sales-call-prep-assistant
Generate pre-call research briefs with company news, stakeholder backgrounds, and custom discovery question sets.
Generate pre-call research briefs with company news, stakeholder backgrounds, and custom discovery question sets.
Text embeddings for semantic search and similarity. Use when converting text to vectors, choosing embedding models, implementing chunking strategies, or building document similarity features.
Query decomposition for multi-concept retrieval. Use when handling complex queries spanning multiple topics, implementing multi-hop retrieval, or improving coverage for compound questions.
Reranking patterns for improving search precision. Use when implementing cross-encoder reranking, LLM-based relevance scoring, or improving retrieval quality in RAG pipelines.
Advanced RAG with Self-RAG, Corrective-RAG, and knowledge graphs. Adaptive retrieval, document grading, query rewriting, web fallback. Use when building self-correcting retrieval systems.
LLM output evaluation and quality assessment. Use when implementing LLM-as-judge patterns, quality gates for AI outputs, or automated evaluation pipelines.
LLM evaluation and testing patterns including prompt testing, hallucination detection, benchmark creation, and quality metrics. Use when testing LLM applications, validating prompt quality, implementing systematic evaluation, or measuring LLM performance.
HyDE (Hypothetical Document Embeddings) for improved semantic retrieval. Use when queries don't match document vocabulary, retrieval quality is poor, or implementing advanced RAG patterns.
LLM guardrails with NeMo, Guardrails AI, and OpenAI. Input/output rails, hallucination prevention, fact-checking, toxicity detection, red-teaming patterns.
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
Extract key concepts from any content and create spaced-repetition flashcards. Multiple formats: Anki-compatible, printable PDFs, interactive web.
Aggregate and analyze customer reviews from G2, Capterra, Trustpilot, App Store, and other platforms. Performs sentiment analysis, identifies pain points, extracts feature feedback, generates marketing claims, and compares competitor reviews. Use when users need review analysis, competitive intelligence, or customer feedback insights.
Activates when querying environmental data from GCS. Use this skill for: pesticides, nitrogen leaching, BNBO drinking water protection, wetlands, soil types, environmental compliance, biodiversity. Keywords: miljø, environment, pesticide, pesticid, nitrogen, kvælstof, BNBO, wetlands, vådomr, soil, jord, biodiversity
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file
Build and operate an AI astrology assistant that calculates birth charts, planetary positions, houses, and aspects using Swiss Ephemeris logic. Use when creating natal charts, birth chart calculators, astrology APIs, horoscope bots, or interpreting planetary positions.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
奇异植物 - Stella深入研究盖亚星球的植物生态,发现既美丽又危险的外星植被,并尝试找到可利用的资源
信号塔修复 - Stella尝试修复或建造信号发射装置,希望联系地球或发送求救信号
古代遗迹 - Stella深入探索盖亚星球的古代文明遗迹,解开失落文明的秘密
紧急求救 - 飞船坠毁后与Stella的首次联系,帮助她评估损伤并制定初步生存计划
洞穴探险 - Stella发现一个深邃的洞穴系统,深入探索发现bioluminescent晶体、地下水源和神秘的古老痕迹