Skill UI

Manage document template governance with a central library. Track template name, type, owning module and department, owner, last updated, and content link. Supports CSV, SQL DDL, JSON Schema, and Notion mapping outputs.

Designs the smallest useful time tracking setup for a business: purpose, granularity, approval and lock rules, then emits CSV, SQL, JSON Schema or Notion artifacts on request. Produces empty templates only, never real employee or customer data.

Builds the smallest useful vendor and contractor register for a business: field list, owner, linked contract dates, payment terms, risk tagging and review cycle, with CSV, SQL, JSON or Notion outputs produced only on request.

Provides standardized field schemas, SQL DDL, JSON Schema, and operational registers for configuring rate-limiting windows and automated circuit breakers across Web3 smart contracts and relayers.

Registers zero-knowledge SNARK proof verification keys, circuit complexity constraints, and nullifier tracking for double-spending prevention in privacy systems. Provides standardized field schemas, SQL DDL, JSON validation, and best practices for auditable cryptographic verification across distributed applications and smart contracts.

A browser runtime skill that provides isolated WPE WebKit sessions, native input, screenshots, and ordered JSONL automation. Supports docker-based container lifecycle, deterministic testing, and GitHub Actions verification. Useful for reproducible browser checks and self-hosted runtime integration.

Statically review MCP configuration files (.mcp.json, Cursor, VS Code, Claude, Windsurf) for mutable package references such as @latest, tags, or version ranges before approval or in CI, without executing discovered servers.

Use xberg batch to extract documents in bulk with shared config, bounded parallelism, per-file overrides, and fault-tolerant error recovery. Supports various formats, JSON envelope output, and configurable concurrency.

Xberg extracts tabular data from PDFs, spreadsheets, and images using layout-aware detection and configurable table models. Supports markdown and JSON output formats, with options for table model selection, confidence thresholds, and programmatic access via Python and Node.js APIs.