Stock API
zhangxiangliang/stock-api
Fetch real-time stock quotes, K-line (candlestick) history, and search symbols for China A-shares, Hong Kong, and US markets.
Analyze new, pending, or expanding ETF products as product signals, exposure maps, demand indicators, and potential asset-pricing read-throughs.
Install Etf Listing Analysis
$ npx skills add byteseek/Mira --skill etf-listing-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install byteseek/Mira etf-listing-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/byteseek/Mira.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/etf-listing-analysis .claude/skills/etf-listing-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "etf-listing-analysis" agent skill from https://github.com/byteseek/Mira/tree/main/skills/etf-listing-analysis into .claude/skills/etf-listing-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "etf-listing-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/byteseek/Mira/tree/main/skills/etf-listing-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add byteseek/Mira --skill etf-listing-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install byteseek/Mira etf-listing-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/byteseek/Mira.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/etf-listing-analysis .agents/skills/etf-listing-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "etf-listing-analysis" agent skill from https://github.com/byteseek/Mira/tree/main/skills/etf-listing-analysis into .agents/skills/etf-listing-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "etf-listing-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add byteseek/Mira --skill etf-listing-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install byteseek/Mira etf-listing-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/byteseek/Mira.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/etf-listing-analysis .cursor/skills/etf-listing-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "etf-listing-analysis" agent skill from https://github.com/byteseek/Mira/tree/main/skills/etf-listing-analysis into .cursor/skills/etf-listing-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "etf-listing-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/byteseek/Mira.git --path skills/etf-listing-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add byteseek/Mira --skill etf-listing-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install byteseek/Mira etf-listing-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/byteseek/Mira.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/etf-listing-analysis .gemini/skills/etf-listing-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "etf-listing-analysis" agent skill from https://github.com/byteseek/Mira/tree/main/skills/etf-listing-analysis into .gemini/skills/etf-listing-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "etf-listing-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install byteseek/Mira etf-listing-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add byteseek/Mira --skill etf-listing-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/byteseek/Mira.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/etf-listing-analysis .github/skills/etf-listing-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "etf-listing-analysis" agent skill from https://github.com/byteseek/Mira/tree/main/skills/etf-listing-analysis into .github/skills/etf-listing-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "etf-listing-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add byteseek/Mira --skill etf-listing-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install byteseek/Mira etf-listing-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/byteseek/Mira.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/etf-listing-analysis .opencode/skills/etf-listing-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "etf-listing-analysis" agent skill from https://github.com/byteseek/Mira/tree/main/skills/etf-listing-analysis into .opencode/skills/etf-listing-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "etf-listing-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
etf-listing-analysis- GitHub stars
- 275
- Token cost
- ~1.6k tokens
- SKILL.md length
- 468 words
- Files
- 2 (incl. references)
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Analyze new, pending, or expanding ETF products as product signals, exposure maps, demand indicators, and potential asset-pricing read-throughs.
- Works in 6 steps: Issuer Intent → Structure And Access → Exposure And Constituent Map → …
- Tasks that involve Stock and market analysis
- SKILL.md covers Use When, Avoid When, Required Inputs and Framework, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Etf Listing Analysis is an agent skill from byteseek/Mira. Analyze new, pending, or expanding ETF products as product signals, exposure maps, demand indicators, and potential asset-pricing read-throughs.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/etf-listing-framework.md`).
It sits in Business, Finance & HR, covering Stock and market analysis. The repository describes itself as: Agent-native investment research workspace for evidence-tracked, refreshable investment theses across equities, earnings, macro, and portfolio review. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Stock and market analysis
Example prompts
- “/etf-listing-analysis”
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit adddce7. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Etf Listing Analysis loads about 1.6k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 41 tokens; SKILL.md has 468 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from byteseek/Mira at commit adddce7, republished under its Apache-2.0 licence (© byteseek). 468 words, ~1,613 tokens.
Download SKILL.mdSave it as
.claude/skills/etf-listing-analysis/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- etf-listing-analysis
- description
- Analyze new, pending, or expanding ETF products as product signals, exposure maps, demand indicators, and potential asset-pricing read-throughs.
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。
必须区分：这是发行人想卖的故事，还是投资者已经需要的工具。
2. Structure And Access
产品结构决定 ETF 上市信号的含义：
| product type | primary signal | common trap |
|---|---|---|
| passive thematic equity | 主题被产品化 | 名字热但主题纯度低 |
| active ETF | 管理人判断、渠道需求和组合表达 | 持仓漂移或披露滞后 |
| broad/sector index | 配置需求或费率竞争 | 只是低费率复制 |
| leveraged/inverse | 交易需求和波动需求 | 不能代表长期配置需求 |
| covered call / income | 收益需求和波动率货币化 | 用高分红包装弱上行 |
| buffer / defined outcome | 防守和结构化需求 | payoff 复杂，真实风险被隐藏 |
| single-stock ETF | 单股交易工具化 | 反映交易热度而非基本面确认 |
| commodity / crypto | 资产可达性变化 | 初期需求可能是替代原有敞口 |
| bond / duration | 久期、信用或收益偏好 | 宏观利率解释力可能高于产品信号 |
3. Exposure And Constituent Map
必须拆持仓或指数方法论。若持仓尚未披露，必须明确标注 inferred，不得把推断写成事实。
必填字段：
holdings_statusconfirmed、partial、unavailable/inferredselection_universe成分股从哪里来：S&P 500、全球股票、特定行业、交易所上市资产、管理人自选池等selection_rules进入持仓的定量或定性规则top_holdings前十大或预期核心暴露top10_weight前十大集中度，未披露则写 unknownexposure_purity标的是否真有目标主题收入、资产、利润或现金流暴露constituent_transmissionETF 资金和叙事最可能传导到哪些股票、行业、国家或链条liquidity_sensitivity哪些低流动性、小市值或高权重标的更容易受 ETF 影响
4. Mode And Weighting Mechanics
管理模式和权重模式是 ETF 上市分析的核心，不是附录。
| mode / weighting | read-through | risk |
|---|---|---|
| market-cap weighted | 更像大市值 beta 或龙头 wrapper | 成分股机会可能已高度拥挤 |
| equal-weighted | 更容易把主题传导到中小权重公司 | 再平衡交易和低流动性风险更高 |
| modified cap / capped | 兼顾龙头和分散度 | cap 规则可能掩盖真实集中度 |
| theme-revenue / factor weighted | 可能提高主题纯度 | methodology 可能过拟合或样本不稳定 |
| liquidity-weighted | 更适合交易和大资金承载 | 牺牲主题纯度 |
| active discretionary | 代表管理人判断和分销意图 | 持仓漂移、风格漂移和披露滞后 |
| leveraged / inverse / single-stock | 代表交易和波动需求 | 不能外推为长期配置需求 |
必须检查：
rebalance_frequencysingle_name_capsector/country capsderivative_usageturnover_expectationindex_or_manager_discretion
Show full SKILL.md (168 more words)Show less
5. Peer And Timing Context
同类产品比较用于解释产品定位，不用于机械否定新 ETF：
- 新 ETF 是否比竞品更纯、更便宜、更主动、更高收益或更容易交易
- 发行人是否有分销优势或过往同类成功经验
- 主题处在早期产品化、主升扩散、拥挤尾声，还是回撤后再包装
- 若多个发行人同时推类似 ETF，说明主题进入产品竞赛
- 若竞品很多但都很小，可能是用户需求弱或主题表达困难
6. Post-Listing Tracking
上市后资金、成交和价差用于复盘，不是首轮分析的必要门槛。
跟踪重点：
- 5、20、60 个交易日 AUM 和净流入
- 成交量、买卖价差、折溢价
- 持仓披露是否确认首轮暴露判断
- 同类 ETF 是否出现新增需求或只是 cannibalization
- 再平衡和持仓变化是否带来成分股传导
- 发行人营销、媒体叙事、卖方讨论和期权生态是否扩散
Output Package
默认输出一份 etf-listing-analysis，至少包含：
- analysis setup
- core conclusion
- product anatomy
- issuer intent
- structure and access
- exposure and constituent map
- mode and weighting mechanics
- peer and category comparison
- bull interpretation
- bear interpretation
- practical trade/read-through
- post-listing tracking plan
- falsification conditions
- evidence log notes
如果 ETF 分析指向具体股票机会，再进入 equity-research-core：
- 先选成分股或受益链条
- 再执行
framework selection - 必要时叠加
supply-chain或variant-perception
Signal Interpretation
ETF 新上市通常可以有六种解释：
early-institutionalization主题开始从故事变成可配置产品，值得继续跟踪。confirmed-user-demand产品设计明显回应了用户、顾问或机构的现有需求。strategic-platform-move发行人通过新 ETF 表达自身业务方向或产品线迁移。late-cycle-packaging产品在主题拥挤、估值极高或散户热度很高时推出，更多是兑现情绪。synthetic-access-signalETF 解决了准入、托管、税务、监管、期限、杠杆或收益结构问题，重点在资产可达性变化。low-signal-lineup-fill主要是补货架、费率竞争或产品线防守，投资含义有限。
Quality Bar
- 不允许只凭 ETF 名字判断主题暴露
- 必须核对招募说明书、持仓、指数方法论或主动管理披露
- 必须明确
management_mode和weighting_mode - 必须区分 confirmed holdings 和 inferred holdings
- 必须解释发行人意图，不只复述产品介绍
- 必须比较同类 ETF，避免把普通产品线扩张误读成趋势信号
- 必须说明底层资产流动性是否足以让 ETF 持仓或再平衡产生价格影响
- 必须给出
what would falsify this listing signal - 如果持仓或方法论数据不足，只能输出
watchlist / needs-holdings-confirmation，不能升级为投资结论
Source Requirements
优先来源：
L1ETF 招募说明书、issuer product page、持仓披露、公告L2交易所、监管文件、指数提供商方法论L5AUM、净流入、成交量、价差、折溢价、成分股市场数据L3/L4ETF 行业研究、财经媒体、发行人访谈、策略评论
L3/L4 只能帮助解释产品语境和市场叙事，不能替代持仓、结构、权重机制和方法论。
Refresh Triggers
必须刷新分析的情况：
- 上市后 5、20、60 个交易日
- 持仓首次披露或发生大幅变化
- AUM 或净流入突破同类产品显著分位
- 成交量和价差明显改善或恶化
- 期权上市或衍生品使用明显增加
- 同主题出现多个竞品 ETF 或发行人撤回/清盘
- 底层主题出现政策、财报、监管或价格冲击
© byteseek, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (references) in skills/etf-listing-analysis of byteseek/Mira.
- SKILL.md
- references/etf-listing-framework.md
Open the folder on GitHubat commit adddce7
Compare with similar skills
Etf Listing Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
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|---|---|---|---|---|---|---|
| Etf Listing Analysis this skillbyteseek/Mira | 275 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
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More from byteseek/Mira
All 10 skills in this repoEtf Listing Discovery
byteseek/Mira
Discover listed, pending, filed, or newly announced ETFs and create a structured candidate watchlist for ETF listing analysis.
Equity Research Core
byteseek/Mira
Run Mira's core single-equity research workflow across fundamentals, financial quality, macro context, technical pricing, events, and thesis framing.
Commodity Cycle Analysis
byteseek/Mira
Analyze commodity cycles, futures curves, inventories, cost curves, policy/geopolitics, positioning, and transmission into related assets.
Data Analysis Quality Gate
byteseek/Mira
Gate quantitative Mira conclusions by requiring reproducible data, formulas, calculation ledgers, or explicit downgrades when numbers drive judgment.
Earnings Report Analysis
byteseek/Mira
Analyze earnings releases, filings, transcripts, guidance, peer comparisons, market reaction, and thesis impact for a company reporting event.
Industry Concept Analysis
byteseek/Mira
Map an unclear industry concept into boundaries, value chain, supply-demand mechanics, profit pools, evidence gaps, and investable candidates.
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Questions about Etf Listing Analysis
What does Etf Listing Analysis do?
Analyze new, pending, or expanding ETF products as product signals, exposure maps, demand indicators, and potential asset-pricing read-throughs. Etf Listing Analysis is an agent skill from byteseek/Mira. Analyze new, pending, or expanding ETF products as product signals, exposure maps, demand indicators, and potential asset-pricing read-throughs.
When should I use Etf Listing Analysis?
Etf Listing Analysis fits situations like: tasks that involve Stock and market analysis.
How do I install Etf Listing Analysis in Claude Code?
Run `npx skills add byteseek/Mira --skill etf-listing-analysis -a claude-code`. Or copy the skill folder (skills/etf-listing-analysis in byteseek/Mira) into .claude/skills/etf-listing-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Etf Listing Analysis in Codex?
Run `npx skills add byteseek/Mira --skill etf-listing-analysis -a codex`. Or copy the skill folder (skills/etf-listing-analysis in byteseek/Mira) into .agents/skills/etf-listing-analysis in your project. Codex loads it when a task matches its description.
Can I use Etf Listing Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add byteseek/Mira --skill etf-listing-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/etf-listing-analysis, .gemini/skills/etf-listing-analysis, .github/skills/etf-listing-analysis and .opencode/skills/etf-listing-analysis in your project.
What does Etf Listing Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Etf Listing Analysis is instructions for the agent only.
Does Etf Listing Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Etf Listing Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Etf Listing Analysis use?
Etf Listing Analysis is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Etf Listing Analysis use?
About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.
What are the alternatives to Etf Listing Analysis?
Skills that share tags, products or a category with Etf Listing Analysis: Stock API (zhangxiangliang/stock-api, 2k stars), Tushare Data (zillionare/zillionare, 321 stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars) and Digital Oracle (komako-workshop/digital-oracle, 878 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Etf Listing Analysis?
byteseek (a GitHub organization) maintains it in byteseek/Mira, which has 275 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 8, 2026.
Source: byteseek/Mira on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.