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 Travisun/Opptrix --skill universe-screengit clone --depth 1 https://github.com/Travisun/OpptrixWrote 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/travisun/opptrix/universe-screen)<a href="https://agentmods.dev/skills/travisun/opptrix/universe-screen"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/universe-screen/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/travisun/opptrix/universe-screen"><img src="https://agentmods.dev/badge/skills/travisun/opptrix/universe-screen.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 | $0.00075 | $0.00819 |
| Opus 5 | $0.00037 | $0.00409 |
| Sonnet 5 | $0.00015 | $0.00164 |
| Haiku 4.5 | $0.00007 | $0.00082 |
Grade A, and why
universe-screen 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 5d 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
股票池筛选
何时使用
用户要在已知成分（指数/板块）或自建池上按条件筛选，得到可复核的候选表。边界：这是筛选事实表，不是荐股池、回测结果或「明日必涨名单」。单票信号诊断用 @skill:instrument-signals；本技能只输出条件命中表，入选≠看好。
分析架构（投研方法）
- 问题/假设：在给定宇宙与硬性约束下，哪些标的满足条件？
- 证据清单：成分列表、批量快照、可选财务字段
- 多维交叉验证：条件计数 vs 表行数；缺失字段不得当通过
- 结论与不确定：入选≠看好；条件可被操纵
- 事实 | 假设 | 推断 分栏：筛选项为假设/规则；表内行情为事实
数据维度
| 维度 | 取数方向 | 缺失时 |
|---|---|---|
| 宇宙 | get_index_constituents / get_sector_constituents / get_sector_list |
用户给代码清单 |
| 筛选条件 | ask_user |
先确认硬性条件 |
| 批量行情 | batch_instrument_snapshots |
降级逐个或缩小池 |
| 财务过滤 | get_instrument_financials（抽样或必要字段） |
跳过该条件并标明 |
| 交付 | list_web_vendor → create_web |
可跳过口头要点 |
步骤
- 确认宇宙与条件（硬性/软性分开）。
- 拉取成分 → 批量快照。
- 应用过滤：缺字段记「未知」而非通过。
- 输出候选表 + 条件命中统计；明确「非荐股」。
- 交付网页（默认）：可筛选表格；见
@skill:create-web。
网页报告建议目录
- 宇宙、条件与时效
- 成分来源说明
- 筛选结果表
- 条件命中统计与数据缺口
- 事实 / 推断分栏（禁止写成推荐清单）
- 免责声明（非荐股池）
禁止
- 把筛选结果包装成荐股池、目标价或仓位建议
- 编造成分或快照字段
- 禁止无交付就结束
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.
- 5d ago First seen · 63 lines · 75 tokens per session scan A f4c1af394488
universe-screen is a skill published in the GitHub repository Travisun/Opptrix (231 stars, last pushed 2d ago), licensed Apache-2.0. It adds 75 tokens to every session and 819 once invoked, about $0.0004 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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