advanced-evaluation-v2

advanced-evaluation-v2 is a skill for Claude Code, Codex from diegosouzapw/awesome-omni-skills. It costs 93 tokens per session (5,219 once invoked), scanned A, a copy of advanced-evaluation, MIT.

A guide to evaluating responses from large language models, including using another language model as a judge.

In plain words
What is it for?
Use it to create scoring rubrics, compare model responses directly or in pairs, build evaluation pipelines, and reduce common judging biases.
Why use it?
It helps teams compare outputs consistently and account for problems such as scoring bias or unfair judging criteria.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex; mentions Gemini CLI; mentions OpenCode.

Good fit Use it to create scoring rubrics, compare model responses directly or in pairs, build evaluation pipelines, and reduce common judging biases.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/diegosouzapw/awesome-omni-skills/advanced-evaluation-v2
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 diegosouzapw/awesome-omni-skills --skill advanced-evaluation-v2
Clone the repo
git clone --depth 1 https://github.com/diegosouzapw/awesome-omni-skills

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.

agentmods badge for advanced-evaluation-v2

README.md
[![agentmods](https://agentmods.dev/badge/skills/diegosouzapw/awesome-omni-skills/advanced-evaluation-v2/github.svg)](https://agentmods.dev/skills/diegosouzapw/awesome-omni-skills/advanced-evaluation-v2)
Your own site
<a href="https://agentmods.dev/skills/diegosouzapw/awesome-omni-skills/advanced-evaluation-v2"><img src="https://agentmods.dev/badge/skills/diegosouzapw/awesome-omni-skills/advanced-evaluation-v2/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.

agentmods 80×15 button for advanced-evaluation-v2

Your own site · 80×15
<a href="https://agentmods.dev/skills/diegosouzapw/awesome-omni-skills/advanced-evaluation-v2"><img src="https://agentmods.dev/badge/skills/diegosouzapw/awesome-omni-skills/advanced-evaluation-v2.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,219 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 84% 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.05219
Opus 5 $0.00046 $0.02610
Sonnet 5 $0.00019 $0.01044
Haiku 4.5 $0.00009 $0.00522

Measured 12d ago against content hash e0503ff38b01, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

advanced-evaluation-v2 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 12d 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.

Origin

This is a copy

84% identical to advanced-evaluation — 549 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.

skills/advanced-evaluation-v2/SKILL.md · 606 lines

How it starts

The opening of the file, as written. The whole thing — 606 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Advanced Evaluation

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/advanced-evaluation from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Advanced Evaluation This skill covers production-grade techniques for evaluating LLM outputs using LLMs as judges. It synthesizes research from academic papers, industry practices, and practical implementation experience into actionable patterns for building reliable evaluation systems. Key insight: LLM-as-a-Judge is not a single technique but a family of approaches, each suited to different evaluation contexts. Choosing the right approach and mitigating known biases is the core competency this skill develops.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core Concepts, Evaluation Approaches, Task, Original Prompt, Response to Evaluate, Criteria.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

  • Building automated evaluation pipelines for LLM outputs
  • Comparing multiple model responses to select the best one
  • Establishing consistent quality standards across evaluation teams
  • Debugging evaluation systems that show inconsistent results
  • Designing A/B tests for prompt or model changes
  • Creating rubrics for human or automated evaluation

Operating Table

Situation Start here Why it matters
First-time use metadata.json Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review ORIGIN.md Gives reviewers a plain-language audit trail for the imported source
Workflow execution SKILL.md Starts with the smallest copied file that materially changes execution
Supporting context SKILL.md Adds the next most relevant copied source file without loading the entire package
Handoff decision ## Related Skills Helps the operator switch to a stronger native skill when the task drifts

Read the full file on GitHub · 606 lines

Files

What ships with it

2 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.

  1. 12d ago First seen · 606 lines · 93 tokens per session scan A e0503ff38b01

Subscribe to this mod's changes

advanced-evaluation-v2 is a skill published in the GitHub repository diegosouzapw/awesome-omni-skills (140 stars, last pushed 2mo ago), licensed MIT. It adds 93 tokens to every session and 5,219 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to advanced-evaluation, differing in 549 lines, and is treated as a copy.

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