Skill UI

Builds a unified team calendar with events, attendees, and time zones. Produces CSV, SQL, or Notion artifacts on request for shared scheduling and availability.

Proofreads English technical writing such as READMEs, API references, tutorials and blog drafts for typos, grammar, punctuation, terminology consistency and structure. Returns an itemized Original → Suggestion → Reason checklist with statistics, never rewriting the document.

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.

Ultracave is a communication mode that strips all fluff from technical responses. It uses sentence fragments, one word per fact, and preserves code, commands, and paths verbatim. This style ensures maximum compression while maintaining technical substance. It persists throughout the session until explicitly disabled. Ideal for developers needing precise, concise information without unnecessary explanations.

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.

Coordinates sponsored meta-transaction nodes, fee reservation pools, and cryptographic nonce tracking for frictionless Web3 user onboarding. Provides standardized data models and verification schemas for managing relayer infrastructure.

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.

This skill helps identify explanatory attributes or hypotheses for variations in process metrics such as duration, waiting time, utilization, and rework. It involves checking metadata correlations, statistical evidence, and cohort comparisons to distinguish competing explanations. The method emphasizes evidence-based analysis, avoiding silent assumptions, and framing findings as testable hypotheses rather than definitive causal claims. It supports structured investigation of process efficiency and bottlenecks using specific analytical tools and frozen baseline scopes.

Guides analysis of object-centric processes using OCPM tools, including object types, executions, and edges. Provides filter construction for timeframes and delays, emphasizing evidence-based conclusions.

Guides investigating common or slow process variants, cases with repeated work, and exact-case queries in Process Mining. Provides step-by-step tool calls for variant metrics, rework filtering, and attribute-based case selection, adhering to shared contracts and investigation methods.

This skill enables comparing process cohorts, departments, or time periods using matched definitions. It involves fixing outcome definitions, metrics, and aggregations while freezing baselines. Users should use specific API calls to retrieve metrics and statistics for matched pairs, ensuring reproducibility and avoiding data leakage between exploratory and baseline filters. It supports analyzing before-and-after results with strict time window controls.