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 YangsonHung/awesome-agent-skills --skill tweetclaw-twitter-automation-cngit clone --depth 1 https://github.com/YangsonHung/awesome-agent-skillsWrote 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/yangsonhung/awesome-agent-skills/tweetclaw-twitter-automation-cn)<a href="https://agentmods.dev/skills/yangsonhung/awesome-agent-skills/tweetclaw-twitter-automation-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/tweetclaw-twitter-automation-cn/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/yangsonhung/awesome-agent-skills/tweetclaw-twitter-automation-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/tweetclaw-twitter-automation-cn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00064 | $0.00926 |
| Opus 5 | $0.00032 | $0.00463 |
| Sonnet 5 | $0.00013 | $0.00185 |
| Haiku 4.5 | $0.00006 | $0.00093 |
Grade A, and why
tweetclaw-twitter-automation-cn 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 12d 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.
What it actually says
TweetClaw Twitter 自动化
当用户希望 Agent 通过 Xquik 或 TweetClaw OpenClaw 插件处理 X/Twitter 工作流时,使用此 Skill。
使用场景
用户提出以下需求时使用:
- 抓取推文、长帖、回复、引用、提及、点赞或媒体
- 搜索推文或推文回复
- 查询用户、粉丝、关注列表或认证粉丝
- 在用户批准后发推、回复推文或上传媒体
- 在账号授权后读取或发送私信
- 创建监控、Webhook 或抽奖
- 判断哪个 TweetClaw 或 Xquik 端点适合当前任务
不要使用
不要将此 Skill 用于:
- 垃圾信息、骚扰、欺骗性互动、冒充身份或规避平台规则
- 大量未请求私信、批量关注、批量点赞、批量转发或刷互动
- TweetClaw 不提供的 X 广告、分析看板或定时发布功能
- 只配置了只读访问时执行写入操作
- 在没有明确授权时访问私有或账号级数据
- 要求用户在聊天中粘贴 API key、签名密钥、Cookie 或令牌
使用说明
- 先把用户需求归类为一个工作流:读取、抽取、写入、媒体、私信、监控、Webhook、抽奖或能力发现。
- 当安装、配置、限制或 API 细节会影响结果时,先查看当前文档:
- 在 OpenClaw 中安装时,优先使用明确的 npm 选择器:
openclaw plugins install npm:@xquik/tweetclaw
- 安装或更新后,先验证运行时再执行真实任务:
openclaw plugins inspect tweetclaw --runtime --json
openclaw skills info tweetclaw
- 将凭证保存在 Xquik dashboard、OpenClaw 插件配置或环境变量支持的密钥存储中。不要打印或回显凭证值。
- 使用 TweetClaw 能力发现或 Xquik 文档选择最小可行端点和请求数量。
- 在任何可见、会改变状态、涉及私有数据、付费、周期性、抽取、监控、Webhook、抽奖或账号级操作前,说明目标、账号、动作、限制、数据处理方式,以及可获得的使用影响。等待用户明确确认。
- 发推或回复前,展示最终文本和媒体列表。不要添加用户没有要求的链接、提及、话题标签或声明。
- 创建监控或 Webhook 时,说明目标、事件类型、投递方式,以及用户如何停止该资源。
- 输出结果时保持简洁,包含 ID、URL、数量和任何部分失败。
常见工作流
搜索推文
当用户需要 Agent 搜索 X/Twitter 内容时使用 TweetClaw。保持查询范围明确,设置结果数量,并总结返回的推文 ID、URL、作者、时间和匹配文本。
导出粉丝
确认账号或主页、请求数量,以及用户需要原始行还是摘要。私有账号数据必须限制在用户授权范围内。
发布推文
展示准确的推文文本和附件媒体。发送前先请求确认。操作成功后返回创建的推文 URL。
监控动态
只有在用户确认账号、关键词或事件目标后才创建监控。说明将监控什么内容,以及结果如何投递。
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.
- 12d ago First seen · 75 lines · 64 tokens per session scan A d8f0d034d516
tweetclaw-twitter-automation-cn is a skill published in the GitHub repository YangsonHung/awesome-agent-skills (18 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 926 once invoked, about $0.0003 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.
Other skills, from other repositories
vastai
Vast.ai CLI to manage GPU instances, volumes, serverless endpoints, and billing.
vastai-sdk
Vast.ai Python SDK — high-level API for GPU instances, volumes, serverless endpoints, and billing.
gdpr-compliance-checker
Autonomous GDPR compliance auditor that scans a codebase to identify PII collection, storage, and sharing, then produces an article-by-article gap analysis, a pre-filled Data Processing Agreement (DPA), and a ROPA (Record of Processing Activities) starter kit — all exported as downloadable files (.docx recommended).…
pii-detector
Proactive PII add-on — augments the main response with PII guidance. Auto-trigger on any form, schema, migration, model, API route, GraphQL resolver, auth flow, or data design discussion. Also fires on: middleware, webhooks, workers, seed/fixture/factory files, delete/export/purge/anonymize functions, cron jobs, HTTP…
modellix
Integrate Modellix's unified API for AI image, video, and audio workflows. Use this skill whenever the user wants to generate or edit images, create or transform videos, synthesize speech, transcribe audio, clone a voice, do virtual try-on, or call any Modellix model API. Also trigger when the user mentions Modellix…
app-release
Automates the release process for Skill Lake app, including version bumping, building, packaging, and publishing to GitHub and Homebrew.