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 byteseek/Mira --skill etf-listing-analysisgit clone --depth 1 https://github.com/byteseek/MiraWrote 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/byteseek/mira/etf-listing-analysis)<a href="https://agentmods.dev/skills/byteseek/mira/etf-listing-analysis"><img src="https://agentmods.dev/badge/skills/byteseek/mira/etf-listing-analysis/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/byteseek/mira/etf-listing-analysis"><img src="https://agentmods.dev/badge/skills/byteseek/mira/etf-listing-analysis.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 | $0.00034 | $0.02821 |
| Opus 5 | $0.00017 | $0.01411 |
| Sonnet 5 | $0.00007 | $0.00564 |
| Haiku 4.5 | $0.00003 | $0.00282 |
Grade A, and why
etf-listing-analysis 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ETF Listing Analysis Skill
这个 skill 用于分析新上市 ETF、即将上市 ETF、ETF 申请文件和 ETF 产品线扩张。
它不把 ETF 新上市直接等同于买入信号,也不要求新 ETF 在首轮分析中已经完成资金验证。新上市本身首先是一个 product signal:发行人为什么现在愿意把某类暴露做成产品,想卖给谁,底层持仓和权重机制会把这个信号传导到哪里。
核心目标是回答:
新 ETF 上市到底代表真实配置方向、交易工具需求、资产可达性变化、用户偏好,还是主题营销和周期尾声包装?
Use When
- 用户要求分析一个新上市 ETF 或即将上市 ETF
- 用户想从 ETF 新发看市场偏好、配置方向、主题热度或成分股机会
- 研究对象是 ETF 申请、上市公告、招募说明书、指数方法论或主动 ETF 组合
- 需要判断某个主题是否开始进入机构可配置产品货架
- 需要把 ETF 暴露传导到股票、行业、国家、债券、商品或加密资产
Avoid When
- ETF 只是已有宽基产品的低费率复制,且没有新的配置含义
- 上市主要是基金转换、税务结构调整或发行人内部产品整理
- 底层资产极度不透明,无法确认持仓、指数规则或管理方式
- 研究问题本质是单家公司财报、基本面或事件,ETF 只是背景噪音
Required Inputs
- etf_name
- ticker
- market
- issuer
- listing_date
- product_type 例如 passive index、active ETF、rules-based active、leveraged/inverse、covered call、buffer、single-stock、commodity、crypto、bond、thematic equity
- management_mode 例如 passive index、active discretionary、rules-based active、quantitative active、synthetic/derivative based
- weighting_mode 例如 market-cap weighted、equal-weighted、modified market-cap、liquidity-weighted、factor-weighted、theme-revenue-weighted、active discretionary
- underlying_exposure 例如国家、行业、主题、因子、期限、商品、币种或单股
- holdings_status
confirmed、partial或unavailable/inferred - research_cutoff_date
- thesis_horizon
建议补充:
- fee、index_provider、index_methodology、holdings、weighting_rules、rebalance_frequency
- top holdings、top10_weight、single_name_cap、sector/country caps、theme revenue purity
- peer ETF set、category products、issuer product history、distribution channel
- seed capital、AUM、volume、bid-ask spread、creation/redemption unit
- authorized participants、market makers、options listing status
- underlying holdings liquidity、float、short interest、ownership and crowding
Framework
首轮分析必须分成四个核心判断和一个后续跟踪层:
issuer intentstructure and accessexposure and constituent mapmode and weighting mechanicspost-listing tracking
post-listing tracking 是后续验证层,不是新 ETF 首轮结论的前置条件。
1. Issuer Intent
先判断发行人为什么现在推这个产品。允许多标签,但必须给主判断:
hype-capture追热点、抢主题名字、承接媒体和散户热度。long-term-allocation建立长期配置货架,服务模型组合、顾问、机构或长期主题配置。user-preference响应客户、RIA、交易员、机构或零售用户已经存在的表达需求。strategic-direction代表发行人产品线或平台方向,例如主动 ETF 化、加密资产、能源转型、期权收益。access-innovation把难直接买、难托管、难税务处理或难跨境配置的资产包装成普通账户可交易产品。theme-purity试图比现有 ETF 更纯粹地表达某个主题、产业链或因子。fee-lineup-competition补全产品线、降低费率、替代竞品或防止客户流失。
What ships with it
1 file 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.
- 11d ago First seen · 254 lines · 34 tokens per session scan A 1fd4a6d24df5
etf-listing-analysis is a skill published in the GitHub repository byteseek/Mira (268 stars, last pushed 3d ago), licensed Apache-2.0. It adds 34 tokens to every session and 2,821 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 2026-08-30.
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