gedd

A coaching command for creating a trusted evaluation dataset for an AI agent, deploying the agent, and handing the result to an ML engineer for production use with SageMaker and MLflow.

In plain words
What is it for?
Use it to build labeled evaluation data, deploy the agent, and prepare it for a SageMaker machine-learning pipeline tracked with MLflow.
Why use it?
It organizes the handoff from domain experts to machine-learning engineers and makes the required stages explicit.

Command for Claude Code

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.

agentmods
npx agentmods add commands/aws-samples/sample-gedd/gedd
Clone the repo
git clone --depth 1 https://github.com/aws-samples/sample-GEDD

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,710 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found 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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01710
Opus 5 $0.00000 $0.00855
Sonnet 5 $0.00000 $0.00342
Haiku 4.5 $0.00000 $0.00171

Measured 2d ago against content hash dd220ef06e94, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gedd 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 2d ago.

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.

grounded-evals/.claude/commands/gedd.md · 217 lines

The source is not reproduced here

Licensed MIT-0

The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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.

  1. 2d ago First seen · 217 lines · 0 tokens per session scan A dd220ef06e94

Subscribe to this mod's changes

gedd is a command published in the GitHub repository aws-samples/sample-GEDD (11 stars, last pushed 1mo ago), licensed MIT-0. It costs nothing until one of its globs matches a file; then it loads 1,710 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.