Skill UI

PIP kicks in when tasks fail repeatedly or the assistant becomes passive, layering Western big-tech performance rhetoric, a systematic debugging methodology, and proactivity enforcement so every code, ops, research, deployment, or writing task is owned, verified, and driven to completion.

An advanced, AI-powered agent designed to generate comprehensive and workable unit tests for virtually any programming language (e.g., Python, C#, Java, Go, TypeScript). It operates via a sophisticated multi-agent pipeline (Research → Plan → Implement → Build → Test → Fix → Lint). This ensures generated tests are not only written following project conventions but also compile, pass all tests, and effectively improve code coverage.

A sophisticated, file-based system designed for organizing and tracking complex, multi-step projects. It utilizes structured Markdown files (task_plan.md, progress.md, findings.md) to maintain a complete record of plans, research findings, and progress updates. Ideal for project analysis, workflow management, and ensuring data integrity throughout the planning lifecycle.

This file-based system provides a structured method for organizing and tracking the progress of complex, multi-stage projects or extensive research tasks. It automatically generates and manages key files like `task_plan.md`, `findings.md`, and `progress.md`. It is ideal for users needing to deconstruct, plan, and maintain comprehensive visibility over large, complex workflows, supporting automatic session recovery and integrity checks.

Generates professional conference presentation slides from a compiled research paper. This skill produces dual outputs: a polished Beamer LaTeX PDF for high-quality typesetting, and an editable PPTX for flexible adjustments. It supports multiple talk types (Poster, Spotlight, Oral, Invited) and includes detailed guidelines for speaker notes and talk scripting, making it essential for academic researchers preparing for major ML and systems conferences.

A persistent, graph-based knowledge base designed to accumulate structured knowledge throughout the entire research lifecycle. It stores and connects diverse entities—including published papers, novel ideas, conducted experiments, and testable claims. Inspired by LLM Wiki patterns, it ensures knowledge compounding, meaning the wiki becomes progressively smarter with every piece of input, rather than requiring re-derivation for every query.

This comprehensive tool provides real-time, live SEO data directly from the DataForSEO platform. It allows users to analyze live SERPs (Google, YouTube), conduct deep keyword research (volume, difficulty, intent), monitor backlink profiles, analyze competitor domains, and perform on-page content audits. It is crucial for digital marketers and content creators who need up-to-date metrics, especially for tracking AI visibility and LLM mentions, moving beyond static best practices.

This guide details advanced techniques for searching cricket matches by leveraging precise numerical scoring data. Instead of broad terms, users should utilize specific details—such as team totals (e.g., 168/9), runs off balls, wickets taken, or over details—combined with the match type and year to create highly targeted search queries. This method significantly improves search accuracy and efficiency when researching sports statistics.

This technique is used when the required answer in a case query is not directly stated but must be deduced by following a sequence of connected roles, people, or events. It involves mapping complex relationships, such as Victim -> Defendant -> Lawyer -> Witness, to trace indirect connections and reach the final piece of information. Ideal for advanced investigative research and deep knowledge graph traversal.

This technique guides users on decomposing multi-constraint questions, especially in the domain of football trivia or historical research. Instead of searching all criteria simultaneously, it instructs users to rank constraints by distinctiveness (e.g., specific match results first, then historical milestones). By performing incremental, cascading searches, the system dramatically narrows down the result set, leading to more accurate information retrieval.

This technique allows users to locate game developers or projects indirectly by searching for highly distinctive biographical details. Instead of relying on game databases, it leverages unique phrases, historical events, or personal lifestyle details found in interviews, blogs, or conference talks. It is invaluable when the developer's identity is obscured, requiring deep research using exact-match queries on obscure information.

This guide details advanced search techniques for researching musical artists from non-Western regions, including K-pop, Middle Eastern, African, and Latin American genres. It instructs users on moving beyond standard English search terms by incorporating regional keywords, cultural identifiers (like UN Ambassador status), specific platforms (e.g., Coke Studio), and systematic regional branching to find comprehensive information.