Skill UI

Creates high-fidelity visuals through structured JSON prompts and a Python generator script, handling subjects, styles, references, and technical specs for characters, scenes, or products.

A technique for dramatically increasing the hit rate when searching for TV series. Instead of using generic terms like genre or era, combine 2-3 highly distinctive plot details (e.g., character sacrifices, specific season incidents) into a single query. This method leverages the unique nature of plot points to pinpoint specific shows quickly.

Run OpenMM-powered molecular dynamics simulations and MDAnalysis trajectory workflows to build protein or small-molecule systems, minimize energy, equilibrate conditions, and characterize RMSD/RMSF, contacts, and free-energy surfaces for structural biology or drug studies.

This advanced technique allows users to identify an obscure actor by linking indirect clues across three domains: the director, the film's characteristics, and the actor's biographical details. It is essential when direct searches fail, using the director's work or a film's context as the primary entry point to resolve the actor's identity.

A comprehensive diagnostic guide for common ElevenLabs API errors, organized by HTTP status code. It provides detailed causes, fixes, and troubleshooting steps for issues such as invalid API keys (401), quota exhaustion, exceeding character limits (400), and rate limiting (429). Essential for developers debugging TTS, voice cloning, or streaming requests.

This skill provides methods to optimize ElevenLabs usage costs for Text-to-Speech (TTS) workloads. It covers model selection (e.g., using Flash/Turbo for savings), implementing character-efficient text pre-processing to reduce character count, and setting up real-time quota monitoring with budget alerts. Ideal for developers managing high-volume, cost-sensitive voice applications.

This guide sets up a professional, cost-effective local development workflow for ElevenLabs TTS/voice projects. It includes SDK mocking to prevent character quota overruns during testing, hot-reloading capabilities, and quota-aware scripts. Ideal for developers building robust AI voice applications.

Implements a robust data pipeline for handling large documents with the Grammarly API. This utility manages text chunking to comply with API character limits (max 100k), processes text in manageable segments, and aggregates multiple scoring metrics (like correctness, clarity, and tone) into a single, comprehensive report. Ideal for large-scale content analysis and data ingestion.

Lambda is a compact, machine-native communication protocol specifically designed for agent-to-agent (A2A) messaging. It functions as a shared, unambiguous vocabulary built from 'atoms' (2-character codes), completely bypassing the need for human natural language interpretation. It is ideal for orchestrators, task delegation, and logging structured coordination signals (like heartbeats or state changes) in multi-agent systems. Crucially, Lambda is intended only for machine communication, not for user-facing dialogue.

This advanced skill is an end-to-end tool for transforming complex research topics into professional, visualized knowledge graph PDFs. It automatically conducts multi-round web searches, extracts key entities, structures related knowledge, and designs the optimal visualization (supporting Graphviz, PlantUML, etc.). Ideal for deep academic analysis, mapping character relationships, or visualizing complex technical architectures where existing structured data is unavailable.

This technique is designed for the final verification stage when analyzing a candidate TV series. Instead of accepting initial matches, users must perform targeted searches combining the show name and specific character details (e.g., birth year, specific plot event, relationship). This ensures that the candidate show satisfies all complex constraints, eliminating false positives and confirming the accuracy of the plot details.