Bright Data MCP
brightdata/skills
Bright Data MCP handles ALL web data operations. An agent skill from brightdata/skills.
Searches and fetches pages through a real logged-in Chromium session when ordinary API or HTML retrieval cannot get past login walls, scripts or anti-bot checks.
SKILL.md written in Chinese; this summary is our English description.
$ npx skills add taxueseek/argo --skill ego-search -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install taxueseek/argo ego-search --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/taxueseek/argo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sub-skills/ego-search .claude/skills/ego-search && 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 "ego-search" agent skill from https://github.com/taxueseek/argo/tree/main/sub-skills/ego-search into .claude/skills/ego-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ego-search", 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/taxueseek/argo/tree/main/sub-skills/ego-searchType 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 taxueseek/argo --skill ego-search -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install taxueseek/argo ego-search --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/taxueseek/argo.git skills-src && mkdir -p .agents/skills && cp -r skills-src/sub-skills/ego-search .agents/skills/ego-search && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ego-search" agent skill from https://github.com/taxueseek/argo/tree/main/sub-skills/ego-search into .agents/skills/ego-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ego-search", 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 taxueseek/argo --skill ego-search -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install taxueseek/argo ego-search --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/taxueseek/argo.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/sub-skills/ego-search .cursor/skills/ego-search && 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 "ego-search" agent skill from https://github.com/taxueseek/argo/tree/main/sub-skills/ego-search into .cursor/skills/ego-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ego-search", 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/taxueseek/argo.git --path sub-skills/ego-search--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 taxueseek/argo --skill ego-search -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install taxueseek/argo ego-search --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/taxueseek/argo.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/sub-skills/ego-search .gemini/skills/ego-search && 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 "ego-search" agent skill from https://github.com/taxueseek/argo/tree/main/sub-skills/ego-search into .gemini/skills/ego-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ego-search", 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 taxueseek/argo ego-searchInstalls 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 taxueseek/argo --skill ego-search -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/taxueseek/argo.git skills-src && mkdir -p .github/skills && cp -r skills-src/sub-skills/ego-search .github/skills/ego-search && 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 "ego-search" agent skill from https://github.com/taxueseek/argo/tree/main/sub-skills/ego-search into .github/skills/ego-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ego-search", 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 taxueseek/argo --skill ego-search -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install taxueseek/argo ego-search --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/taxueseek/argo.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/sub-skills/ego-search .opencode/skills/ego-search && 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 "ego-search" agent skill from https://github.com/taxueseek/argo/tree/main/sub-skills/ego-search into .opencode/skills/ego-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ego-search", 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.
ego-searchSearches and fetches pages through a real logged-in Chromium session when ordinary API or HTML retrieval cannot get past login walls, scripts or anti-bot checks.
This sub-skill of the argo search tool, documented in Chinese, drives a real browser runtime for content that plain HTTP retrieval misses: pages behind logins on sites such as Zhihu, Xiaohongshu, Weibo and X, JavaScript-rendered and single-page apps, pages behind anti-bot checks (best effort, heavy protection may still fail), interactive searches with paging or load-more, live search result pages, and same-origin API endpoints that can be called directly.
Professional search mode is off by default and is switched on with an enable command, which the agent may run only when you explicitly ask for it. Once on, search, fetch, act and api commands are available. Two runtimes are supported and complement each other: the ego lite browser and a bridge to your own browser extension, and either one being online is enough. Results print as JSON to stdout.
Every result carries provenance fields marking that a login state was used, that it belongs to the login partition, that it must not be written to the shared public search cache, and that it may still be merged with public results for evidence scoring. The skill advises trying ordinary retrieval first because it is faster and cheaper, and escalating only when results or page text are missing.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit a6657b0. It shows what the files ask for, not the result of running them.
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.
Ships 7 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
zhihu.comcn.bing.comAlso links to:
lite.ego.appkimi.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Ego Browser Search loads about 2.1k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 109 tokens; SKILL.md has 473 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.
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); the scripts in this folder are not scanned.
The full file from taxueseek/argo at commit a6657b0, republished under its MIT licence (© taxueseek). 473 words, ~2,123 tokens.
.claude/skills/ego-search/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.ego-search 是 argo 的登录态专业搜索子技能(v1.4 完全态):
ego-browser)与 WebBridge(用户浏览器扩展桥)互补,不互相替代search / fetch / act / api 在至少一条运行时在线时可用cache_eligible=false,禁止进公共 SearchCachemerge_with_public_ok=true,分析层可把 public + login 两路结果一起喂 evidence本子技能涉及真实浏览器登录态继承,出于安全与可靠性考虑默认关闭。开启后
search/fetch/act/api 与直接浏览器操作才可用;未开启时调用会被拒绝并提示开启命令。
# 开启(必须由用户明确要求「开启专业搜索模式」后执行)
python3 sub-skills/ego-search/scripts/ego_search.py enable
# 关闭
python3 sub-skills/ego-search/scripts/ego_search.py disable
# 查看状态
python3 sub-skills/ego-search/scripts/ego_search.py statusenable。~/.local/state/ego-search/pro-mode.json,开启后长期生效,直到手动关闭。主系统 API/HTML 检索覆盖不足时,升级到 ego-search:
| 场景 | 常规检索 | ego-search 补什么 |
|---|---|---|
| 登录墙内容(知乎/小红书/微博/X/公众号/会员站) | 拿不到正文 | 任务空间继承登录态,搜并抓取 |
| JS 渲染 / SPA / 懒加载页面 | 可能空壳 | 真实浏览器执行 JS 后提取 |
| 反爬 / Cloudflare 保护(尽力而为) | HTTP 失败 | 真实浏览器尝试,重度防护可能失败 |
| 需要交互的动态搜索(翻页/「加载更多」/表单筛选) | 单次请求不够 | act 或 ego-browser heredoc 多步 |
| 搜索引擎实时 SERP(Google/Bing/百度) | 可能被反爬 | 真实 SERP 结构化提取 |
| 深嵌套 iframe 页面 | 常挂 | 快照专长 |
| 已知同源 API URL | DOM 不全 | api + browserFetch |
| 未知 XHR 尚未拿到 URL | — | 不在 CLI 内;heredoc 自探或先拿 URL 再 api |
决策顺序:
常规检索(快、省 token)
→ 结果不足 / 正文拿不到 / 需要登录态
→ ego-search search|fetch|act|api(pro-mode 开启)
→ 更复杂多步 → ego-browser nodejs heredoc
高后果结论 → 证据核验ego-browser(~/.local/bin)。command -v ego-browser。未安装时按 references/install.md 完成安装。# 首次使用:先开启专业搜索模式(需用户确认;开启后长期生效)
python3 sub-skills/ego-search/scripts/ego_search.py enable
# 探测运行时与专业模式(--fix 幂等启 WebBridge 桥)
python3 sub-skills/ego-search/scripts/ego_search.py status [--fix]
# 浏览器态搜索(真实 SERP,输出 argo JSON schema)
# --runtime auto(默认: 有 ego 用 ego,否则 webbridge) | ego | webbridge
python3 sub-skills/ego-search/scripts/ego_search.py search "AI agent 浏览器自动化" --engine bing --n 8
# 强制登录态站点搜索(如知乎/小红书,需登录态)
python3 sub-skills/ego-search/scripts/ego_search.py search "site:zhihu.com AI 搜索" --engine bing
# 浏览器态正文提取(JS 渲染/反爬/登录墙页面)
python3 sub-skills/ego-search/scripts/ego_search.py fetch "https://example.com/article" --focus 关键词
# 同源 API 数据直取(登录态站点接口)
python3 sub-skills/ego-search/scripts/ego_search.py api "https://www.zhihu.com/api/v4/search_v3?t=general&q=AI代理&limit=5" --origin "https://www.zhihu.com"
# 指定任务空间名(同一目标的多轮操作复用同名空间)
python3 sub-skills/ego-search/scripts/ego_search.py search "竞品分析" --task-space "竞品调研"输出约定:JSON 到 stdout(机器可读,可管道给 evidence.py / 解析喂 RRF),日志到 stderr。
所有 search / fetch / act / api 输出均带:
| 字段 | 值 | 含义 |
|---|---|---|
login_state_used | true | 使用了浏览器登录态 |
auth_partition | login | 认证分区标签(不写 cookie) |
cache_eligible | false | 禁止写入 argo 公共 SearchCache / set_fetch |
search_partition | login | 与常规 public 检索分区隔离 |
merge_with_public_ok | true | 允许在汇总分析时与 public 结果一并送入 evidence |
runtime | ego | webbridge | 实际使用的运行时 |
公共库路径 ~/.cache/unified-search/cache.db 在 set / set_engine / set_fetch 入口会硬拒绝
此类载荷。登录态结果默认不缓存 body。
| 阶段 | 规则 |
|---|---|
| 检索 | public(argo)与 login(本技能)分开跑、分 cache、分 partition |
| 缓存 | login 永不进 argo 公共缓存;两路互不 soft-hit |
| 汇总 | Agent 可将两路 results / 正文一并交给 evidence 或报告生成;用 source / runtime / search_partition 区分权重与可信语境 |
| 控制 | 默认 | 说明 |
|---|---|---|
| 专业模式闸门 | 关 | 需用户 enable 后才跑登录态检索 |
| URL 守卫 | 拦 | fetch/api/navigate 仅 http(s),默认禁本机/字面私有 IP;EGO_SEARCH_STRICT_SSRF=1 全量 DNS;ARGO_ALLOW_PRIVATE_URLS=1 放行 |
| 任务空间收尾 | 关空间 | ego 路径默认 completeTaskSpace keep:false,防标签堆积 |
--keep-space / --site | 见右 | 多轮保温;--site zhihu.com → site:zhihu.com 并默认 keep |
| 登录墙质量信号 | 开 | fetch/act 输出 quality.auth_wall_suspected / login_likely_ok |
| WebBridge session | 不自动 close_session | 避免误关用户标签 |
| 公共缓存 | 拒写 | cache_eligible=false + SearchCache 硬守卫 |
| 分析融合 | merge | 与 public 结果隔离缓存、汇总时用 merge --public --login |
| 降级 | auto | 任一安装即可;ego 优先,失败降 WebBridge |
登录态稳定建议:
--site zhihu.com(或 --task-space site:zhihu.com --keep-space) quality.login_likely_ok=false → 在 ego App 或用户 Chrome 人工登录后重试 merge打开指定搜索引擎的真实结果页,js() 提取结构化 SERP,输出:
{
"query": "AI agent 浏览器自动化",
"engine": "ego_browser_bing",
"source": "ego-browser",
"url": "https://cn.bing.com/search?q=...",
"results": [
{"title": "...", "url": "https://...", "snippet": "..."}
],
"count": 8,
"fetch_method": "browser",
"login_state_used": true,
"auth_partition": "login",
"cache_eligible": false
}--engine:bing(默认,最稳)/ baidu(中文)/ google(需网络可达,可能弹验证)。--n:结果条数(默认 8)。fetch 打开结果页取正文后再下判断(与 argo「SERP 链禁止当正文来源」纪律一致)。浏览器态正文提取。优先 article/main/[role=main] 等语义容器,回退 document.body.innerText,
输出 { url, title, content, word_count, fetch_method: "browser" },正文可管道给 argo 质量信号分析。
--focus 关键词:若传,只返回包含该关键词附近的段落(减少 token)。浏览器上下文同源 API 数据直取(v1.1.0)。
先打开目标站点页面(继承登录态),再用 browserFetch 从该页面上下文请求同源接口,
拿回结构化 JSON/文本。覆盖 DOM 提取拿不到的场景:
search_v3),比解析 SERP 更干净。{
"api_url": "https://www.zhihu.com/api/v4/search_v3?t=general&q=...",
"page_url": "https://www.zhihu.com/",
"page_title": "(1 条消息) 首页 - 知乎",
"data": { "paging": {...}, "data": [...] },
"data_type": "json",
"fetch_method": "browser_api"
}--origin:登录态上下文页面 URL。默认取 API URL 同源(scheme://host);
跨子域场景(如 cn.bing.com 请求 www.bing.com)须显式指定,否则 browserFetch 受
同源约束失败。data_type:json / text / error(跨域、网络错误等归一化为 error,脚本不崩)。data 超 100KB 时截断并标记 truncated: true、data_type 加
_truncated 后缀。argo_evidence 核验。把「搜索 → 点开结果 → 抓正文」等常见链式动作一次跑完。
支持 --engine bing|baidu|google(与 search 同表,默认 bing)。
输出含 query / results / detail 与登录态 provenance。
更复杂的多步交互(登录、表单、翻页、对比多个页面)用 ego-browser nodejs heredoc;
ego_search.py 只覆盖高频确定路径。
results 可直接喂
python3 scripts/evidence.py "查询词" --stdin --json 做 Selection×Absorption 评分;
正文可复用 content_signals / content_security 检查。source=ego-browser / engine=ego_browser_<engine> 可参与多源去重;
envelope 会标 login_state_used=true。不得把该路结果写入公共 SearchCache。cache_eligible=false + SearchCache 硬守卫。~/.cache/ego-search/,键含 auth_partition,禁止 soft-hit 公共 combo。复杂交互、heredoc 全 helper 速查、任务空间归属权纪律 → references/browser-runtime.md;安装细节 → references/install.md;升级到原版运行时 → references/original-ego-upgrade.md。
references/install.md(依赖安装)© taxueseek, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 11 other files (scripts, references) in sub-skills/ego-search of taxueseek/argo.
Open the folder on GitHubat commit a6657b0
Ego Browser Search 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 |
|---|---|---|---|---|---|---|
| Ego Browser Search this skilltaxueseek/argo | 188 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Bright Data MCPbrightdata/skills | 264 | 1 repos | ~3.7k | Automated safety check: Pass | MIT | |
| Web Access via Browser CDPeze-is/web-access | 9.1k | 4 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Reddit JSON Fetcherykdojo/claude-code-tips | 10k | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Scrapingbee CLIScrapingBee/scrapingbee-cli | 108 | — | ~3.2k | Automated safety check: Notes | MIT | |
| Web AccessZhanlinCui/Agent-Skills-Hunter | 191 | — | ~1.4k | Automated safety check: Pass | MIT |
brightdata/skills
Bright Data MCP handles ALL web data operations. An agent skill from brightdata/skills.
eze-is/web-access
Routes every web task, from searching to logged-in browsing, through a tiered choice of search, fetch, curl or a real Chrome or Edge session driven over CDP.
ykdojo/claude-code-tips
Fetches Reddit posts, threads and search results as JSON through a browser session, using a DuckDuckGo redirect to get past Reddit's automated-access block.
ScrapingBee/scrapingbee-cli
Fetch and read any web page, search the web, crawl a site, or pull structured data out of pages.
ZhanlinCui/Agent-Skills-Hunter
Routes every networked task to the lightest channel that reaches it: a direct search, a page fetch, or a persistent browser for logins and dynamic pages.
tinyfish-io/tinyfish-cookbook
Use TinyFish for web search, fetching URLs, reading pages, current information, source-backed answers, research, docs, pricing/product pages, extraction, scraping, and browser automation.
taxueseek/argo
Unified web search, page fetching and evidence checking across hundreds of sources, with result verification, a research-dossier mode and vertical search engines.
taxueseek/argo
Searches local files and code through one script, seek.py, that picks between rg, fd and macOS Spotlight and works in three layers: locate, context, close reading.
taxueseek/argo
Runs web-page JavaScript without a browser, in a V8 sandbox with a browser-environment shim, for scripts that only probe the environment and compute a result.
taxueseek/argo
Zero-cost fallback for the argo search skill, wrapping 29 local engines for web, news, academic, code and reference queries when paid API quota should be saved.
Searches and fetches pages through a real logged-in Chromium session when ordinary API or HTML retrieval cannot get past login walls, scripts or anti-bot checks. This sub-skill of the argo search tool, documented in Chinese, drives a real browser runtime for content that plain HTTP retrieval misses: pages behind logins on sites such as Zhihu, Xiaohongshu, Weibo and X, JavaScript-rendered and single-page apps, pages behind anti-bot checks (best effort, heavy protection may still fail), interactive searches with paging or load-more, live search result pages, and same-origin API endpoints that can be called directly.
Ego Browser Search fits situations like: searching content that sits behind a login wall; extracting results from JavaScript-rendered or single-page sites; paging through or expanding a dynamic search that one request cannot cover; fetching data from a known same-origin API through the browser.
Run `npx skills add taxueseek/argo --skill ego-search -a claude-code`. Or copy the skill folder (sub-skills/ego-search in taxueseek/argo) into .claude/skills/ego-search in your project. Claude Code loads it when a task matches its description.
Run `npx skills add taxueseek/argo --skill ego-search -a codex`. Or copy the skill folder (sub-skills/ego-search in taxueseek/argo) into .agents/skills/ego-search in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add taxueseek/argo --skill ego-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ego-search, .gemini/skills/ego-search, .github/skills/ego-search and .opencode/skills/ego-search in your project.
Going by SKILL.md and its folder, Ego Browser Search needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: macOS with the ego browser runtime and its ego-browser command, or the WebBridge browser extension; Professional search mode switched on by you; Python 3 to run ego_search.py.
SKILL.md names 4 domains. In commands or code: zhihu.com and cn.bing.com; the agent is likely to contact these when it follows the instructions. As links in the text: lite.ego.app and kimi.com. This is read from the text; nothing was executed.
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Ego Browser Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.5k 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.
Skills that share tags, products or a category with Ego Browser Search: Bright Data MCP (brightdata/skills, 264 stars), Web Access via Browser CDP (eze-is/web-access, 9.1k stars), Reddit JSON Fetcher (ykdojo/claude-code-tips, 10k stars) and Scrapingbee CLI (ScrapingBee/scrapingbee-cli, 108 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
taxueseek (a GitHub user) maintains it in taxueseek/argo, which has 188 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 6, 2026.
Source: taxueseek/argo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.