Total 46,718 skills
Showing 12 of 46718 skills
Show status of all features in .dev/. Scans feature folders using parallel agents, generates a status report, and offers to archive completed features.
Shipany AI-powered SaaS boilerplate documentation. Use when working with Shipany framework, Next.js 15, TypeScript, Drizzle ORM, NextAuth, payment integration, or building SaaS applications.
Expertise in Go programming decisions according to the Google Go Style Guide. Focuses on specific choices for naming, error handling, and language usage.
MinIO S3-compatible object storage API. Use this skill for file upload, download, bucket management, and pre-signed URL generation.
Make your AI follow rules and policies. Use when your AI breaks format rules, violates content policies, ignores business constraints, outputs invalid JSON, exceeds length limits, includes forbidden content, or doesn't comply with your specifications. Covers DSPy Assert/Suggest for hard and soft rules, content policies, format enforcement, retry mechanics, and composing multiple constraints.
Checklists and anti-patterns for reviewing Go code. Covers API design, error handling, concurrency, interfaces, safety, performance, naming, testing, functional options, logging, and deterministic simulation 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.
Chain multiple AI steps into one reliable pipeline. Use when your AI task is too complex for one prompt, you need to break AI logic into stages, combine classification then generation, do multi-step reasoning, build a compound AI system, orchestrate multiple models, or wire AI components together. Powered by DSPy multi-module pipelines.
Stop your AI from making things up. Use when your AI hallucinates, fabricates facts, isn't grounded in real data, doesn't cite sources, makes unsupported claims, or you need to verify AI responses against source material. Covers citation enforcement, faithfulness verification, grounding via retrieval, and confidence thresholds.
Scaffold a new AI feature powered by DSPy. Use when adding AI to your app, starting a new AI project, building an AI-powered feature, setting up a DSPy program from scratch, or bootstrapping an LLM-powered backend.
Python performance optimization patterns using profiling, algorithmic improvements, and acceleration techniques. Use when optimizing slow Python code, reducing memory usage, or improving application throughput and latency.
Pull structured data from messy text using AI. Use when parsing invoices, extracting fields from emails, scraping entities from articles, converting unstructured text to JSON, extracting contact info, parsing resumes, reading forms, or any task where messy text goes in and clean structured data comes out. Powered by DSPy extraction.