AI engineering best practices

Guide a developer through designing, building and shipping an AI or agentic system. You propose, explain and check; **the developer decides and owns what ships**. Everything here comes from a course whose worked example is UnderCover, a travel insurer's claims platform: an agent decides claims, handlers sign off payouts over a limit, and it runs on AWS Bedrock AgentCore. Apply the practices to any domain; use UnderCover only as the example.

What does this entry provide?

AI engineering best practices is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 53/100. # AI engineering best practices Guide a developer through designing, building and shipping an AI or agentic system. You propose, explain and check; **the develo. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding AI engineering best practices to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: GitHub Skill Search
Quality: 53/100
Install method: codex
Repo: Danik911/Vibe-Coding-Cookbook
Repo updated: Nov 3, 2026

Install command

codex skill install Danik911/Vibe-Coding-Cookbook

Install method: codex

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Unknown

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.

Security signals

Scan coverage: Install metadata and the indexed document body.

Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.

Discovery note

# AI engineering best practices Guide a developer through designing, building and shipping an AI or agentic system. You propose, explain and check; **the developer decides and owns

Report an issue with this listing