Fetch Agents
/install fetch-agents
Fetch Agents
Send queries to Fetch.ai Agentverse agents and return the agent's reply in natural language.
CRITICAL RULES — READ FIRST
- NEVER show the user a bash command, a script path, or anything that looks like
python3 ...orbash .... Those are for YOU to run internally. The user is chatting in Telegram/CLI and wants plain language. - If the user asks "how do I use X" or "how does this work" — DO NOT respond with commands. Respond with plain-English example prompts, like: "Just ask me things like 'get trading signals for TSLA' or 'translate hello to French' and I'll take care of the rest."
- When the user makes an actual request (get signals, translate, etc.), run the script yourself and reply with the agent's answer. Format it nicely. Do not tell them to run anything.
- The only time you reveal paths or commands is if the user explicitly asks for debug/diagnostic info.
How to answer common user questions
- "How do I use this?" / "What can this do?" → Explain in plain English: it calls Fetch.ai Agentverse agents for real-time data, translations, stats, stock signals, image generation, etc. Give 3-4 example prompts the user can try (in natural language, NOT bash).
- "What agents are available?" / "Show me the catalog" → Run
catalog.pyand format the result as a friendly list. - "Find a [topic] agent" → Run
search.pyand return the top matches in plain text. - Any actual task (signals, translation, stats, etc.) → Run
fire.sh, tell the user to hold on ~40 seconds, then runresult.shand reply with the agent's answer in your own words.
Natural-language prompts the user might send
- "get me trading signals for TSLA" → call
signalsagent - "what does ASI1-Mini think about quantum computing?" → call
asiagent - "translate 'hello world' to Japanese" → call
translateagent - "compute stats for 1, 2, 3, 4, 5" → call
statsagent - "stock analysis on AAPL" → call
stocksagent - "search the agentverse for weather agents" → run marketplace search
- "latest news on Fetch.ai" → call
search(Tavily web search) agent - "get github info for fetchai" → call
githubagent - "generate an image of a cyberpunk cat" → call
imageagent - "call the Crypto Fear & Greed Agent for the current index" → agent by name, auto-searched
Agent Shortcuts
| Key | Agent | Purpose |
|---|---|---|
stats |
Average Agent | Mean, median, mode, variance, std dev |
signals |
Asset Signal | BUY/SELL/WAIT trading signals |
stocks |
Technical Analysis | Stock SMA/EMA/WMA indicators |
image |
DALL-E 3 Generator | Image generation from text |
asi |
ASI1-Mini | General-purpose AI chat |
translate |
OpenAI Translator | Text translation |
github |
Github Organisation | GitHub org metadata |
search |
Tavily Search | Web search (NOT marketplace search) |
Internal Execution (for you, the agent, not the user)
The following are the commands YOU run with the exec tool. Never show these to the user.
Show the curated catalog
Runs in \x3C5 seconds. Use for "what agents are available?" type questions.
python3 {baseDir}/scripts/catalog.py
Search the Agentverse marketplace
Runs in \x3C5 seconds. Use when the user wants to find agents by topic.
python3 {baseDir}/scripts/search.py "query" -n 10
Call an agent (two-step, ~40 seconds total)
Calling an Agentverse agent takes 30-60 seconds. Use the two-step pattern:
Step 1 — Fire (returns instantly):
bash {baseDir}/scripts/fire.sh \x3Cshortcut-or-address-or-name> "user's query"
Accepts: a shortcut key from the table above, a full agent1q... address, or an agent name (auto-searched).
Step 2 — Tell the user something like: "Calling the agent, this takes about 30-60 seconds..."
Step 3 — After 30-60 seconds, read the result:
bash {baseDir}/scripts/result.sh
Then reply to the user with the agent's answer, rewritten in your own words / formatted nicely. Never show the raw command.
Rules
- Resolve
{baseDir}to the absolute path of this SKILL.md's parent directory. - Single absolute-path command per exec call. No
cd, no&&. - The user never sees the commands or paths. Just give them the agent's answer.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install fetch-agents - 安装完成后,直接呼叫该 Skill 的名称或使用
/fetch-agents触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Fetch Agents 是什么?
Call Fetch.ai Agentverse agents by address. Search the Agentverse marketplace, browse a curated catalog of top agents (Tavily Search, ASI1-Mini, DALL-E 3, Te... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 90 次。
如何安装 Fetch Agents?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install fetch-agents」即可一键安装,无需额外配置。
Fetch Agents 是免费的吗?
是的,Fetch Agents 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Fetch Agents 支持哪些平台?
Fetch Agents 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(darwin, linux)。
谁开发了 Fetch Agents?
由 Steve-Dusty(@steve-dusty)开发并维护,当前版本 v0.3.0。