Markdown Article Formatter
JimLiu/baoyu-skills
Reformats plain text or Markdown articles with frontmatter, a title, a summary, headings, bold, lists and code blocks, and saves a separate formatted copy.
预测美股个股次日走势，输出图文并茂的 Markdown 分析报告（含逻辑推导、中间结果、概率量化、操作建议）。触发条件：用户输入美股股票名称或代码，并希望获得次日走势预测；关键词包括"预测明天走势"、"明天能涨吗"、"帮我分析一下XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、"值得持有吗"等。即使用户只说"帮我看看NVDA明天怎么走"或"AAPL明天能不能买…
Install Us Stock Predictor
$ npx skills add digoal/blog --skill us-stock-predictor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install digoal/blog us-stock-predictor --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/digoal/blog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skills_for_claude_web/us-stock-predictor .claude/skills/us-stock-predictor && 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 "us-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/us-stock-predictor into .claude/skills/us-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-stock-predictor", 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/digoal/blog/tree/master/skills/skills_for_claude_web/us-stock-predictorType 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 digoal/blog --skill us-stock-predictor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install digoal/blog us-stock-predictor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/skills_for_claude_web/us-stock-predictor .agents/skills/us-stock-predictor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "us-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/us-stock-predictor into .agents/skills/us-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-stock-predictor", 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 digoal/blog --skill us-stock-predictor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install digoal/blog us-stock-predictor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/skills_for_claude_web/us-stock-predictor .cursor/skills/us-stock-predictor && 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 "us-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/us-stock-predictor into .cursor/skills/us-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-stock-predictor", 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/digoal/blog.git --path skills/skills_for_claude_web/us-stock-predictor--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 digoal/blog --skill us-stock-predictor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install digoal/blog us-stock-predictor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/skills_for_claude_web/us-stock-predictor .gemini/skills/us-stock-predictor && 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 "us-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/us-stock-predictor into .gemini/skills/us-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-stock-predictor", 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 digoal/blog us-stock-predictorInstalls 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 digoal/blog --skill us-stock-predictor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/skills_for_claude_web/us-stock-predictor .github/skills/us-stock-predictor && 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 "us-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/us-stock-predictor into .github/skills/us-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-stock-predictor", 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 digoal/blog --skill us-stock-predictor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install digoal/blog us-stock-predictor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/digoal/blog.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/skills_for_claude_web/us-stock-predictor .opencode/skills/us-stock-predictor && 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 "us-stock-predictor" agent skill from https://github.com/digoal/blog/tree/master/skills/skills_for_claude_web/us-stock-predictor into .opencode/skills/us-stock-predictor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "us-stock-predictor", 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
us-stock-predictor- GitHub stars
- 8.6k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 147 words
- Files
- 2 (incl. references)
- Skills in repo
- 98
- Repo updated
- First seen
- Licence
- GPL-2.0
At a glance
预测美股个股次日走势，输出图文并茂的 Markdown 分析报告（含逻辑推导、中间结果、概率量化、操作建议）。触发条件：用户输入美股股票名称或代码，并希望获得次日走势预测；关键词包括"预测明天走势"、"明天能涨吗"、"帮我分析一下XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、"值得持有吗"等。即使用户只说"帮我看看NVDA明天怎么走"或"AAPL明天能不能买…
- Works in 9 steps: ：解析输入 → ：多线搜索（并行收集数据） → ：逐维打分 → …
- Tasks that involve Markdown
- SKILL.md covers 核心方法论, 执行流程（Step-by-Step）, 报告结构模板 and 可视化图表规范, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Us Stock Predictor is an agent skill from digoal/blog. 预测美股个股次日走势，输出图文并茂的 Markdown 分析报告（含逻辑推导、中间结果、概率量化、操作建议）。触发条件：用户输入美股股票名称或代码，并希望获得次日走势预测；关键词包括"预测明天走势"、"明天能涨吗"、"帮我分析一下XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、"值得持有吗"等。即使用户只说"帮我看看NVDA明天怎么走"或"AAPL明天能不能买"，也应使用本 skill。输出 Markdown 文件保存到当前项目 markdown/ 目录，要求逻辑清晰、概率可量化、图文并茂，投资小白也能看懂。
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/methodology.md`).
It sits in Documents & Office, covering Markdown. The repository describes itself as: AI,Opensource,Database,Business,Finance,Minds. git clone --depth 1 https://github.com/digoal/blog. The licence is GPL-2.0.
When your agent uses it
- Tasks that involve Markdown
Example prompts
- “预测明天走势”
- “帮我分析一下XX股票”
- “等。即使用户只说”
- “/us-stock-predictor”
Workflow steps
9 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 ad6fcb7. 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 (its code samples are markdown).
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
Us Stock Predictor loads about 1.1k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 147 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 digoal/blog at commit ad6fcb7, republished under its GPL-2.0 licence (© digoal). 147 words, ~1,068 tokens.
Download SKILL.mdSave it as
.claude/skills/us-stock-predictor/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- us-stock-predictor
- description
- 预测美股个股次日走势，输出图文并茂的 Markdown 分析报告（含逻辑推导、中间结果、概率量化、操作建议）。触发条件：用户输入美股股票名称或代码，并希望获得次日走势预测；关键词包括"预测明天走势"、"明天能涨吗"、"帮我分析一下XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、"值得持有吗"等。即使用户只说"帮我看看NVDA明天怎么走"或"AAPL明天能不能买"，也应使用本 skill。输出 Markdown 文件保存到当前项目 markdown/ 目录，要求逻辑清晰、概率可量化、图文并茂，投资小白也能看懂。
美股个股次日走势预测 Skill
核心方法论
使用 MTVSF 五维框架（详见 references/methodology.md）：
- M - Macro Pulse 宏观脉搏（权重15%）
- T - Technical Signals 技术信号（权重30%）
- V - Valuation & Fundamentals 估值基本面（权重20%）
- S - Sentiment & News Flow 情绪与消息流（权重25%）
- F - Fund Flow & Positioning 资金流与持仓（权重10%）
执行流程（Step-by-Step）
Step 1：解析输入
- 识别股票代码（如 AAPL）或名称（如苹果）
- 标准化为美股 Ticker 代码
Step 2：多线搜索（并行收集数据）
同时搜索以下信息：
搜索1："{TICKER} stock price today technical analysis"
搜索2："{TICKER} news today tomorrow catalyst"
搜索3："{TICKER} analyst rating upgrade downgrade {当前年份}"
搜索4："{TICKER} options unusual activity put call ratio"
搜索5："VIX index today market sentiment"
搜索6："{TICKER} earnings date next quarter"
搜索7："{TICKER} short interest short float"
搜索8："S&P 500 futures tomorrow {当前日期}"数据收集清单（必须尽量填满）：
| 维度 | 数据项 | 来源 |
|---|---|---|
| 宏观 | VIX当前值、美债10Y收益率、标普期货方向 | 搜索 |
| 技术 | 当日收盘价、RSI(14)、MACD信号、均线位置、成交量vs均量 | 搜索 |
| 基本面 | P/E、下次财报日、近期EPS修正 | 搜索 |
| 情绪 | 今日重要新闻、分析师评级变动、Put/Call Ratio | 搜索 |
| 资金 | 期权异动、机构动向、资金净流向 | 搜索 |
Step 3：逐维打分
对每个维度独立评分，记录推理过程：
M得分（0-15）= 宏观顺风/逆风程度
T得分（0-30）= 技术信号强弱与一致性
V得分（0-20）= 估值合理性与基本面动量
S得分（0-25）= 消息面正负面及强度
F得分（0-10）= 资金流方向与聪明钱信号
总分 = M + T + V + S + F（满分100）Step 4：三情景概率分布
输出三种情景的概率（必须合计100%）：
- 情景A（看涨）：明日涨幅 > +1%，概率 P_A%
- 情景B（震荡）：明日涨跌 -1% ~ +1%，概率 P_B%
- 情景C（看跌）：明日跌幅 > -1%，概率 P_C%
计算预期收益：
E = P_A × 典型涨幅 + P_B × 0 + P_C × 典型跌幅若 E > 0 且 风险收益比 > 1.5，具有操作价值。
Step 5：输出 Markdown 报告
报告结构模板
报告必须包含以下七个部分，配合可视化图表：
# {股票名称}（{TICKER}）次日走势预测报告
> 分析日期：{日期} | 分析师：MTVSF量化模型
## ⚡ 核心结论（30秒速览）
[一句话结论 + 操作建议 + 置信度]
## 📊 五维评分仪表盘
[ASCII 或 SVG 可视化评分图]
## 🌍 第一维：宏观环境（M，满分15）
[分析 + 得分 + 理由]
## 📈 第二维：技术信号（T，满分30）
[K线形态描述 + 各指标解读 + ASCII走势图 + 得分]
## 💰 第三维：估值基本面（V，满分20）
[估值合理性 + 财报风险 + 得分]
## 📰 第四维：情绪与消息（S，满分25）
[重要新闻 + 市场情绪 + 期权信号 + 得分]
## 🏦 第五维：资金流向（F，满分10）
[资金净流 + 机构动向 + 得分]
## 🎯 综合评分与概率分布
[总分 + 三情景概率 + 预期收益计算]
## ⚠️ 风险提示与操作建议
[具体止损位 + 目标位 + 仓位建议 + 禁忌]可视化图表规范
1. 五维雷达图（SVG）
使用 SVG 绘制五边形雷达图，显示五维得分占比
颜色：绿色=高分，红色=低分，黄色=中性2. 技术走势图（ASCII）
用 ASCII 字符模拟近期价格走势和关键均线位置
示例：
┌─────────────────────────────────────────────┐
│ {TICKER} 近10日走势示意 │
│ ▲ │
│ │ ╭──╮ ←── 阻力位 $xxx │
│ │ ╭╯ ╰──╮ │
│ │ ╭╯ ╰──╮ ←── 当前价 $xxx │
│ │ ╭╯ ╰╮ │
│ │─────────────── MA20 ($xxx) ─ ─ ─ │
│ │─────────────── MA50 ($xxx) ────── │
│ │ ╰──╯ ←── 支撑位 $xxx │
└─────────────────────────────────────────────┘3. 概率分布图（ASCII）
用横向条形图显示三情景概率
示例：
情景A（看涨）: ████████░░░░░░░░░░░░ 40%
情景B（震荡）: ████████████░░░░░░░░ 35%
情景C（看跌）: █████████░░░░░░░░░░░ 25%4. 信号汇总表（Mermaid 或 ASCII 表格）
所有技术信号 → 方向 → 强度 → 权重 的汇总专业术语词典（报告中首次出现时附注释）
| 术语 | 简单解释 |
|---|---|
| RSI | 相对强弱指数，衡量涨跌速度，>70超买，<30超卖 |
| MACD | 移动平均线的差值，判断趋势动能方向 |
| 布林带 | 价格波动区间，上轨附近有压力，下轨有支撑 |
| VIX | 恐惧指数，越高市场越恐慌 |
| Put/Call Ratio | 看跌/看涨期权比值，越高越悲观 |
| Short Interest | 短卖比例，空头持仓 |
| OBV | 能量潮，用成交量验证价格趋势 |
| P/E | 市盈率，股价/每股盈利 |
| EPS | 每股盈利 |
| 催化剂 | 可能推动股价大幅波动的事件 |
风险控制模块（每份报告必须包含）
## ⚠️ 风险提示
### 止损位设置
- 技术止损：跌破 [关键支撑位] 止损出局
- 幅度止损：亏损超过 -3% 无条件止损
### 特别警告
- 若距离财报 ≤ 5 个交易日：建议仓位减半或回避
- 若 VIX > 30：建议全面回避短线操作
- 本报告仅供参考，不构成投资建议
### 置信度声明
当以下情况存在时，本报告置信度降低：
❌ 数据不完整（关键指标无法获取）
❌ 信号严重矛盾（多空信号各半）
❌ 宏观面极端不稳定
❌ 当日为重大事件前夕（FOMC会议、CPI公布等）输出文件规范
文件名：{TICKER}-next-day-forecast-{YYYYMMDD}.md
保存路径：markdown/
编码：UTF-8
语言：中文为主，专业术语保留英文并附中文注释质量检查清单（输出前自查）
- 五维均已分析，无跳过项
- 所有专业术语首次出现均有解释
- 三情景概率合计 = 100%
- 包含止损位建议
- 包含财报日提醒
- 可视化图表至少 3 个（雷达图 + 走势示意 + 概率分布）
- 结论部分清晰说明"买/卖/观望"
- 包含免责声明
局限性说明
- 次日预测准确率行业标准约 55-65%，本模型不保证超越此范围
- 重大突发消息（黑天鹅）可使任何预测失效
- 本报告不构成投资建议，操作风险自负
© digoal, GPL-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/skills_for_claude_web/us-stock-predictor of digoal/blog.
- SKILL.md
- references/methodology.md
Open the folder on GitHubat commit ad6fcb7
Compare with similar skills
Us Stock Predictor 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Us Stock Predictor this skilldigoal/blog | 8.6k | — | ~1.1k | Automated safety check: Pass | GPL-2.0 | |
| Markdown Article FormatterJimLiu/baoyu-skills | 26k | 6 repos | ~3.5k | Automated safety check: Pass | MIT | |
| MarkitdownImCa0/just-laws | 782 | 14 repos | ~3.2k | Automated safety check: Notes | MIT | |
| Obsidian MarkdownAtmosphere/atmosphere | 3.8k | 20 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Gzh Designisjiamu/gzh-design-skill | 3.9k | 1 repos | ~2.2k | Automated safety check: Pass | AGPL-3.0 | |
| Crosspostingwasp-lang/wasp | 19k | — | ~1.1k | Automated safety check: Pass | MIT |
Similar skills
Markitdown
ImCa0/just-laws
Convert files and office documents to Markdown. An agent skill from ImCa0/just-laws.
Obsidian Markdown
Atmosphere/atmosphere
Create and edit Obsidian Flavored Markdown with wikilinks, embeds, callouts, properties, and other Obsidian-specific syntax.
Gzh Design
isjiamu/gzh-design-skill
微信公众号文章排版引擎，将 Markdown 转换为可直接粘贴到公众号编辑器的 HTML。主题风格从 references/theme-index.md 注册的自定义主题库中选取，自动章节编号、关键词下划线标记、引言卡片、目录导航、代码块、图片/GIF、作者签名。支持 Markdown / Word(.docx) / PDF / 纯文本输入（非 Markdown…
Crossposting
wasp-lang/wasp
Crosspost Wasp blog articles (MDX) to DEV.to and Medium. An agent skill from wasp-lang/wasp.
- Official
Review The Docs
supabase/supabase
Review Supabase docs changes locally in your supabase/supabase checkout — either an open PR (triage, classify, verify) or your own branch before opening a PR (local self-review).
More from digoal/blog
All 98 skills in this repoArticle Fact Checker
digoal/blog
三层审查模型,逐段逐句验证文章真伪、证据链与逻辑结构。Use when the user asks to fact-check, verify, audit, or evaluate the credibility of an article, essay, report, opinion piece, social-media post, or any written claim —…
Find Postgres Bug
digoal/blog
Find latent bugs in a local PostgreSQL source tree (RELxxSTABLE branch or HEAD) the way a core hacker does: build a heavily-poisoned debug instance (cassert + cache-discard + -O0/-ggdb3 + core…
Digoal
digoal/blog
Portable digital employee distilled from digoal's personal blog for PostgreSQL, PolarDB, DuckDB, AI+database, vector/RAG, database operations, source-code reading, technical content creation…
Paper Interpretation
digoal/blog
从论文 PDF 文件或论文 PDF URL 生成通俗易懂、图文并茂、带批判性评估的中文 Markdown 解读，并保存到当前项目的 markdown 目录。Use when the user asks to interpret,精读,解读,summarize,explain,analyze, or write an article from an academic paper PDF…
Product Multi Role Analysis
digoal/blog
Analyze a product from documentation, websites, PDFs, articles, release notes, pricing pages, app listings, reviews, filings, or related links; save separate intermediate analyses from seven roles…
Blog Cover Poster
digoal/blog
Turn a blog post, article, notes, or any source material into a set of vertical poster images — one cover plus several coherent content slides that explain the core points.
Related
Categories
Questions about Us Stock Predictor
What does Us Stock Predictor do?
预测美股个股次日走势，输出图文并茂的 Markdown 分析报告（含逻辑推导、中间结果、概率量化、操作建议）。触发条件：用户输入美股股票名称或代码，并希望获得次日走势预测；关键词包括"预测明天走势"、"明天能涨吗"、"帮我分析一下XX股票"、"明天该买吗"、"次日预测"、"做T建议"、"短线操作"、"明日行情"、"值得持有吗"等。即使用户只说"帮我看看NVDA明天怎么走"或"AAPL明天能不能买…. Us Stock Predictor is an agent skill from digoal/blog.
When should I use Us Stock Predictor?
Us Stock Predictor fits situations like: tasks that involve Markdown.
How do I install Us Stock Predictor in Claude Code?
Run `npx skills add digoal/blog --skill us-stock-predictor -a claude-code`. Or copy the skill folder (skills/skills_for_claude_web/us-stock-predictor in digoal/blog) into .claude/skills/us-stock-predictor in your project. Claude Code loads it when a task matches its description.
How do I install Us Stock Predictor in Codex?
Run `npx skills add digoal/blog --skill us-stock-predictor -a codex`. Or copy the skill folder (skills/skills_for_claude_web/us-stock-predictor in digoal/blog) into .agents/skills/us-stock-predictor in your project. Codex loads it when a task matches its description.
Can I use Us Stock Predictor 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 digoal/blog --skill us-stock-predictor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/us-stock-predictor, .gemini/skills/us-stock-predictor, .github/skills/us-stock-predictor and .opencode/skills/us-stock-predictor in your project.
What does Us Stock Predictor need to run?
SKILL.md names no scripts, command-line tools or credentials: Us Stock Predictor is instructions for the agent only.
Does Us Stock Predictor 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 Us Stock Predictor 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 Us Stock Predictor use?
Us Stock Predictor is published under the GPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Us Stock Predictor use?
About 1.1k tokens (SKILL.md is roughly 4.3k 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 1.7k tokens, read only when the agent opens those files.
What are the alternatives to Us Stock Predictor?
Skills that share tags, products or a category with Us Stock Predictor: Markdown Article Formatter (JimLiu/baoyu-skills, 26k stars), Markitdown (ImCa0/just-laws, 782 stars), Obsidian Markdown (Atmosphere/atmosphere, 3.8k stars) and Gzh Design (isjiamu/gzh-design-skill, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Us Stock Predictor?
digoal (a GitHub user) maintains it in digoal/blog, which has 8,586 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on October 9, 2026.
Source: digoal/blog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.