全面的 Telegram 开发指南,涵盖 Bot 开发、Mini Apps (Web Apps)、客户端开发的完整技术栈。
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontelegram-devExecute the skills CLI command in your project's root directory to begin installation:
Fetches telegram-dev from 2025emma/vibe-coding-cn and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate telegram-dev. Access via /telegram-dev in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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全面的 Telegram 开发指南,涵盖 Bot 开发、Mini Apps (Web Apps)、客户端开发的完整技术栈。
当需要以下帮助时使用此技能:
Bot API - 创建机器人程序
Mini Apps API (Web Apps) - 创建 Web 应用
Telegram API & TDLib - 创建客户端
API 端点:
https://api.telegram.org/bot<TOKEN>/METHOD_NAME
获取 Bot Token:
/newbot第一个 Bot (Python):
import requests
BOT_TOKEN = "your_bot_token_here"
API_URL = f"https://api.telegram.org/bot{BOT_TOKEN}"
# 发送消息
def send_message(chat_id, text):
url = f"{API_URL}/sendMessage"
data = {"chat_id": chat_id, "text": text}
return requests.post(url, json=data)
# 获取更新(长轮询)
def get_updates(offset=None):
url = f"{API_URL}/getUpdates"
params = {"offset": offset, "timeout": 30}
return requests.get(url, params=params).json()
# 主循环
offset = None
while True:
updates = get_updates(offset)
for update in updates.get("result", []):
chat_id = update["message"]["chat"]["id"]
text = update["message"]["text"]
# 回复消息
send_message(chat_id, f"你说了:{text}")
offset = update["update_id"] + 1
更新管理:
getUpdates - 长轮询获取更新setWebhook - 设置 WebhookdeleteWebhook - 删除 WebhookgetWebhookInfo - 查询 Webhook 状态消息操作:
sendMessage - 发送文本消息sendPhoto / sendVideo / sendDocument - 发送媒体sendAudio / sendVoice - 发送音频sendLocation / sendVenue - 发送位置editMessageText - 编辑消息deleteMessage - 删除消息forwardMessage / copyMessage - 转发/复制消息交互元素:
sendPoll - 发送投票(最多 12 个选项)answerCallbackQuery - 响应回调查询文件操作:
getFile - 获取文件信息downloadFile - 下载文件支付功能:
sendInvoice - 发送发票answerPreCheckoutQuery - 处理支付设置 Webhook:
import requests
BOT_TOKEN = "your_token"
WEBHOOK_URL = "https://yourdomain.com/webhook"
requests.post(
f"https://api.telegram.org/bot{BOT_TOKEN}/setWebhook",
json={"url": WEBHOOK_URL}
)
Flask Webhook 示例:
from flask import Flask, request
import requests
app = Flask(__name__)
BOT_TOKEN = "your_token"
@app.route('/webhook', methods=['POST'])
def webhook():
update = request.get_json()
chat_id = update["message"]["chat"]["id"]
text = update["message"]["text"]
# 发送回复
requests.post(
f"https://api.telegram.org/bot{BOT_TOKEN}/sendMessage",
json={"chat_id": chat_id, "text": f"收到: {text}"}
)
return "OK"
if __name__ == '__main__':
app.run(port=5000)
Webhook 要求:
创建内联键盘:
def send_inline_keyboard(chat_id):
keyboard = {
"inline_keyboard": [
[
{"text": "按钮 1", "callback_data": "btn1"},
{"text": "按钮 2", "callback_data": "btn2"}
],
[
{"text": "打开链接", "url": "https://example.com"}
]
]
}
requests.post(
f"{API_URL}/sendMessage",
json={
"chat_id": chat_id,
"text": "选择一个选项:",
"reply_markup": keyboard
}
)
处理回调:
def handle_callback_query(callback_query):
query_id = callback_query["id"]
data = callback_query["data"]
chat_id = callback_query["message"]["chat"]["id"]
# 响应回调
requests.post(
f"{API_URL}/answerCallbackQuery",
json={"callback_query_id": query_id, "text": f"你点击了 {data}"}
)
# 更新消息
requests.post(
f"{API_URL}/editMessageText",
json={
"chat_id": chat_id,
"message_id": callback_query["message"]["message_id"],
"text": f"你选择了:{data}"
}
)
配置内联模式:
与 @BotFather 对话,发送 /setinline
处理内联查询:
def handle_inline_query(inline_query):
query_id = inline_query["id"]
query_text = inline_query["query"]
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
telegram-dev has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for telegram-dev matched our evaluation — installs cleanly and behaves as described in the markdown.
telegram-dev reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added telegram-dev from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: telegram-dev is focused, and the summary matches what you get after install.
Useful defaults in telegram-dev — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: telegram-dev is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend telegram-dev for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for telegram-dev matched our evaluation — installs cleanly and behaves as described in the markdown.
Registry listing for telegram-dev matched our evaluation — installs cleanly and behaves as described in the markdown.
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