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advanced-evaluation

Advanced Evaluation skill from sickn33/agentic-awesome-skills

Quality

50%

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/advanced-evaluation/SKILL.md

The canonical home for this skill is advanced-evaluation in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

56%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body delivers genuinely useful, well-templated LLM-as-a-judge guidance with worked examples and explicit bias-mitigation protocols — its strongest dimensions are actionability and workflow clarity. Its weaknesses are verbosity (duplicated boilerplate sections, ASCII art, and concept re-explanations Claude already knows) and a monolithic structure whose "internal references" point at non-existent files.

Suggestions

Delete the duplicated pre-amble (the first "## When to use" and "## Description" sections, which repeat the body's "## When to Use"), the "Skill Metadata" block, and the ASCII pipeline diagram — together they are ~80 lines of padding that add no guidance Claude doesn't already have.

Trim concept re-explanations (Likert scale tradeoffs, generic bias definitions, the standard metrics table) to one-line pointers, keeping only the actionable mitigations and the MT-Bench-backed recommendation that is specific to this skill.

Either split the detailed material into real one-level-deep reference files (e.g., references/bias-mitigation.md, references/rubric-generation.md) and link them clearly, or remove the "Internal reference" entries that point at files that don't exist in the bundle.

DimensionReasoningScore

Conciseness

The ~460-line body has several padded sections: a duplicated "Use this skill when you need guidance on evaluating model outputs" boilerplate that repeats the "## When to Use" section, a redundant "## Description" section, a 30-line ASCII pipeline diagram, a "Skill Metadata" block with dates, and re-explanations of concepts Claude already knows (Likert scale tradeoffs, standard bias definitions, agreement metrics like Cohen's κ and Spearman's ρ). This fits "Noticeably verbose; several unnecessary explanations or padded sections" rather than anchor 3's "some unnecessary explanation", because the padding is structural (whole sections), not incidental.

2 / 5

Actionability

The body provides copy-paste-ready prompt templates with {prompt}/{response} placeholders for both direct scoring and pairwise comparison, plus three worked examples with concrete JSON outputs (e.g., the position-swap example mapping "winner": "A" to the mapped result). This is mostly executable guidance with concrete commands, but minor gaps keep it below anchor 5: Example 2's responses are placeholders ("[Technical explanation with jargon]"), and the "Internal reference" entries ("LLM-as-Judge Implementation Patterns", "Bias Mitigation Techniques", "Metric Selection Guide") are not actual files or links, so they cannot be followed.

4 / 5

Workflow Clarity

The core workflows are clearly sequenced with a validation checkpoint: the "Position Bias Mitigation Protocol" gives 4 numbered passes with a consistency check ("If passes disagree, return TIE with reduced confidence") and the confidence-calibration rule, and the anti-patterns section reinforces error handling ("Scoring without justification", "Single-pass pairwise comparison"). This matches "Clear sequence with most checkpoints present; minor validation gaps" — it falls short of anchor 5 because validation-against-human-judgment is a bare guideline ("Validate against human judgments") with no procedure or checklist.

4 / 5

Progressive Disclosure

The body has real section structure (Core Concepts, Evaluation Approaches, Examples, Guidelines, References) but is a single ~460-line monolith, and the "Internal reference" items are bare names with no paths, pointing to files that do not exist in the bundle (no references/, scripts/, or assets/ directories). This fits "Some structure but could be better organized; references present but not clearly signaled; content that should be separate is inline" — the detailed rubric-generation and bias-mitigation material would live better in one-level-deep reference files. Not anchor 2 because the section headers make navigation genuine, not minimal.

3 / 5

Total

13

/

20

Passed

Description

20%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is effectively a title plus provenance, not a capability description. It fails to state what the skill does, when to use it, or how it differs from sibling evaluation skills. It also omits the body's actual substance (LLM-as-a-judge patterns, bias mitigation, rubric generation), which would make a strong description if surfaced.

Suggestions

Rewrite the description to list the concrete capabilities already in the body, e.g.: "Evaluates LLM outputs with LLM-as-a-judge techniques: direct scoring, pairwise comparison with position-swap bias mitigation, rubric generation, and metric selection. Use when building evaluation pipelines, comparing model responses, or debugging inconsistent judge results."

Add explicit trigger phrases users would naturally say ("LLM-as-a-judge", "eval pipeline", "rubric", "compare model responses", "judge bias") to improve both trigger matching and distinctiveness.

Distinguish this skill from the foundational "evaluation" skill it extends (e.g., "extends the foundational evaluation skill with production-grade bias mitigation and rubric calibration") to reduce conflict risk within the collection.

DimensionReasoningScore

Specificity

The entire description is "Advanced Evaluation skill from sickn33/agentic-awesome-skills" — it names a topic area (evaluation) but contains zero concrete action verbs or capabilities, matching the anchor "Entirely vague; no concrete actions; pure abstract language". It does not fit anchor 2 because that anchor requires at least a minimal or generic action (e.g., "Processes PDF files"), and this description has none.

1 / 5

Completeness

The description has a vague 'what' ("Advanced Evaluation skill" says nothing about what it actually does or evaluates) and no 'when' clause whatsoever, matching "Has a vague 'what' and no 'when'". Not anchor 1 only because a topic is at least named; the missing 'Use when...' guidance caps completeness per the judging guidelines.

2 / 5

Trigger Term Quality

"Evaluation" is the single generic keyword present; the natural phrases users would say ("evaluate model outputs", "LLM-as-judge", "eval pipeline", "rubric") are all missing, fitting "One or two generic keywords; missing the natural phrases users say". Not a 1 only because "Evaluation" is a plausible natural term rather than pure jargon; not a 3+ because no synonyms, variations, or concrete trigger phrases appear.

2 / 5

Distinctiveness Conflict Risk

"Advanced Evaluation skill" is broad and — per the body itself, which references a foundational "evaluation" skill in the same collection — carries high overlap risk with sibling evaluation skills, fitting "Very broad; high overlap risk with many similar skills". It is not a 3 because the description offers nothing (no scope, audience, or trigger) that would distinguish it from those similar skills.

2 / 5

Total

7

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills/skills/advanced-evaluation/SKILL.md

Reviewed

Table of Contents

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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.