What is amazon-bedrock?

A guide for building generative-AI applications with Amazon Bedrock, AWS's service for using and managing foundation models. It covers model calls, document search with Knowledge Bases, agents, safety guardrails, and managed agent workflows.

Use it to call Bedrock models, build RAG systems that retrieve relevant documents before answering, create agents, configure guardrails, and set up Bedrock Knowledge Bases.

It gives current procedures for tasks whose model identifiers and settings can change. It helps connect model use, retrieval, agent behavior, and safety controls in one application.

amazon-bedrock — Skill for Claude Code and Codex by jkomyno/.dotfiles

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add jkomyno/.dotfiles --skill amazon-bedrock

Clone the repo

git clone --depth 1 https://github.com/jkomyno/.dotfiles

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/jkomyno/.dotfiles/amazon-bedrock/github.svg)](https://agentmods.dev/skills/jkomyno/.dotfiles/amazon-bedrock)

Your own site

<a href="https://agentmods.dev/skills/jkomyno/.dotfiles/amazon-bedrock"><img src="https://agentmods.dev/badge/skills/jkomyno/.dotfiles/amazon-bedrock/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/jkomyno/.dotfiles/amazon-bedrock"><img src="https://agentmods.dev/badge/skills/jkomyno/.dotfiles/amazon-bedrock.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 215 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 7,560 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 88% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00215	$0.07560
Opus 5.5	$0.00086	$0.03024
Sonnet 5.5	$0.00043	$0.01512
Haiku 4.5	$0.00021	$0.00756

Measured 5d ago against content hash 672c7628a1b8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

amazon-bedrock scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/fetch_bedrock_agent.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

88% identical to amazon-bedrock — 34 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

target/home/.agents/skills/amazon-bedrock/SKILL.md · 396 lines

How it starts

The opening of the file, as written. The whole thing — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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_skill tool: The skill is not installed on the local filesystem. You MUST fetch each reference or script via retrieve_skill with the file parameter (e.g. file="references/managed-knowledge-bases-setup.md" or file="scripts/fetch_bedrock_agent.py"), and run the script from the returned content. Do NOT file_read these 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.

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)
Common Workflows (includes: Prompt Caching, Quota Health, Cost Tracking, Model Migration)
Troubleshooting
AgentCore Services
Model Selection
Additional Resources

Amazon Bedrock

Overview

Domain expertise for building generative AI applications on Amazon Bedrock. Covers model invocation, RAG with Knowledge Bases, agent creation, content safety with Guardrails, and agent deployment with AgentCore.

Read the full file on GitHub · 396 lines

Files

What ships with it

37 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

5d ago First seen · 396 lines · 215 tokens per session scan A 672c7628a1b8

Subscribe to this mod's changes

amazon-bedrock is a skill published in the GitHub repository jkomyno/.dotfiles (5 stars, last pushed 4d ago), licensed MIT. It adds 215 tokens to every session and 7,560 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to amazon-bedrock, differing in 34 lines, and is treated as a copy.

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