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Found 17 Skills
Verify and validate AI output before it reaches users. Use when you need guardrails, output validation, safety checks, content filtering, fact-checking AI responses, catching hallucinations, preventing bad outputs, quality gates, or ensuring AI responses meet your standards before shipping them. Covers DSPy assertions, verification patterns, and generate-then-filter pipelines.
Condense long content into short summaries using AI. Use when summarizing meeting notes, condensing articles, creating executive briefs, extracting action items, generating TL;DRs, creating digests from long threads, summarizing customer conversations, or turning lengthy documents into bullet points. Powered by DSPy summarization.
Generate articles, reports, blog posts, or marketing copy with AI. Use when writing blog posts, creating product descriptions, generating newsletters, drafting reports, producing marketing copy, creating documentation, writing email campaigns, or any task where AI writes long-form content from a topic or brief. Powered by DSPy content generation pipelines.
Generate synthetic training data when you don't have enough real examples. Use when you're starting from scratch with no data, need a proof of concept fast, have too few examples for optimization, can't use real customer data for privacy or compliance, need to fill gaps in edge cases, have unbalanced categories, added new categories, or changed your schema. Covers DSPy synthetic data generation, quality filtering, and bootstrapping from zero.
Reduce your AI API bill. Use when AI costs are too high, API calls are too expensive, you want to use cheaper models, optimize token usage, reduce LLM spending, route easy questions to cheap models, or make your AI feature more cost-effective. Covers DSPy cost optimization — cheaper models, smart routing, per-module LMs, fine-tuning, caching, and prompt reduction.
Auto-sort, categorize, or label content using AI. Use when sorting tickets into categories, auto-tagging content, labeling emails, detecting sentiment, routing messages to the right team, triaging support requests, building a spam filter, intent detection, topic classification, or any task where text goes in and a category comes out.
Fine-tune models on your data to maximize quality and cut costs. Use when prompt optimization hit a ceiling, you need domain specialization, you want cheaper models to match expensive ones, you heard "fine-tuning will make us AI-native", you have 500+ training examples, or you need to train on proprietary data. Covers DSPy BootstrapFinetune, BetterTogether, model distillation, and when to fine-tune vs optimize prompts.
This skill should be used when the user asks to "build a RAG pipeline", "create retrieval augmented generation", "use ColBERTv2 in DSPy", "set up a retriever in DSPy", mentions "RAG with DSPy", "context retrieval", "multi-hop RAG", or needs to build a DSPy system that retrieves external knowledge to answer questions with grounded, factual responses.
Measure and improve how well your AI works. Use when AI gives wrong answers, accuracy is bad, responses are unreliable, you need to test AI quality, evaluate your AI, write metrics, benchmark performance, optimize prompts, improve results, or systematically make your AI better. Covers DSPy evaluation, metrics, and optimization.
Find every way users can break your AI before they do. Use when you need to red-team your AI, test for jailbreaks, find prompt injection vulnerabilities, run adversarial testing, do a safety audit before launch, prove your AI is safe for compliance, stress-test guardrails, or verify your AI holds up against adversarial users. Covers automated attack generation, iterative red-teaming with DSPy, and MIPROv2-optimized adversarial testing.
Score, grade, or evaluate things using AI against a rubric. Use when grading essays, scoring code reviews, rating candidate responses, auditing support quality, evaluating compliance, building a quality rubric, running QA checks against criteria, assessing performance, rating content quality, or any task where you need numeric scores with justifications — not just categories.
Auto-moderate what users post on your platform. Use when you need content moderation, flag harmful comments, detect spam, filter hate speech, catch NSFW content, block harassment, moderate user-generated content, review community posts, filter marketplace listings, or route bad content to human reviewers. Covers DSPy classification with severity scoring, confidence-based routing, and Assert-based policy enforcement.