Skill UI

A specialized cognitive psychology skill designed to engineer highly engaging headlines, subject lines, and titles. It utilizes principles like the curiosity gap, self-relevance, and contrast to create compelling hooks for marketing copy, landing pages, emails, and social media ads. It ensures attention-grabbing power while maintaining ethical guardrails and promise continuity.

As a Cognitive Psychologist, this skill specializes in engineering email subject lines and notification copy that maximize open rates. It applies principles of behavioral psychology, such as the curiosity gap, self-referential processing, and pattern interruption, to create highly engaging and relevant communication triggers. Use this when you need to optimize messaging for specific audience psychographics, sequence stages, and desired emotional responses (e.g., urgency, relevance, curiosity), ensuring the subject line builds genuine interest rather than false hype.

Scans repository context and chat history to recommend awesome-copilot Custom Agent files that are missing or outdated locally, outlines relevance/rationale, and waits for user approval before installing or updating.

This skill enhances research query formulation by translating vague, colloquial, or generalized descriptions into precise, standard academic terminology. When initial search terms are broad (e.g., "conjugal happiness"), this technique suggests multiple plausible academic synonyms (e.g., "marital satisfaction," "relationship quality"). By improving the precision of the search query and incorporating structured constraints (like keywords, years, or sample sizes), it significantly boosts the relevance and effectiveness of academic paper retrieval.

This skill teaches users how to optimize search queries for specific, structural information found within academic theses or dissertations. It emphasizes the critical need to include qualifying terms like "acknowledgment," "thesis," or "dissertation" in searches to successfully retrieve details about committee members, dedicating recipients, or other section-specific data, rather than just topic abstracts. This dramatically improves the relevance and accuracy of information retrieval.

This skill is designed to translate vague, colloquial, or descriptive biological details (such as behaviors, appearances, or cultural uses) into precise scientific or common species names. It is essential for constructing effective search queries in biological databases when the question does not use formal taxonomic names. By accurately identifying candidate species names from descriptive clues, users can drastically improve search relevance and accuracy.

This workflow provides a comprehensive solution for keeping an Algolia search index synchronized with external source data. It covers critical tasks such as full reindexing (zero downtime), efficient partial updates to minimize latency, managing synonyms for better search relevance, and setting up advanced query rules. Ideal for maintaining robust, real-time search capabilities for SaaS applications.

A comprehensive guide to implementing advanced user behavior tracking and real-time data synchronization with Algolia. This guide demonstrates how to use the Insights API to track clicks, conversions, and views, and how to build event-driven pipelines using database change listeners (e.g., Prisma middleware) to keep your Algolia index perfectly synced with your core application data. Essential for deep search analytics and relevance tuning.

Automates the CI/CD process for Glean enterprise search connectors. This tool runs comprehensive unit tests with mocked responses on every Pull Request, and executes integration tests against a staging Glean instance upon merging to the main branch. It validates connector data transforms, indexing API calls, and performs search relevance regression testing to ensure high search quality.

This comprehensive guide details the setup and deployment workflow for Glean enterprise search across development, staging, and production environments. It emphasizes strict environment isolation by managing separate datasources, API tokens, and configurations for each stage. The skill covers best practices for promotion workflows, validation steps, and error handling, ensuring search relevance and data integrity during scaling and updates.

This tool provides comprehensive observability for enterprise search systems (Glean). It tracks critical metrics such as search latency (p95), zero-result query rates, indexing throughput, and stale content ratios. By monitoring connector sync status and detecting indexing degradation, it allows teams to proactively maintain search relevance and ensure sub-second response times, preventing silent data quality decay.

A comprehensive guide to diagnosing and enhancing search relevance within Qdrant. This skill addresses reported issues such as low precision, low recall, or irrelevant matches. It guides users through determining if the problem lies in the embedding model, Qdrant configuration, or the query strategy. Techniques covered include optimizing chunk splitting, tuning HNSW parameters, implementing hybrid search, and utilizing reranking for superior result quality.