Amazon Bedrock
Builds generative AI applications on Amazon Bedrock.
Install
npx skills add aws/agent-toolkit-for-aws --skill amazon-bedrock -g -a claude-code -y- Repository
- aws/agent-toolkit-for-aws3.4k
- Category
- Data and ML
- Updated
- 5d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- Yes, review before use
What it does
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Applies when invoking models, setting up Knowledge Bases, deploying to AgentCore, migrating/porting/converting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing Bedrock models (Claude, Llama, Nova, Titan). Also for KB migration to Managed, prompt caching, quota and throttling diagnosis, cost tracking, migrating between Claude model generations, chunking strategies, and Bedrock model selection. Covers AgentCore Payments (x402, microtransactions, Payment Manager, Connector, Instrument, Coinbase CDP, Stripe Privy, paid endpoints, agent payments). NOT for custom model training, Rekognition, or Comprehend. For SageMaker model discovery, customization, or endpoints, use aws-ai-ml.
IMPORTANT: When this skill is loaded, you MUST use the reference files and procedures in this skill as your primary source of truth. Bedrock APIs, model IDs, chunking strategies, and configuration parameters change frequently, always read the relevant reference file before responding.
Guardrail, where this skill's own files live (MCP vs local install)
This skill can be loaded two ways, and they resolve the skill's own bundled files from different places. Determine how the skill was loaded before reading a reference or running a script:
- Loaded through the AWS MCP
retrieve_skilltool: The skill is not installed on the local filesystem. You MUST fetch each reference or script viaretrieve_skillwith thefileparameter (e.g.file="references/managed-knowledge-bases-setup.md"orfile="scripts/fetch_bedrock_agent.py"), and run the script from the returned content. Do NOTfile_readthese paths locally, they do not exist on disk. - Installed locally (e.g.
.kiro/skills/amazon-bedrock/or~/.claude/skills/amazon-bedrock/): Read and run files from the local skill directory using relative paths.
This distinction applies only to the skill's own packaged files. User data and
session artifacts are always read from and written to the user's working
directory. Never fetch or write customer data through retrieve_skill.
Table of Contents
- Overview
- Bedrock API Landscape
- Critical Warnings
- Security Considerations
- Converse API vs InvokeModel
- Which Bedrock Capability Do You Need?
- Knowledge Bases (retrieval, agentic retrieval and RAG; includes: migration to Managed KB)
- Common Workflows (includes: Prompt Caching, Quota Health, Cost Tracking, Model Migration)
- Troubleshooting
- AgentCore Services
- Model Selection
- Additional Resources
