Loading…
AWS SageMaker
Build, train, and deploy AI models with deep AWS AI/ML expertise brought directly into your coding assistants, covering the surface area of Amazon SageMaker AI.
Skills19
dataset-evaluationValidates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schem
dataset-transformationGenerates code that transforms datasets between ML schemas for model training or evaluation. Use when the user says "transform", "convert", "reformat", "change the format", or when a dataset's schema needs to change to match the target format — always use this skill for format ch
directory-managementManages project directory setup and artifact organization. Use when starting a new project, resuming an existing one, or when a PLAN.md needs to be associated with a project directory. Creates the project folder structure (specs/, scripts/, notebooks/, manifests/, agent_memory/)
finetuningGenerates code that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, RLVR, and RLAIF trainers, including RLVR Lam
finetuning-techniqueSelects a fine-tuning technique (SFT, DPO, RLVR, or RLAIF) for the user's use case and validates it against the selected model's available recipes. Use when the user has decided to finetune and needs to choose a technique, or when the technique needs to be validated against a mod
Related plugins
SCX AI
Use SCX.ai models directly inside Cherri Code. Generate code, debug, and chat using SCX Coder — fast Australian-hosted models built for agentic workflows and long-context tasks.
Artie
Artie real-time CDC pipelines via MCP
Composio
Connect and operate 1000+ external apps from Cherri Code via the Composio MCP server. Managed OAuth, intelligent tool routing, and a remote sandbox for bulk data processing.AWS Data Analytics
Data lake, analytics, search, and ETL workflows with S3 Tables, AWS Glue, Athena, Amazon Redshift, and Amazon OpenSearch Service. Covers managed Iceberg tables on S3 Tables, ingestion from JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Amazon Redshift, Snowflake, BigQuery, and DynamoDB, AWS Glue Data Catalog inventory and asset discovery, federated Athena queries, vector storage and semantic search on Amazon S3 Vectors, and Amazon OpenSearch Service and Serverless (migration from Solr/Elasticsearch, provisioning, vector/semantic/hybrid search, log analytics, trace analytics).AWS Core
Build, deploy, and operate applications on AWS. Skills to author infrastructure-as-code (CDK, CloudFormation), use core services (Lambda, API Gateway, Step Functions, ECS/Fargate, ECR, IAM, Amazon Bedrock with Knowledge Bases and Guardrails, AWS Blocks), select and operate databases across relational, key-value, document, wide-column, graph, time-series, and in-memory engines (Aurora PostgreSQL/MySQL, Aurora DSQL, RDS, Oracle Database@AWS, DynamoDB, DocumentDB, Keyspaces, Neptune, Timestream, ElastiCache, and MemoryDB), and complete common tasks across observability (CloudWatch, X-Ray, CloudTrail, ADOT), messaging and streaming (SQS, SNS, EventBridge, Kinesis, MSK), AWS SDKs (boto3, JS v3, Swift), and cost optimization.AWS Agents
Build, deploy, and operate AI agents on AWS. Skills for scaffolding agents with Amazon Bedrock AgentCore (Strands, LangGraph), connecting tools via Gateway and MCP, multi-agent and A2A orchestration, memory, Cedar policies, evaluation, observability, debugging traces and logs, and production hardening (inbound auth, IAM, rate limiting, cold-start tuning).