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llm-to-bedrock

Skill

Use when the user wants to migrate code that calls OpenAI, Gemini/Google AI, or the Anthropic API to Amazon Bedrock — a pure model/SDK rewrite. End-to-end: assesses the codebase, then rewrites SDK calls, evaluates output quality against Bedrock, and delivers a ready-to-merge git branch. Not for: age

0Cloud

Install

git clone https://github.com/awslabs/startups.git ~/.claude/skills/llm-to-bedrock

What is llm-to-bedrock?

Use when the user wants to migrate code that calls OpenAI, Gemini/Google AI, or the Anthropic API to Amazon Bedrock — a pure model/SDK rewrite. End-to-end: assesses the codebase, then rewrites SDK calls, evaluates output quality against Bedrock, and delivers a ready-to-merge git branch. Not for: agent runtime selection, agentic architecture decisions, or agent migration planning — use agent-advisor for those. Not for standalone Bedrock cost estimates or infrastructure-only migration. The Assess phase is handled by this plugin's own gcp-to-aws skill.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~139 tokens of context used while enabled, before you invoke anything

Documentation

README · ~17 min read

Migrate to Bedrock (Assess + Execute)

Single-command AI migration: OpenAI / Gemini / Anthropic → Amazon Bedrock.

The skill base directory is given in the "Base directory for this skill: X" line the harness emits at load time. Call it <SKILL_BASE>. Derived paths:

  • $SCRIPTS = <SKILL_BASE>/scripts
  • $HELPERS = <SKILL_BASE>/references/helpers (the former helper skills, now references)

Step 0 — Check prerequisites

0a. Check that uv is available

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