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Found 1,865 Skills
Manage sub-accounts for reseller and enterprise scenarios. This skill provides Ruby SDK examples.
Email engagement tracking for sales — open tracking, click tracking, attachment views, real-time notifications, follow-up timing, and engagement analytics. Use when setting up email tracking, interpreting open/click data, Mixmax tracking, Woodpecker tracking, timing follow-ups based on engagement, understanding tracking limitations (Apple MPP, pixel blocking), Reply.io tracking, or choosing a tracking tool. For Yesware-specific help, use /sales-yesware. Do NOT use for email deliverability (use /sales-deliverability), cadence design (use /sales-cadence), or buying intent signals beyond email (use /sales-intent).
Use this skill when you receive a 402 Payment Required response that contains an `agentkit` extension. Covers checking 402 responses for the AgentKit extension before paying, constructing and signing a CAIP-122 challenge (SIWE for EVM, SIWS for Solana), sending the signed `agentkit` HTTP header, and interpreting access modes (free, free-trial, discount). Supports both EOA wallets (EIP-191) and Smart Contract Wallets (ERC-1271, e.g. Coinbase Smart Wallet, Safe).
Performs advanced network reconnaissance using Nmap's scripting engine, timing controls, evasion techniques, and output parsing to discover hosts, enumerate services, detect vulnerabilities, and fingerprint operating systems across authorized target networks.
Adds an "AI Summary Request" footer component with clickable AI platform icons (ChatGPT, Claude, Gemini, Grok, Perplexity) that pre-populate prompts for users to get AI summaries of the website. Optionally creates an llms.txt file for enhanced AI discoverability. Use when users want to add AI platform integration buttons or make their website AI-friendly.
Query the official CrewAI documentation for answers. Use when the user has a CrewAI question that isn't fully covered by the getting-started, design-agent, design-task skills — e.g., specific API details, configuration options, advanced features, troubleshooting errors, enterprise features, tool references, or anything where the latest docs are the best source of truth.
This skill should be used when the user asks "where should I put this", "can X import from Y", "Angular folder structure", mentions feature isolation, lazy loading placement, dependency violations, architecture audit, circular dependency, import cycle, barrel file, bundle size, initial load performance, signal store placement, state management, or when creating/moving Angular components, services, or modules between folders. Also use when reviewing PRs for architectural compliance, scaffolding new features, or setting up eslint-boundaries. Angular enterprise architecture advisor for placement decisions, dependency rules, isolation patterns, and architectural verification.
XSLT injection testing: processor fingerprinting, XXE and document() SSRF, EXSLT write primitives, PHP/Java/.NET extension RCE surfaces. Use when user-controlled XSLT/stylesheet input or transform endpoints are in scope.
Use when computing orbits, planning maneuvers, propagating trajectories, or analyzing orbital perturbations for spacecraft or celestial bodies. Use when "orbit, trajectory, maneuver, delta-v, Hohmann, Keplerian, perturbation, J2, TLE, orbital elements, semi-major axis, eccentricity, inclination, RAAN, spacecraft propagation, Lambert solver, interplanetary, " mentioned.
Apply when implementing order integration hooks, feeds, or webhook handlers for VTEX marketplace connectors. Covers Feed v3 (pull) vs Hook (push), filter types (FromWorkflow and FromOrders), order status lifecycle, payload validation, and idempotent processing. Use for building order integrations between VTEX marketplaces and external systems such as ERPs, WMS, or fulfillment services.
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.
Reference knowledge for Markuplint HTML linter. Covers violation interpretation, CLI usage, config patterns, and documentation URLs. Auto-loaded when working with HTML linting.