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Found 683 Skills
This skill provides comprehensive guidance for using the Replicate CLI to run AI models, create predictions, manage deployments, and fine-tune models. Use this skill when the user wants to interact with Replicate's AI model platform via command line, including running image generation models, language models, or any ML model hosted on Replicate. This skill should be used when users ask about running models on Replicate, creating predictions, managing deployments, fine-tuning models, or working with the Replicate API through the CLI.
Modifies DAG structure during execution in response to failures, new requirements, or runtime discoveries. Supports node insertion, removal, and dependency rewiring. Activate on 'replan dag', 'modify workflow', 'add node', 'remove node', 'dynamic modification'. NOT for initial DAG building (use dag-graph-builder) or scheduling (use dag-task-scheduler).
Build, integrate, and troubleshoot SharePlay GroupActivities features, including GroupActivity definitions, activation flows, GroupSession lifecycle, messaging and journals, ShareLink and SharePlay UI surfaces, and visionOS spatial coordination. Use when implementing or debugging SharePlay experiences across Apple platforms, especially visionOS.
Generate audio replies using TTS. Trigger with "read it to me [URL]" to fetch and read content aloud, or "talk to me [topic]" to generate a spoken response. Also responds to "speak", "say it", "voice reply".
Classify a batch of influencer replies into actionable categories (interested, negotiating, declined, needs info, ghosted) and generate a suggested next action for each. This skill should be used when triaging creator responses, classifying influencer replies, sorting outreach responses, categorizing creator DMs, reviewing batch replies, processing influencer inbox, prioritizing creator follow-ups, organizing outreach results, checking who replied to a campaign, figuring out which creators to follow up with, or cleaning up a messy outreach thread. For writing the initial outreach messages, see outreach-writer. For negotiating rates with creators, see rate-negotiation-playbook.
Summarize a chat and draft 2 reply options. Stops before sending.
Эксперт DB replication. Используй для настройки репликации MySQL, PostgreSQL, MongoDB, failover и high availability.
Developer machine tool for replicating plugin source code between local project repositories. Use when you want to push plugin updates from agent-plugins-skills to a consumer project, or pull the latest plugins into a consumer project from this central repo. Works with explicit --source and --dest paths; supports additive-update (default), --clean (also removes deleted files), --link (symlink), and --dry-run modes.
When the user wants to design or optimize replenishment strategies, determine replenishment policies, or improve inventory flow between locations. Also use when the user mentions "inventory replenishment," "stock replenishment," "min-max inventory," "DRP," "auto-replenishment," "vendor-managed inventory," "forward pick replenishment," or "retail store replenishment." For safety stock calculations, see inventory-optimization. For multi-echelon networks, see multi-echelon-inventory.
Enable a Gmail out-of-office auto-reply with a custom message and date range.
Iteratively improves a PR until Greptile gives it a 5/5 confidence score with zero unresolved comments. Triggers Greptile review, fixes all actionable comments, pushes, re-triggers review, and repeats. Use when the user wants to fully optimize a PR against Greptile's code review standards.
Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.