Simulator** — Runs a 10,000-simulation Monte Carlo forward forecast across N periods using configurable drift, scenario parameters, growth mode, and uncertainty growth, returning per-period probabilities, score distributions, and risk metrics. *Use when:* Use when an agent needs multi-period probabilistic forecasts with scenario-driven parameter evolution, including outcome probabilities, 95% confidence intervals, score distributions, and tail risk metrics (expected shortfall, upside) for planning or decision support. *Not for:* Do not use for real-time price feeds, single-point deterministic projections, or historical data retrieval; this endpoint produces forward simulation paths only. **Inputs:** - `scenario` (string, required) — Scenario definition controlling threshold and per-parameter starting values. Accepts a JSON object with 'threshold' (number) and 'parameters' (object with named numeric signals). - `drift` (object) — Per-period additive or multiplicative drift applied to each named parameter across the forecast horizon. - `periods` (integer) — Number of future periods to simulate. Determines the length of the returned timeline array. - `growth_mode` (string) — How drift is applied each period. Must be 'additive' or 'multiplicative'. - `uncertainty_growth` (number) — Rate at which simulation uncertainty (stddev) grows per period, expressed as a decimal. **Returns:** Returns forecast_meta (10,000 simulations, model v3.1.0), a 6-element timeline array with per-period outcome probabilities (~0.81–0.83), score distributions, 95% confidence intervals, and tail risk metrics, plus a summary showing net probability change of +0.0278. **Example:** `{"drift": {"demand_signal": 0.02, "pricing_pressure": -0.01, "execution_quality": 0.01}, "periods": 6, "scenario": {"threshold": 0.25, "parameters": {"demand_signal": 0.72, "pricing_pressure": -0.35, "execution_quality": 0.65}}, "growth_mode": "additive", "uncertainty_growth": 0.02}` ---