continuous-eval

continuous-eval is a skill for Claude Code from aws-samples/sample-oh-my-aidlcops. It costs 83 tokens per session (2,492 once invoked), scanned A, original, MIT-0.

A continuous evaluation process for AI responses using Ragas. It runs after each deployment and every hour, measuring answer quality and safety indicators such as faithfulness, relevance, toxicity, and personal-data leakage.

In plain words
What is it for?
Use it to manage a golden dataset, run recurring evaluations, measure quality and safety, and enforce deployment gates.
Why use it?
It detects regressions after releases and can block a canary deployment when results fall 5 percentage points below the baseline.

Skill for Claude Code ✓ vendor

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Part of the agenticops plugin — 11 skills shipped together

Good fit Use it to manage a golden dataset, run recurring evaluations, measure quality and safety, and enforce deployment gates.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aws-samples/sample-oh-my-aidlcops/continuous-eval
About the project

sample-oh-my-aidlcops is a plugin marketplace for Claude Code and Kiro that packages practices for managing the AWS AI-Driven Development Lifecycle, including design correctness and agent safety. It is for teams using agents to develop and operate AWS systems with approval checkpoints. Its catalogue contains the marketplace's plugins, skills, agents, and commands.

aws-samples/sample-oh-my-aidlcops · 19 stars · on GitHub · aws-samples.github.io

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 aws-samples/sample-oh-my-aidlcops --skill continuous-eval
Clone the repo
git clone --depth 1 https://github.com/aws-samples/sample-oh-my-aidlcops

Made for: Claude Code.

Or install agenticops, the plugin that ships this one along with the rest of its 11 skills.

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.

agentmods badge for continuous-eval

README.md
[![agentmods](https://agentmods.dev/badge/skills/aws-samples/sample-oh-my-aidlcops/continuous-eval.svg)](https://agentmods.dev/skills/aws-samples/sample-oh-my-aidlcops/continuous-eval)
Your own site
<a href="https://agentmods.dev/skills/aws-samples/sample-oh-my-aidlcops/continuous-eval"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-oh-my-aidlcops/continuous-eval.svg" alt="Measured on agentmods" height="20"></a>
Per session 83 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,492 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 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 5.1 $0.00083 $0.02492
Opus 5 $0.00042 $0.01246
Sonnet 5 $0.00017 $0.00498
Haiku 4.5 $0.00008 $0.00249

Measured 7d ago against content hash a5684cb4a87a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

continuous-eval 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 7d 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.

plugins/agenticops/skills/continuous-eval/SKILL.md · 206 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. 7d ago First seen · 206 lines · 83 tokens per session scan A a5684cb4a87a

Subscribe to this mod's changes

continuous-eval is a skill published in the GitHub repository aws-samples/sample-oh-my-aidlcops (19 stars, last pushed 2d ago), licensed MIT-0. It adds 83 tokens to every session and 2,492 once invoked, about $0.0004 per session on Opus 5. 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.

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