Skill UI

This skill is designed to manage complex, multi-step tasks by coordinating the efforts of multiple specialized AI agents. It provides structured methods for listing available agents, initiating real-time conversations, submitting complex background tasks (such as data analysis or report generation), tracking task status, and maintaining conversational context using session IDs. It is essential when a core task requires diverse expert knowledge or sequential collaboration.

Analyzes and generates a self-contained, explorable HTML report detailing usage metrics for Claude Code sessions. It tracks token consumption (input/output), subagent usage, skill calls, and cache efficiency across specified time ranges. This tool helps developers visualize resource waste and pinpoint areas for workflow optimization, ensuring cost-effective and efficient AI development cycles.

A powerful AI tool designed to transform complex scientific concepts into publication-quality visual schematics. Utilizing Nano Banana 2 AI for generation and Gemini 3.1 Pro Preview for rigorous quality review, the skill specializes in creating architectural diagrams, neural network structures, biological pathways, and complex flowcharts. It employs smart iterative refinement, ensuring the output meets predefined quality thresholds for academic journals, posters, and reports.

This advanced skill orchestrates a comprehensive, multi-agent review of legal contracts. It analyzes risk, compliance, missing protections, and plain-English readability simultaneously. By simulating a team of legal specialists, it aggregates findings into a single executive report, complete with a quantifiable Contract Safety Score (0-100). Ideal for founders, freelancers, or small businesses needing expert legal insights without retaining full-time counsel.

This skill provides comprehensive diagnosis and optimization for agent skill libraries. By analyzing historical session transcripts from platforms like Claude Code and Codex, alongside static skill file checks, it scores each skill across 8 dimensions. It identifies issues such as low trigger rates, poor post-invocation user reaction, and incomplete workflow execution, generating a prioritized report (P0/P1/P2) to significantly improve the agent's overall performance and reliability.

This powerful compiler ingests heterogeneous research inputs, including PDF papers, code repositories, experiment logs, and raw notes. It transforms this diverse data into a comprehensive, structured Agent-Native Research Artifact (ARA). The system extracts core knowledge atoms, builds cognitive maps (claims, concepts, heuristics), and generates a verifiable, executable knowledge package for advanced AI consumption and research iteration.

A systematic auditor designed to evaluate the resilience and quality of complex AI workflows. It scans across five critical dimensions—Prompt Quality, Context Efficiency, Tool Health, Architecture Fitness, and Safety—providing a scored report and prioritized, actionable remediation steps. Use this tool to find hidden flaws and ensure robustness before deploying any AI agent or system.

This skill searches GitHub and the web to discover the latest Japanese Natural Language Processing (NLP) resources, tools, and libraries (e.g., NER, LLM, TTS) that are not yet included in the awesome-japanese-nlp-resources list. It is designed for developers and researchers who want to track the cutting edge of Japanese language technology or prepare a contribution.

Combines a curated Japanese NLP resource dataset with live web research to produce an up-to-date trend report on models, tooling, benchmarks, embeddings, speech, and related subfields.

This skill generates a comprehensive issue report on the current challenges, limitations, and open problems within Japanese Natural Language Processing (NLP) for a specified topic. By combining knowledge from a curated local dataset with real-time web search, it provides a deep dive into ongoing research gaps, evaluating the state-of-the-art and recommending areas for future work.

This skill acts as a comprehensive hybrid router for any research request. It first deterministically classifies the user's intent, delegating the query to specialized modules like Pulse (trends/sentiment), Grants (NIH funding), or LitReview (academic papers). If no specialist matches, it falls back to a robust general search and synthesis workflow. The system ensures routing transparency, provides comprehensive reports, and includes full citations and an audit log.

A generic entry point for delegating self-contained, multi-step tasks to specialized LLM agents (Codex, Claude Code, Pi). Utilizes background processing tools to manage the full lifecycle of AI-driven sub-tasks, such as policy review, complex report synthesis, document generation, or large-scale code refactoring. Ideal for meta-skill workflows requiring full agent agency.