Agent skill · AI agents · muratcankoylan

advanced-evaluation agent skill by muratcankoylan

Guides advanced LLM evaluation, including LLM-as-judge systems, direct scoring, pairwise comparison, rubric calibration, evaluator bias mitigation, confidence scoring, and automated quality assessment.

View on GitHub Read SKILL.md

At a glance

Publisher	muratcankoylan
Repository	muratcankoylan/Agent-Skills-for-Context-Engineering (19 listed skills)
Category	AI Agents and LLM Engineering
License	MIT
Last commit	October 11, 2026 (repository)
SKILL.md	404 lines, 2,162 words
Bundled files	6 files, including references, scripts
Quality score	86/100 · B Passes all seven graded checks
Security scan	Not scanned
README badge	Get the badges for this listing

Before you install

Read from the skill's files at the directory's October 19, 2026 snapshot: what ships with it, what its code reads, and the terms it is published under.

Bundled scripts: 1 script file (1 Python). Your agent may run them, so read them first.
License: MIT, an open-source or open-content license.

Install advanced-evaluation

The skills CLI works with Claude Code, Codex, Cursor and other agents; the other routes copy the folder by hand.

Skills CLI

npx skills add https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering/tree/main/skills/advanced-evaluation

Claude Code, project-level copy

tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering.git "$tmp/repo"
mkdir -p .claude/skills
cp -R "$tmp/repo/"skills/advanced-evaluation .claude/skills/
rm -rf "$tmp"

Codex installer

python3 ~/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py \
    --repo muratcankoylan/Agent-Skills-for-Context-Engineering \
    --path skills/advanced-evaluation

muratcankoylan/Agent-Skills-for-Context-Engineering is third-party code. Read SKILL.md and any bundled scripts before you install it.

How the author describes it

This skill should be used for advanced LLM evaluation: LLM-as-judge systems, direct scoring, pairwise comparison, rubric calibration, evaluator bias mitigation, confidence scoring, and automated quality assessment.

From the description field of SKILL.md. Agents read this line to decide when to load the skill.

Sections in SKILL.md

When to Activate
Core Concepts
The Evaluation Taxonomy
The Bias Landscape
Metric Selection Framework
Evaluation Approaches
Direct Scoring Implementation
Pairwise Comparison Implementation
Rubric Generation
Practical Guidance
Evaluation Pipeline Design
Decision Framework: Direct vs. Pairwise
Scaling Evaluation
Examples
Example 1: Direct Scoring for Accuracy
Example 2: Pairwise Comparison with Position Swap

Files in the skill folder

SKILL.md
references/bias-mitigation.md
references/evaluation-pipeline.md
references/implementation-patterns.md
references/metrics-guide.md
scripts/evaluation_example.py

Suede Skill Check: 86/100 · B

Report snapshot · October 19, 2026 · graded-v2

The rubric totals 100 points; published scores are capped at 99. Security scan: not scanned.

Source revision: 9ff0c99108b3. Report version 5ec5f291ce68. Badge URLs follow the latest listing; save the report to keep this version.

Download report · Request a fresh review

What to review next

Boundary clause: 0 of 4 points. 4 when the description says when not to use the skill (“Not for …”, “Do not use …”, “Use … instead”).
Example request: 0 of 3 points. 3 when the description quotes an example request (3–60 characters in quotation marks).
Tool permissions declared: 0 of 2 points. 2 when the frontmatter declares allowed-tools.

Add declarations and bundled files when they describe the skill’s actual needs. Update the source, then request a fresh review with the changed commit or PR.

advanced-evaluation passes the required frontmatter check and all seven graded checks, which cover the SKILL.md format, a declared license and a commit in the last year. Those checks earn 56 of the score’s points; the rest come from description quality, instruction depth, bundled files, maintenance and curated-list citations. How the score works.

See the checks and points

Check	Result
Frontmatter parses and declares a name and a description	Pass
Name uses lowercase letters, digits and hyphens, 64 characters or fewer	Pass
Name matches the skill's folder name	Pass
Description is between 50 and 1,024 characters	Pass
Description says when an agent should use the skill	Pass
SKILL.md body is 500 lines or fewer	Pass
A license is declared in the frontmatter or the repository	Pass
Repository has a commit in the last 12 months	Pass

Score component	Points
Structural checks	56 of 56
Description length	5 of 5
Boundary clause	0 of 4
Example request	0 of 3
Instruction depth	7 of 7
Reference files	3 of 3
Bundled scripts	2 of 2
Recent maintenance	9 of 9
Curated-list citations	4 of 7
Tool permissions declared	0 of 2
Compatibility declared	0 of 2

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Markdown

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HTML

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<a href="https://skills.suedeai.ai/directory/muratcankoylan/agent-skills-for-context-engineering/advanced-evaluation/"><img src="https://skills.suedeai.ai/directory/muratcankoylan/agent-skills-for-context-engineering/advanced-evaluation/badge.svg" alt="Suede Skill Check: Grade B" width="160" height="175"></a>

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Limited-time feature offer: display either the numeric or letter badge in your repository or skill README (both also qualify), then request badge verification. Eligible skills scoring 80–99 can receive a featured placement after Suede verifies at least one valid badge linked to the skill’s listing. Suede has not announced an end date.