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 ZJU-REAL/Easel --skill skill-quality-gategit clone --depth 1 https://github.com/ZJU-REAL/EaselWrote 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/zju-real/easel/skill-quality-gate)<a href="https://agentmods.dev/skills/zju-real/easel/skill-quality-gate"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-quality-gate/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/zju-real/easel/skill-quality-gate"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-quality-gate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00119 | $0.00739 |
| Opus 5 | $0.00060 | $0.00369 |
| Sonnet 5 | $0.00024 | $0.00148 |
| Haiku 4.5 | $0.00012 | $0.00074 |
Grade A, and why
skill-quality-gate 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 8d 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
发布前质量关卡
一个 SKILL 完成两道把关：合规风险检测 + 产物质量审核。
输入
用户提供待检查内容：文本、图片路径、视频路径、或混合。 可选：目标发布平台。
输出
{
"overall_verdict": "✅ 可发布 | ⚠️ 需修改 | ❌ 不达标",
"platform": "平台名或 generic",
"compliance": {
"risk_level": "low|medium|high",
"issues": [{ "type": "", "severity": "", "text": "", "reason": "", "suggestion": "" }],
"passed_checks": []
},
"quality": {
"score": "✅|⚠️|❌",
"dimensions": [{ "name": "", "score": "", "note": "" }]
},
"top_fixes": ["修改建议1", "修改建议2", "修改建议3"]
}
执行步骤
第一关：合规检测
- 读取内容（文本和/或图片）
- 加载通用合规规则 →
references/general-rules.md - 根据 Profile 或用户指定的平台加载对应规则：
- 小红书 →
references/platform-xiaohongshu.md - 抖音 →
references/platform-douyin.md - B站 →
references/platform-bilibili.md - 无平台 → 仅通用规则
- 小红书 →
- 逐项检测：绝对化用语、医疗违规、违禁内容、平台特有限制
- 汇总合规结果
第二关：质量审核
- 识别产物类型（文本/图片/视频）
- 按维度逐项检查 →
references/review-dimensions.md - 给出三级结论 →
references/review-levels.md- ✅ 通过：可直接发布
- ⚠️ 有瑕疵：建议微调后发布
- ❌ 不达标：需返工
- 如结论为 ❌，按
references/rework-rules.md给出返工指引
综合判定
- 合规高风险 → 整体 ❌ 不达标
- 质量审核为 ❌（返工级）→ 整体 ❌ 不达标
- 合规低风险 + 质量 ✅ → 整体 ✅ 可发布
- 其他组合 → 整体 ⚠️ 需修改
- 输出 Top 3 优先修改建议
Profile 感知
- 有 Profile：读取 platform 加载平台规则、检查风格适配
- 无 Profile：仅通用合规检查 + 通用质量标准
What ships with it
8 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.
- 8d ago First seen · 76 lines · 119 tokens per session scan A 1202b426093b
skill-quality-gate is a skill published in the GitHub repository ZJU-REAL/Easel (794 stars, last pushed yesterday), licensed Apache-2.0. It adds 119 tokens to every session and 739 once invoked, about $0.0006 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 2026-09-03.
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