Loading...
Loading...
Found 705 Skills
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.
Reads open review comments from a GitHub PR, triages them, applies code fixes, and drafts reply messages. Use when user wants to address PR comments, says 'address review comments', 'fix PR feedback', 'handle PR comments', 'respond to review', or mentions addressing code review feedback on a pull request.
Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.
Replicate integration. Manage data, records, and automate workflows. Use when the user wants to interact with Replicate data.
Single entry point for all AEM 6.5 LTS Replication skills. Covers configuring replication agents, activating/deactivating content, using the Replication API programmatically, and troubleshooting distribution issues for Adobe Experience Manager 6.5 LTS.
Use these skills when you need to monitor replication health, manage sync states between nodes, and ensure the high availability and data distribution of your AlloyDB cluster.
Package and build custom AI models with Cog for deployment on Replicate. Use when creating a cog.yaml or predict.py, defining model inputs and outputs, loading model weights at setup time, building Docker images for ML models, serving locally with cog serve or cog predict, or porting a HuggingFace, GitHub, or ComfyUI model to run on Replicate. Trigger on phrases like "build a model", "package a model", "create a Cog model", "wrap a model", "containerize an AI model", "predict.py", "cog.yaml", "BasePredictor", or "Cog container", and when referencing cog.run, github.com/replicate/cog, or github.com/replicate/cog-examples. Covers GPU and CUDA setup, pget for fast weight downloads, async predictors with continuous batching, streaming outputs, and cold-boot optimization for image, video, audio, and LLM models. For pushing built models to Replicate, see publish-models. For running existing models, see run-models.
Use Replay MCP to inspect the contents of https://replay.io recordings.
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.
Provides comprehensive guidance for Parcel bundler including zero-configuration setup, asset handling, hot module replacement, and production builds. Use when the user asks about Parcel, needs to set up a build tool quickly, or work with Parcel's automatic configuration.
Operate and evolve agent-memory-workbench with replay-first memory, minimal JSON edits, and a strict two-branch policy (normal + human-verification).
A micro-prompt that reminds the agent that it is an interactive programmer. Works great in Clojure when Copilot has access to the REPL (probably via Backseat Driver). Will work with any system that has a live REPL that the agent can use. Adapt the prompt with any specific reminders in your workflow and/or workspace.