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-discoverygit 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-discovery)<a href="https://agentmods.dev/skills/byteseek/mira/etf-listing-discovery"><img src="https://agentmods.dev/badge/skills/byteseek/mira/etf-listing-discovery/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-discovery"><img src="https://agentmods.dev/badge/skills/byteseek/mira/etf-listing-discovery.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 | $0.00030 | $0.01423 |
| Opus 5.5 | $0.00012 | $0.00569 |
| Sonnet 5.5 | $0.00006 | $0.00285 |
| Haiku 4.5 | $0.00003 | $0.00142 |
Grade A, and why
etf-listing-discovery 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 2mo 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ETF Listing Discovery Skill
这个 skill 用于查找新上市、即将上市、已提交申请或刚被媒体/发行人宣布的 ETF/ETP。
它是 etf-listing-analysis 的前置发现层:
ETF listing discovery -> new-etf-watchlist -> ETF listing analysis
它不负责深度判断 ETF 是否值得买入,只负责把候选产品找出来、去重、补齐关键字段、排序,并决定哪些进入 etf-listing-analysis。
Use When
- 用户要求查找最近新上市 ETF
- 用户要求监控新 ETF、ETF 申请、ETF launch、ETF issuer 新产品
- 用户想从 ETF 新发中发现市场偏好、配置方向、主题热度或结构变化
- 用户给出一个主题,要求找相关新 ETF 或申请中的 ETF
etf-listing-analysis缺少输入,需要先发现候选产品
Required Inputs
- market_scope 例如 US、global、HK、CN、EU
- discovery_window 例如 last 7 days、last 30 days、YTD、since date
- discovery_mode 例如 listed、upcoming、filed、announced、all
- theme_filter 可选,例如 crypto、AI、covered call、single-stock、duration、China、commodity
- output_limit 默认先保留前 20 个候选
- research_cutoff_date
Source Priority
优先级从高到低:
exchange notices交易所新上市/新发行通知,确认 ticker、上市日期、交易所。issuer launch pages发行人产品页、新闻稿、招募说明书,确认策略、费用、持仓、指数。regulatory filingsSEC/监管文件,确认申请、修订、规则和基金注册信息。ETF industry mediaETF.com、ETF Trends、VettaFi、Bloomberg/Reuters 等,用于发现线索和语境。market dataAUM、成交、价差、首日交易数据,用于初步排序,不替代上市确认。
Discovery Workflow
1. Define Search Scope
先明确:
- 市场:US / global / local market
- 时间窗口:上市日、公告日、申请日,不能混用
- 状态:已上市、即将上市、已申请、传闻/媒体报道
- 产品范围:ETF only,还是包含 ETN、ETC、ETP、closed-end fund
2. Search Source Buckets
至少覆盖三类来源:
- 交易所或监管来源
- 发行人或指数提供商来源
- ETF 行业媒体或市场数据来源
如果只找到媒体文章,必须标记为 needs_primary_confirmation。
3. Normalize Candidate Records
每个候选至少补齐:
- ticker
- ETF name
- issuer
- exchange
- listing_status
- listing_date 或 filing_date
- product_type
- underlying_exposure
- source_id
- source_url
- source_publish_date 或 last_checked_date
- why_worth_analyzing
4. Deduplicate
去重规则:
- 同 ticker 同 exchange 视为同一产品
- 同一 ETF 的媒体报道、交易所通知、发行人页面合并成一个候选
- share class、dual listing、fund conversion 不能误判为全新产品,必须标记
5. Score Priority
每个候选给出 priority_score,建议 0 到 5:
5: 新主题/新资产可达性/多发行人集中推出/上市后快速放量4: 有清晰结构创新、机构配置含义或高热度主题3: 普通但值得观察的新 ETF2: 低费率复制、存量产品变体或主题纯度存疑1: 信息不足、可能只是产品噪音0: 重复、转换、清盘替代或不属于 ETF/ETP 范围
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.
- 2mo ago First seen · 174 lines · 30 tokens per session scan A 8774b5b5bf44
etf-listing-discovery is a skill published in the GitHub repository byteseek/Mira (282 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 1,423 once invoked, about $0.0001 per session on Opus 5.5. 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.
etf-listing-discovery compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| etf-listing-discoverybyteseek/Mira | Skill | 282 | 2mo ago | Apache-2.0 | A | 30 | Claude Code, Codex |
| costSethGammon/Citadel | Skill | 927 | yesterday | MIT | A | 46 | Claude Code |
| get_financial_statementssupremeb/Oniva-ai | Skill | 5 | 15d ago | none | A | 21 | Claude Code, Codex |
| aml_screeningsupremeb/Oniva-ai | Skill | 5 | 15d ago | none | A | 14 | Claude Code, Codex |
| analyze_risk_metricssupremeb/Oniva-ai | Skill | 5 | 15d ago | none | A | 24 | Claude Code, Codex |
| fetch_economic_indicatorssupremeb/Oniva-ai | Skill | 5 | 15d ago | none | A | 17 | Claude Code, Codex |
| fetch_market_datasupremeb/Oniva-ai | Skill | 5 | 15d ago | none | A | 20 | Claude Code, Codex |