Loading...
Loading...
Found 5,849 Skills
Diagnose and fix common FiftyOne issues automatically. Use when a dataset disappeared, the App won't open, changes aren't saving, MongoDB errors occur, video codecs fail, notebook connectivity breaks, operators are missing, or any recurring FiftyOne pain point needs solving.
Ultra-lightweight AI assistant in Go that runs on $10 hardware with <10MB RAM, supporting multiple LLM providers, tools, and single-binary deployment across RISC-V, ARM, MIPS, and x86.
Decision-first data analysis with statistical rigor gates. Use when analyzing CSV, JSON, database exports, API responses, logs, or any structured data to support a business decision. Handles: trend analysis, cohort comparison, A/B test evaluation, distribution profiling, anomaly detection. Do NOT use for codebase analysis (use codebase-analyzer), codebase exploration (use explore-pipeline), or ML model training.
Statistical rule discovery through measurement of Go codebases: Count patterns, derive confidence-scored rules, produce Style Vector fingerprint. Use when analyzing codebase conventions, extracting implicit coding rules, profiling a repo before onboarding or PR automation. Use for "analyze codebase", "find coding patterns", "what conventions does this repo use", "extract rules", or "codebase DNA". Do NOT use for code review, bug fixes, refactoring, or performance optimization.
Use when creating viral content on Xiaohongshu, optimizing posts for maximum reach and engagement, analyzing what makes posts go viral, replicating viral success patterns, or aiming to create breakthrough content that reaches beyond existing audience
Extract design DNA from existing app screenshots or live URLs using Google Stitch. Produces color palettes, typography specs, spacing tokens, and component patterns as design-tokens.json or Tailwind config. Use when auditing an existing design, creating a design system from a live app, or ensuring new pages match an established visual identity.
Expert knowledge for Azure US Government development including decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when handling FedRAMP/DoD IL5 scope, SACA patterns, Gov CI/CD, Gov Marketplace, or sovereign APIs, and other Azure US Government related development tasks. Not for Azure Local (use azure-local), Azure Arc (use azure-arc), Azure Networking (use azure-networking), Azure Security (use azure-security).
Flutter cross-platform development guide covering widget patterns, Riverpod/Bloc state management, GoRouter navigation, performance optimization, and platform-specific implementations. Includes const optimization, responsive layouts, testing strategies, and DevTools profiling. Use when: building Flutter apps, implementing state management (Riverpod/Bloc), setting up GoRouter navigation, creating custom widgets, optimizing performance, writing widget tests, cross-platform development.
Personal finance CLI for tracking income, expenses, accounts, budgets, and savings goals. Use when the user wants to manage personal finances, track spending, set budgets, or analyze financial data. Install via npx finance-cli. All commands support --json for structured output.
Designs structured benchmarks for comparing algorithms, models, or implementations. Selects appropriate metrics (latency, throughput, memory, accuracy), designs representative test cases, captures hardware/software context, produces comparison tables with tradeoff analysis, and includes reproduction instructions. Triggers on: "benchmark", "compare performance", "which is faster", "latency comparison", "memory comparison", "run benchmark", "design benchmark", "compare implementations", "evaluate algorithms", "performance comparison", "throughput test", "speed test". Use this skill when comparing two or more implementations, algorithms, or models.
Use this skill whenever deciding what features to extract from raw marketplace assets — listing photos, owner-entered listing metadata, sitter wizard responses — to power item-to-item (similar listings), user-to-item (homefeed ranking), or user-to-user (mutual-fit matching) recommenders in a two-sided trust marketplace. Covers asset auditing, first-principles feature decomposition from the decision the user is making, vision-feature extraction (CLIP, room-type classification, amenity detection, aesthetic and quality scoring), listing text and metadata encoding (categoricals, multi-hot amenities, H3 geo-hashing, sentence-transformer description embeddings, structured pet triples), sitter wizard design (information-gain ordering, multiple-choice over free text, genuine skippability, hard constraint versus soft preference), derived-composition patterns for i2i / u2i / u2u (precomputed ANN shelves, multi-modal fusion, two-tower affinity, symmetric mutual-fit scoring, interpretable subscores), feature quality governance (single registry, training-serving parity, coverage and drift alarms, PII scrubbing, schema versioning), and incremental value proof (one feature at a time, ablation A/B, kill reviews, exploration slice, permanent feature-free baseline). Trigger even when the user does not explicitly say "feature engineering" but is asking how to get more signal out of listing photos, listing metadata, or the sitter onboarding wizard, or how to improve i2i / u2i / u2u quality without blindly ingesting a new model.
Apply classical rhetoric — Ethos, Pathos, Logos — to analyze persuasive communication and craft effective arguments. Use this skill when the user needs to make a speech more persuasive, analyze why a piece of communication is effective, write a compelling proposal, or evaluate rhetorical strategies — even if they say 'make this more convincing', 'why is this speech so powerful', or 'how do I persuade the board'.