Skill UI

This guide teaches researchers how to strategically position a paper's contribution within established academic lineages (e.g., click models, LTR). It emphasizes moving beyond simple citation coverage to writing precise 'contrast sentences' that articulate the technical delta, ensuring the work's novelty is clearly defined relative to neighboring venues like SIGIR and KDD. Ideal for authors refining their technical writing for top-tier conferences.

This skill guides legal scholars through a systematic preemption check to ensure their academic claim is genuinely novel and not covered by prior work. It simulates comprehensive searches across specialized databases like SSRN, Westlaw, HeinOnline, and Google Scholar. The process helps users accurately draft the critical "what's new" contribution paragraph by classifying the relationship between their claim and existing scholarship.

This skill facilitates cross-version symbol migration and binary diffing. When existing symbols or reverse engineering results from an old version need to be quickly mapped to a new binary version, this tool is used. It leverages LLMs to perform structured structural comparisons between corresponding functions in different versions, enabling the programmatic transfer of function names and offsets even when original PDB files are lost. Ideal for kernel debugging, application updates, and binary analysis.

A specialized skill for analyzing client-side persistence mechanisms, including cookies, localStorage, sessionStorage, IndexedDB, and Service Workers. It is crucial for security testing and CTF environments where application behavior or critical decision branches are determined by stored session state, cached data, or local client-side variables. Use this to trace the smallest stateful sequence leading to a decisive outcome.

A specialized downstream skill for complex CTF challenges, focusing on cryptographic analysis, steganography, and mobile system forensics. It guides the user through recovering complex data chains, such as decoding blobs, tracing cryptographic transforms (keys, IVs, nonces), inspecting hidden media payloads, and analyzing mobile trust boundaries (e.g., APK/IPA signing logic, local storage, SSL pinning). This skill is designed to be used only after a main sandbox orchestrator has established the operational context.

A specialized, downstream skill designed for forensic analysis within a confined sandbox environment, particularly for CTF challenges. It guides the user to inspect the full stack behavior, including API interactions, server routing, browser state (cookies, local storage), and asynchronous worker processes. Use this skill to trace complex, end-to-end request flows, debug authentication/session leaks, or diagnose discrepancies between frontend UI and backend enforcement.

This skill facilitates the computation of Electronic Clinical Quality Measures (eCQMs) by leveraging CQL (Clinical Quality Language) logic against the QDM (Quality Data Model). It is designed to extract crucial facts—such as counseling provided, symptoms, or documented exclusions—from unstructured clinical notes. By lifting these facts, it supplements structured EHR data, ensuring that numerators and valid exclusions are accurately captured for quality measure evaluation. Note that this tool augments data capture and does not replace certified measure engines.

A powerful, on-device tool for removing, masking, or replacing sensitive Protected Health Information (PHI/PII) from clinical free text. It ensures patient privacy by running fully locally, supporting methods like masking, hashing, and date shifting. Essential for preparing medical records for safe sharing, storage, or analysis, adhering to standards like HIPAA and GDPR.

This tool analyzes specified source code files or modules to automatically generate comprehensive and structured test suites. It identifies testable units (functions, classes, methods), adheres to project conventions (like AAA pattern), and ensures high coverage for critical scenarios, including happy paths, boundary edge cases, and error handling. It supports popular frameworks such as Jest, Vitest, and pytest.

A comprehensive framework for conducting authorized security assessments on Large Language Models (LLMs) and AI agents. It covers critical vulnerabilities including advanced prompt injection (OWASP Top 10), tool abuse, RAG data poisoning, memory manipulation, and system prompt extraction. Ideal for red teaming, security auditing, and ensuring the robustness of AI systems in production environments.

A comprehensive guide for installing, configuring, and validating the local long-term memory plugin (`memory-tencentdb`) within the OpenClaw environment. This guide covers everything from environment pre-checks to advanced configuration for data capture, information extraction, context recall, and vector embedding, ensuring robust, self-contained memory capabilities for RAG applications.

A sophisticated, multi-agent system designed to perform deep, comprehensive code reviews on pull requests. It covers core elements like code quality, functionality, security vulnerabilities, and testing coverage. Advanced features include detecting scope drift, enforcing SOLID principles, identifying DRY violations, and providing anti-hallucination safeguards for maintain high software integrity.