Skill UI

This advanced tool generates a comprehensive, five-section academic paper outline (Abstract, Introduction, Method, Results, Discussion). Given a research topic, preferred style, and curated reference sources, it crafts a detailed narrative backbone aiming for 6,500-8,000 words. It ensures that each section contains sufficient concrete substance, sub-topics, and specific findings, providing a robust foundation for authors to expand into a full, high-quality research manuscript.

This specialized tool is designed to curate and structure academic source material for long-form research papers. It takes paper topics, user preferences, search results, and bibliography entries as input. The output is a highly structured source pack, clearly identifying primary, supporting, and excluded sources, along with coverage notes to ensure research depth and methodological rigor.

Use PaperJSX to automate the creation of professional documents, including PPTX presentations, DOCX reports, XLSX spreadsheets, and PDF files. By providing a structured JSON specification, this tool generates ready-to-use files, eliminating manual formatting and ensuring consistency across large-scale reporting and content generation pipelines.

Generates high-quality, short video clips (3-15s) using the Seedance 2.0 model. This tool accepts structured English prompts, an optional first-frame image, and an optional identity/style reference image for continuity. It supports dual backends (OpenRouter, Volcengine, BytePlus) to maximize accessibility and reliability for cinematic shot generation.

An internal tool designed to validate candidate meta-skills (SKILL.md) before registration. It performs comprehensive structural linting (G1 rules) and a scheduler dry-run (G2) to ensure the workflow is deterministic, references are correct, and templates resolve properly. It outputs detailed JSON diagnostics.

An internal utility designed to manage the entire lifecycle of meta-skill proposals within the opensquilla ecosystem. It allows developers to atomically write new skill proposals, list existing candidates, and formally accept them after passing rigorous gate checks (linting, smoke testing, E2E). This tool ensures structured and controlled deployment of new skills.

An internal, non-user-invocable agent used by the meta-skill creator process. It executes positive (G3) and negative (G4) smoke tests against a candidate meta-skill definition (SKILL.md). It simulates meta-resolution using LLM-generated fixtures and reports the results in a structured JSON format.

A utility for managing and installing specialized AI skills into the Codex environment. It supports fetching curated skills from predefined sources (like openai/skills) or installing custom capabilities directly from any GitHub repository, including private ones. It handles listing available skills, installing specific modules, and provides robust fallback methods (download/git sparse checkout).

SkillOpt-Sleep simulates an agent's nightly 'sleep' cycle to continuously improve performance without requiring model retraining. It harvests historical sessions, mines recurring tasks, and replays them offline. Learning and insights are then consolidated into the agent's memory and skills (CLAUDE.md/SKILL.md), proposing bounded, validated edits that the user must explicitly adopt, ensuring measurable, sustained improvement over time.

An internal helper designed for analyzing Rust panics and backtraces. It guides users to perform Rust-specific checks for proper handling of Option and Result types, generates minimal reproducible cargo test commands, and pinpoints exact patch targets for safe code improvements.

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.

Provides comprehensive, programmatic control over tmux sessions. Users can list, capture output from, send specific keystrokes, and programmatically navigate panes/windows in remote, long-running interactive CLI sessions. Essential for monitoring AI code generation tools (like Claude/Codex) or managing complex multi-terminal workflows via scripting.