Skill UI

A comprehensive skill designed to guide users through the installation and configuration of the OpenViking long-term memory plugin for OpenClaw. It enables the agent to automatically capture facts from conversations and recall relevant context across sessions (auto-capture + auto-recall). The process is fully natural-language driven, requiring no command-line knowledge from the user.

This tool functions as a Command Line Interface (CLI) alias for implementing the specific 'pua:mama' protocol within advanced coding models like Codex or Claude Code. It loads and enforces a structured 'mama skill/protocol,' maintaining rigorous verification standards while adjusting the visible narrative style to a specific 'Chinese-mom nagging mode.' It manages configuration by interacting with `~/.pua/config.json`, ensuring existing user fields are preserved.

This CLI alias serves as the primary interface for the Codex /pua:pro protocol, designed for advanced code operations within the Claude Code environment. It manages complex workflows related to self-evolution, platform telemetry monitoring, key performance indicators (KPIs), and system configuration updates, ensuring robust and consistent protocol adherence.

The Ejentum Reasoning Harness is a comprehensive library of cognitive operations designed to guide complex AI agents through critical thinking tasks. It exposes four specialized harnesses (reasoning, code, anti-deception, memory) that mitigate common failure modes like hallucination and reasoning decay. Instead of a fixed answer, the agent ingests a detailed, executable scaffold—including failure patterns, procedures, and falsification tests—to ensure robust, self-verified output.

A rigorous CAIO review framework that interrogates any plan involving AI. It covers six pressing questions around eval sets, hallucination SLOs, EU AI Act risk tiers, API vs fine-tune vs build, cost economics, and hiring prerequisites, before shipping or committing to AI projects.

A specialist tool designed to pressure-test AI Management Systems (AIMS) against the ISO 42001 standard. It executes six critical compliance checks, covering scope definition, risk mapping, policy adherence, and framework integration. Essential for pre-certification readiness, annual internal audits, and new system onboarding.

This skill provides a comprehensive, structured workflow for creating, authoring, and refining new agent skills. It guides users through gathering requirements, drafting structured documentation (SKILL.md), adding utility scripts, and optimizing the skill description for optimal agent recognition. Ideal for system architects and developers building complex AI agent toolsets.

A 12-agent AI pipeline for comprehensive academic paper writing across all disciplines. Supports 11 modes including planning, drafting, revising, and rebuttal auditing. Features style calibration, writing quality checks, citation verification, and multi-format output (LaTeX, DOCX, PDF). Ideal for researchers needing systematic assistance from literature search to final submission.

This skill simulates a comprehensive international journal peer review process by dynamically configuring a 5-seat review panel. It includes a Journal-Fit Reviewer, three peer-review roles, and a Devil's Advocate to challenge core arguments. The system automatically identifies the paper's field and methodology, then generates five role-separated review reports followed by a structured Editorial Decision Letter and Revision Roadmap. It supports various modes including full review, re-review, quick assessment, and reviewer calibration, handling inputs in multiple languages.

This skill helps discover new Japanese Natural Language Processing (NLP) resources, including GitHub repositories and Hugging Face models/datasets, that are not yet documented in the awesome-japanese-nlp-resources list. It analyzes a given topic, suggests candidates using web search, and outputs contribution-ready markdown for easy integration.

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.