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objective-report-evaluation

Score chapters against a fixed 10-dimension rubric to output calibrated 0-100 scores.

2|3|Updated Nov 9, 2025
Search Tags:#multi-model#calibration#rubric#chapter#score#evaluate#dimensions
One-click install
npx skills add https://github.com/genesis-agents/GenesisPod --skill objective-report-evaluation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: objective-report-evaluation
Source: https://github.com/genesis-agents/GenesisPod/tree/main/backend/src/modules/ai-app/playground/mission/skills/objective-report-evaluation
Command: npx skills add https://github.com/genesis-agents/GenesisPod --skill objective-report-evaluation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Chapters often vary in quality and are judged inconsistently across evaluators. This skill provides a fixed, transparent rubric to score chapters uniformly, enabling fair cross-model comparisons and reproducible evaluations.

Core Features & Use Cases

  • Per-chapter scoring using a fixed 10-dimension rubric.
  • Cross-model comparison across chapters to identify model strengths and gaps.
  • Dimension-level feedback plus a final calibrated score for reporting and improvement planning.

Quick Start

Use the evaluation skill to score a chapter by supplying its chapterId, chapterTitle, writerModel, and the chapter content.

Frequently Asked Questions about objective-report-evaluation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I score AI-generated chapters consistently across different models?▼

Score AI-generated chapters consistently by applying a fixed 10-dimension rubric that evaluates content against defined weights, producing a calibrated 0-100 score and letter grade for cross-model comparison.

What is the best way to evaluate chapter quality using a standardized rubric?▼

Evaluating chapter quality with a standardized rubric involves scoring against ten fixed dimensions with defined weights, yielding a calibrated 0-100 score, a letter grade, and per-dimension feedback for reproducible assessments.

How do I get dimension-level feedback for per-chapter analysis in AI evaluation workflows?▼

Get dimension-level feedback for per-chapter analysis by supplying the chapterId, chapterTitle, writerModel, and content to trigger the fixed 10-dimension rubric evaluation, which outputs specific per-dimension feedback.

Can I use a fixed rubric to compare model strengths and gaps across multiple chapters?▼

Compare model strengths and gaps across multiple chapters using a fixed 10-dimension rubric that provides uniform scoring, ensuring fair cross-model comparisons and identifying specific dimensional weaknesses.

Does the chapter evaluation rubric output a calibrated score and letter grade?▼

The chapter evaluation rubric outputs a calibrated 0-100 score and a letter grade by satisfying all ten defined dimensions with specific weights, ensuring transparent and reproducible per-chapter scoring.

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