Skill UI

This technique is designed for the final verification stage when analyzing a candidate TV series. Instead of accepting initial matches, users must perform targeted searches combining the show name and specific character details (e.g., birth year, specific plot event, relationship). This ensures that the candidate show satisfies all complex constraints, eliminating false positives and confirming the accuracy of the plot details.

This guide provides comprehensive implementation details for Webflow webhooks. It covers the entire lifecycle, including registering various trigger types (form submissions, new orders, site publishing) via the API. Critically, it teaches how to set up a secure backend endpoint with HMAC signature verification, allowing users to build robust, event-driven workflows that react automatically to user actions within Webflow.

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.

A comprehensive tool for analyzing local business visibility across major map platforms (Google, Bing, Apple, OSM). It provides advanced features including geo-grid rank tracking, Google Business Profile (GBP) auditing, cross-platform review intelligence, NAP verification, and competitor radius mapping. Essential for improving local SEO performance and understanding market share.

This utility serves as a Command Line Interface (CLI) alias for specialized AI code models, specifically mapping to the Claude Code `/pua:yes` command structure. It facilitates structured code generation or interaction by adopting a specific 'yes skill' protocol. It ensures that while switching to an encouragement-first narration, the system maintains strict verification red lines and handles configuration file updates while preserving unknown fields. Ideal for developers needing consistent, protocol-driven AI code assistance.

A comprehensive CI/CD pipeline for Quarkus applications, designed to verify code quality and deployment readiness. It covers all phases: build, static code analysis (SonarQube, Checkstyle), rigorous functional testing (Unit, Integration, API), security scanning (OWASP, dependency checks), native image compatibility testing, performance load testing (K6), and container image validation (Trivy, Grype).

Provides a structured workflow for systematically accessing and analyzing official intellectual property data from the USPTO. This skill covers patent search (PatentSearch API), trademark status checks (TSDR), ownership transfer tracking, and building reproducible IP landscape logs. It is designed for data collection and record verification, emphasizing the use of official APIs and rigorous logging practices. (Warning: Not for legal advice.)

Simulates a comprehensive, multi-stage academic journal peer review process. This agent dynamically configures five expert reviewers (EIC, 3 peers, and a Devil's Advocate) to evaluate a paper across methodology, domain expertise, cross-disciplinary impact, and core arguments. It provides structured reports, editorial decisions, and revision roadmaps, supporting full reviews, post-revision verification, and calibration modes.

A comprehensive orchestrator designed to manage the entire academic research cycle, from initial deep research to final manuscript submission. It guides users through mandatory stages including writing, integrity verification, two-stage peer review, and revision. This skill does not perform the substantive work itself; instead, it tracks state, recommends modes, and dispatches specialized skills (like deep-research and paper formatter) in a reproducible, controlled workflow, ensuring academic rigor at every step.

A comprehensive 13-agent pipeline designed for rigorous, domain-agnostic academic research. It guides the user through the entire research lifecycle, from formulating precise research questions (Socratic mode) and designing methodologies, to conducting systematic literature reviews, performing meta-analyses, source verification, bias assessment, and compiling final APA 7.0 reports. Ideal for academics, researchers, and students needing deep, evidence-based insights on any complex topic.

This powerful tool compares identical tables across two SQL Server instances (e.g., Production vs. Staging). It efficiently detects missing rows, extra columns, schema drifts, and data mismatches. Leveraging Python and Apache Arrow for fast columnar data transfer, it provides a comprehensive reconciliation report, making it essential for data migration validation and ETL verification.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.