heyreach-automation
skill collectioncomposiohq/awesome-claude-skillscomposio-skills/heyreach-automation/SKILL.md
Automate Heyreach tasks via Rube MCP (Composio). Always search tools first for current schemas. (SKILL.md metadata excerpt)
Compare the method, check the prerequisites, then go to the exact source.
composiohq/awesome-claude-skillscomposio-skills/heyreach-automation/SKILL.md
Automate Heyreach tasks via Rube MCP (Composio). Always search tools first for current schemas. (SKILL.md metadata excerpt)
composiohq/awesome-claude-skillscomposio-skills/heyzine-automation/SKILL.md
Automate Heyzine tasks via Rube MCP (Composio). Always search tools first for current schemas. (SKILL.md metadata excerpt)
huggingface/skillsskills/hf-cli/SKILL.md
Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging (SKILL.md metadata excerpt)
huggingface/skillsskills/hf-cloud-aws-context-discovery/SKILL.md
Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this (SKILL.md metadata excerpt)
sickn33/agentic-awesome-skillsskills/hf-cloud-aws-context-discovery/SKILL.md
Discover the effective local AWS profile, region, account, and caller identity before any AWS task without exposing credentials. (SKILL.md metadata excerpt)
huggingface/skillsskills/hf-cloud-python-env-setup/SKILL.md
Set up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill (SKILL.md metadata excerpt)
huggingface/skillsskills/hf-cloud-sagemaker-deployment-planner/SKILL.md
Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, (SKILL.md metadata excerpt)
huggingface/skillsskills/hf-cloud-sagemaker-iam-preflight/SKILL.md
Ensure a usable SageMaker execution role exists before deploying or training. Use this skill whenever about to create a SageMaker endpoint, model, (SKILL.md metadata excerpt)
huggingface/skillsskills/hf-cloud-sagemaker-production-defaults/SKILL.md
Create a SageMaker endpoint (real-time, real-time scale-to-zero, or async) with autoscaling, CloudWatch alarms, and tagging enabled by default. Use this skill whenever (SKILL.md metadata excerpt)
huggingface/skillsskills/hf-cloud-serving-image-selection/SKILL.md
Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to (SKILL.md metadata excerpt)
sickn33/agentic-awesome-skillsskills/hf-mcp/SKILL.md
Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and (SKILL.md metadata excerpt)
sickn33/agentic-awesome-skillsskills/hf-mem/SKILL.md
Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub (SKILL.md metadata excerpt)
Snapshot w7-discovery-20260912 · 8364 file observations across 30 repositories. Source collection is not a quality or safety assessment.