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Found 60 Skills
Use this skill whenever building, reviewing, or refactoring React components that fetch data from APIs — especially at scale (recommender carousels, infinite feeds, pages with many parallel fetches, dashboards). Covers request orchestration (parallelism, batching, deduplication), cache strategy (keys, normalization, staleTime, SWR), backend protection (concurrency caps, debounce/throttle, jittered retries, circuit breakers), prefetching (route loaders, hover/intent, idle, server hydration), failure resilience (AbortController, timeouts, error boundaries, stale fallback, idempotent mutations), and feed/carousel patterns (virtualization, cursor pagination, summary/detail split). Trigger even if the user doesn't explicitly mention "performance" or "scale" — any non-trivial React data-fetching code benefits from these patterns. Includes 5 ready-to-use scaffolding templates (resource query hook, carousel data loader, infinite feed, hover-prefetch link, request collapser).
Save structured content to Obsidian vault with standardized frontmatter, folder routing, deduplication, and wikilink generation. Persists res-deep research, res-price-compare reports, and generic content. Use when: saving to vault, persisting results, store in obsidian. Triggers: save to vault, vault save, persist this, save research, store in vault, update vault note.
DEFAULT search tool for ALL search/lookup needs. Multi-source search and deduplication layer with intent-aware scoring. Integrates Brave Search (web_search), Exa, Tavily, and Grok to provide high-coverage, high-quality results. Automatically classifies query intent and adjusts search strategy, scoring weights, and result synthesis. Use for ANY query that requires web search — factual lookups, research, news, comparisons, resource finding, "what is X", status checks, etc. Do NOT use raw web_search directly; always route through this skill.
Fetch journal articles from Crossref published after a user-specified date and insert them into PostgreSQL `journals` with DOI deduplication. Use when incrementally ingesting journal metadata from `journals_issn` into `journals`.
Expert B2B list building orchestrator for outbound sales campaigns. Use when the user asks about building lead lists, Sales Navigator search, boolean filters, ICP definition, ICP scoring, lead sources, data validation, email verification, list segmentation, Apollo prospecting, Clay Find People, list hygiene, deduplication, account qualification, ABM lists, or assembling prospect lists for cold outreach. Also triggers on "lead list", "list building", "Sales Navigator", "boolean search", "ICP", "ideal customer profile", "find leads", "prospect list", "lead source", "email verification", "data validation", "list hygiene", "Evaboot", "PhantomBuster", "export leads", "build a list", "find prospects", "deduplicate", "qualify accounts", "ABM". Do NOT use for enrichment workflows (use clay skill) or email writing (use cold-email skill).
Implement Nostr client architecture including relay pool management, subscription lifecycle with EOSE/CLOSED handling, event deduplication, optimistic UI for publishing, and reconnection strategies. Use when building Nostr clients, managing WebSocket relay connections, handling subscription state machines, implementing event caches, or debugging relay communication issues like missed events or broken reconnections.
Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.
Cosmos-Embed1 video-text embedding for text-to-video retrieval, video-to-video search, semantic deduplication, and fine-tuning. Use when the user asks to "fine-tune Cosmos-Embed1", "run cosmos-embed inference", "export Cosmos-Embed1", "embed videos", or "search videos with text".
Design and operate an advanced AI agent memory system on HelixDB using hybrid graph + vector + BM25 search. Use when building long-term memory, user profiles, document/chunk RAG, recall/remember features, memory extraction, deduplication, consolidation, versioning, updating, forgetting/deletion, categorisation, or connector-backed ingestion. Covers tenant-safe Helix data modeling, modality decision rules, the full write/maintain lifecycle, and the product layers an agent must implement around Helix. TypeScript-first (@helix-db/helix-db); a Rust DSL variant is in EXAMPLES.rust.md.
Event deduplication with canonical selection, reputation scoring, and hash-based grouping for multi-source data aggregation. Handles both ID-based and content-based deduplication.
Multi-source search and deduplication layer with intent-aware scoring. Integrates Brave Search (web_search), Exa, Tavily, and Grok to provide high-coverage, high-quality results. Automatically classifies query intent and adjusts search strategy, scoring weights, and result synthesis accordingly. Activated for "deep search", "multi-source search", or when high-quality research is needed.
Integrate multiple plot point analysis results into a comprehensive report, and generate high-quality analysis through deduplication, classification, sorting, and summarization. Suitable for integrating multiple analysis sources and generating unified reports