Borrowing it
Nothing to install: this file belongs to cosdt/PyTorchInsight. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cosdt/PyTorchInsight/main/.opencode/skills/pytorchinsight-briefing-style/SKILL.mdgit clone --depth 1 https://github.com/cosdt/PyTorchInsightWrote 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/cosdt/pytorchinsight/pytorchinsight-briefing-style)<a href="https://agentmods.dev/skills/cosdt/pytorchinsight/pytorchinsight-briefing-style"><img src="https://agentmods.dev/badge/skills/cosdt/pytorchinsight/pytorchinsight-briefing-style/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/cosdt/pytorchinsight/pytorchinsight-briefing-style"><img src="https://agentmods.dev/badge/skills/cosdt/pytorchinsight/pytorchinsight-briefing-style.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 | $0.00036 | $0.00441 |
| Opus 5 | $0.00018 | $0.00220 |
| Sonnet 5 | $0.00007 | $0.00088 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
pytorchinsight-briefing-style 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 12d 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
PyTorchInsight Briefing Style
你是报告样式生成技能，负责将结构化的社区动态分析结果组织为结构清晰的 Markdown 报告。
使用方式
composer agent 在生成报告时调用此 skill。
资源文件
assets/report-template.md: Markdown 报告模板，包含 5 章节结构和占位符references/style-guide.md: 报告样式指导文档，定义区段格式、标识符号、折叠规范
报告生成指令
1. 读取模板
从 assets/report-template.md 读取 Markdown 模板结构。
2. 填充内容
将分析结果填充到模板对应区域：
{{executive_summary}}→ 概览内容{{high_value_items}}→ 重点关注内容（含入选原因）{{categorized_list}}→ 社区动态分类列表{{key_contributors}}→ 关键人物动态{{appendix}}→ 附录（数据采集统计和数据源覆盖状态）{{report_date}}→ 报告生成日期{{time_window}}→ 时间窗口描述{{project_name}}→ 项目名称
3. 样式应用
参照 references/style-guide.md 中的规范：
- 使用影响等级 emoji 标识（🔴🟡🟢）
- 使用
<details>折叠分类列表 - 使用引用块展示入选原因
- 降级数据源使用 ⚠️/❌ 标识
4. 输出
生成标准 GFM Markdown 文件，无外部依赖。文件保存到 orchestrator 指定的路径。
What ships with it
2 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.
- 12d ago First seen · 52 lines · 36 tokens per session scan A 91c8774702ed
pytorchinsight-briefing-style is a skill published in the GitHub repository cosdt/PyTorchInsight (5 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 36 tokens to every session and 441 once invoked, about $0.0002 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 2026-08-31.
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