Overview
- Skill Key
- bangyizhang/tg-stickers
- Author
- bangyizhang
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/bangyizhang/tg-stickers
- Latest Commit SHA
- c99e96aa1b578b647db6dd461b19fa14339eaf35
Collect and send Telegram stickers smartly. Auto-import packs, tag by emotion, select contextually, and respect frequency limits (2-5 messages).
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 tg-stickers 技能。 若已安装,则直接安装 tg-stickers 技能。
# Telegram Stickers Skill Intelligently manage and send Telegram stickers with emotional awareness. ## Core Value **OpenClaw natively supports sending stickers** (`message` tool), but this skill adds: - ✅ **Collection management** - Import entire sticker packs at once - ✅ **Emotion tagging** - 100+ emoji → emotion mappings - ✅ **Smart selection** - Context-based + randomization (avoid repetition) - ✅ **Frequency control** - 2-5 messages between stickers - ✅ **Usage analytics** - Track which stickers work best ## Quick Start ### 1. Import Sticker Packs ```bash ./import-sticker-pack.sh <pack_short_name_or_id> ``` ### 2. Auto-Tag by Emotion ```bash ./auto-tag-stickers.sh ``` ### 3. Send Stickers (in agent code) ```javascript // ✅ Use OpenClaw's message tool directly message(action='sticker', target='<chat_id>', stickerId=['<file_id>']) // No bash script needed - OpenClaw handles sending natively ``` ### 4. Smart Selection ```bash ./random-sticker.sh "goodnight" # Returns random sticker tagged "goodnight" ``` ## Tools | Script | Purpose | Usage | |--------|---------|-------| | `import-sticker-pack.sh` | Bulk import Telegram sticker pack | `./import-sticker-pack.sh pa_XXX...` | | `auto-tag-stickers.sh` | Tag stickers by emoji → emotion | `./auto-tag-stickers.sh` | | `random-sticker.sh` | Select random sticker by tag | `./random-sticker.sh "happy"` | | `check-collection.sh` | View collection stats | `./check-collection.sh` | ## Agent Integration ```markdown ## Sticker Usage When to send: - Goodnight/morning greetings (always use sticker over text) - Celebrating success/milestones - Humorous moments - Emotional responses (joy, sympathy, encouragement) How to send: 1. Use random-sticker.sh to pick appropriate sticker by emotion 2. Call message(action=sticker, ...) directly 3. (Optional) Update stickers.json manually to track usage Frequency: 2-5 messages between stickers (track in agent logic) ``` ## Emotion Tags Auto-tagging maps 100+ emoji to emot...
# tg-stickers Smart Telegram sticker management for OpenClaw agents. ## What This Does **OpenClaw natively sends stickers**, but this skill adds intelligence: - 📦 **Bulk import** - Add entire sticker packs at once - 🏷️ **Auto-tagging** - Map 100+ emoji to emotions (happy, sad, goodnight, etc.) - 🎲 **Smart selection** - Context-based random picks (avoid repetition) - 📊 **Analytics** - Track usage patterns ## Quick Start ```bash # 1. Import a sticker pack ./import-sticker-pack.sh pa_YK0WQxd6HTw52j6bazKo_by_SigStick21Bot # 2. Auto-tag all stickers ./auto-tag-stickers.sh # 3. Select a sticker (returns file_id) ./random-sticker.sh "goodnight" # 4. Send via OpenClaw (in agent code) message(action=sticker, target=<chat_id>, stickerId=[<file_id>]) ``` ## Tools | Script | Purpose | |--------|---------| | `import-sticker-pack.sh` | Import entire Telegram sticker pack | | `auto-tag-stickers.sh` | Tag stickers by emoji → emotion mapping | | `random-sticker.sh` | Pick random sticker by tag | | `check-collection.sh` | View collection stats | ## Files - `stickers.json` - Your collection + usage data - `stickers.json.example` - Empty template - `SKILL.md` - Full documentation ## Usage Philosophy **Use stickers like humans do:** - Greetings (goodnight/morning) → always prefer sticker over text - Celebrations, humor, empathy → great use cases - Technical answers, reports → skip stickers - Frequency: ~1 per 2-5 messages (track yourself in agent logic) ## Integration Read `SKILL.md` for full integration guide with OpenClaw agents. ## License MIT
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