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.
npx skills add xiaomoBoy/claude-writing-skills --skill article-optimizergit clone --depth 1 https://github.com/xiaomoBoy/claude-writing-skillsWrote 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.
[](https://agentmods.dev/skills/xiaomoboy/claude-writing-skills/article-optimizer)<a href="https://agentmods.dev/skills/xiaomoboy/claude-writing-skills/article-optimizer"><img src="https://agentmods.dev/badge/skills/xiaomoboy/claude-writing-skills/article-optimizer/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.
<a href="https://agentmods.dev/skills/xiaomoboy/claude-writing-skills/article-optimizer"><img src="https://agentmods.dev/badge/skills/xiaomoboy/claude-writing-skills/article-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.00545 |
| Opus 5 | $0.00031 | $0.00272 |
| Sonnet 5 | $0.00012 | $0.00109 |
| Haiku 4.5 | $0.00006 | $0.00055 |
Grade A, and why
article-optimizer 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 10d 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.
What it actually says
Article Optimizer
这个 skill 只负责一件事：在固定评分器下优化一篇具体文章。
它适合做的是：
- 给单篇文章打分
- 根据评分返回的改进建议改稿
- 做多轮版本迭代
- 对比不同版本的 viral score
它不负责：
- 调整评分器本身
- 校准整套评分系统
- 批量样本评估
如果目标是改评分 Prompt，而不是改文章，应该改用 score-optimizer。
Working Scope
适用场景：
- 用户说“把这篇文章优化到更高分”
- 用户说“按固定评分规则改稿”
- 用户说“给单篇文章打分并根据建议改写”
- 用户说“跑 single article optimization loop”
不适用场景：
- 用户说“让这套评分系统更准”
- 用户说“批量评估一组样本文章”
Required Reads
开始前先读：
需要看实现时再读：
Workflow
- 先确认当前任务是在改文章，不是在改评分器。
- 读取
references/optimize_program.md，确认实验约束。 - 确认目标文章路径。
- 用单篇打分脚本跑出基线分数和改进建议。
- 每轮只改文章，不动评分规则。
- 保存迭代版本，再重新打分比较。
Commands
在 skill 根目录执行：
python3 scripts/run_single_score.py <article_path>
如果需要图表：
python3 scripts/generate_optimize_chart.py
Guardrails
- 默认不要改
references/score_prompt.md - 默认不要改
scripts/run_single_score.py - 每轮优先只改文章内容
- 如果用户要的是“训练裁判”，不要用这个 skill
What ships with it
5 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.
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.
- 10d ago First seen · 80 lines · 62 tokens per session scan A a432fb9a221b
article-optimizer is a skill published in the GitHub repository xiaomoBoy/claude-writing-skills (31 stars, last pushed 3mo ago), licensed MIT. It adds 62 tokens to every session and 545 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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