score-optimizer

Original：🇨🇳 Chinese

Translated

3 scriptsChecked / no sensitive code detected

Use when the user wants to iterate on a viral-article scoring system itself, calibrate or improve a scoring prompt against labeled samples, or run batch scoring experiments on a fixed article set. Best for prompt-only scoring research where the evaluator scripts stay fixed and only the scoring rubric/prompt is meant to evolve.

4installs

Sourcexiaomoboy/claude-writing-skills

Added on2026-05-26

NPX Install

npx skill4agent add xiaomoboy/claude-writing-skills score-optimizer

SKILL.md Content (Chinese)

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Score Optimizer

This skill only does one thing: optimize the article scoring system itself.

It is suitable for:

Adjusting viral article scoring prompts
Batch scoring sample article collections
Evaluating scoring accuracy against labeled data
Researching whether scoring dimensions, weights, and few-shot examples are more reasonable

It is NOT responsible for:

Directly modifying article content
Platform rewriting
Publishing and packaging

Working Scope

Applicable scenarios:

When the user says "optimize the article scoring prompt"
When the user says "make this viral scoring system more accurate"
When the user says "run a round of sample article collection scoring experiments"
When the user says "calibrate the scoring rules for viral score / composite score"

Inapplicable scenarios:

When the user says "directly modify this article to get a higher score"
When the user says "optimize article content according to this scorer"

The latter should use

article-optimizer

instead.

Required Reads

Read these before starting:

references/score_program.md
references/score_prompt.md

Read these when needing to check implementations:

scripts/run_scoring.py
scripts/evaluate.py
assets/articles/labels.example.json —— Label schema example

Sample article collection location (provided by the user, this skill does not include samples):

```
assets/articles/samples/
```
—— Place your own labeled .md articles here, then
```
cp labels.example.json labels.json
```
and fill in your scores. See details in assets/articles/samples/README.md

Workflow

First confirm that the current task is optimizing the scorer, not modifying articles.
Read
```
references/score_program.md
```
and execute according to its experimental constraints.
By default, only modify
```
references/score_prompt.md
```
; do not touch the evaluation scripts.
Run the batch scoring script, then run the evaluation script.

Compare

composite_score

,

mae

,

spearman

,

classification

.

Record the results and decide whether to keep or roll back.

Commands

Execute in the skill root directory:

bash

python3 scripts/run_scoring.py > scoring.log 2>&1
python3 scripts/evaluate.py > eval.log 2>&1
grep "^composite_score:\|^mae:\|^spearman:\|^classification:" eval.log

If charts are needed: