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Agent Skill · 研究检索

oo(哦)

oo 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

oo 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 31,551。

总安装 2,681周安装 114GitHub Stars 公开资料未说明下载 939核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:oo(哦)
来源仓库:https://github.com/openonion/oo
安装命令:
openclaw skills install oo
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install oo

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

oo 用于在 OpenClaw 中查找、检索和筛选相关信息。适用于需要根据关键词或任务场景定位信息的场景。可结合来源仓库和 README 核验具体用法。安装前需确认权限范围、维护状态及是否触发联网操作。建议核实是否会执行命令或访问敏感数据。oo 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install oo;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

oo 怎么安装?

在终端执行 openclaw skills install oo。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

oo 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

oo 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install oo 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

oo 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

oo 用的人多吗?

公开数据是累计安装 2,681 次,近一周安装 114 次,下载 939 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

oo 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
oo

哦 · 本页

2,681—执行命令MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
oo
description
Use when user mentions a ConnectOnion agent address (0x...), asks to connect/delegate to a remote agent, or uses /oo command. Also triggers when user wants to set up ConnectOnion environment for agent networking.
argument-hint
<0xAddress> <task description>

ConnectOnion Agent Networking

Connect to remote ConnectOnion agents, delegate tasks, and handle multi-turn collaboration.

Environment Setup

Before any interaction, verify the environment is ready. Run these checks sequentially — stop on first failure:

1. Check connectonion is installed:

python -c "import connectonion; print(connectonion.__version__)"

If ImportError: run pip install connectonion, then re-check.

2. Check agent identity exists:

ls .co/keys/agent.key 2>/dev/null || ls ~/.co/keys/agent.key 2>/dev/null

If neither exists: run co init to generate identity.

3. Verify identity is usable:

python -c "
from connectonion import address
from pathlib import Path
a = address.load(Path('.co')) or address.load(Path.home() / '.co')
print(a['address'])
"

If fails: report the error and stop. The user needs to fix their .co/ directory.

Note: import connectonion prints [env] ... lines to stdout. For all environment checks, parse only the last line of stdout output. Ignore everything else.

Skip environment checks after the first successful run in a session.

Connecting to a Remote Agent

Parsing User Intent

Extract from the user's message:

  • Target address: match regex 0x[0-9a-fA-F]{64} (66 chars total)
  • Task description: everything else

For /oo slash command: /oo <address> <task description>

Connection Strategy: Direct-First with Relay Fallback

The default connect() library has a known issue: the relay API may not return an online field, causing direct endpoint resolution to always fail and falling back to relay — which itself may be unreliable. To work around this, the skill uses a smart connection script that:

  1. Queries the relay API for the agent's registered endpoints
  2. Tries each endpoint directly (verifying via /info)
  3. Falls back to relay only if all direct endpoints fail

One-shot Task

Generate and execute this Python script (fill in {address} and {task}):

import sys, json, time, uuid, asyncio
import httpx, websockets
from connectonion import address
from pathlib import Path

TARGET = "{address}"
TASK = "{task}"
TIMEOUT = 60
RELAY_URL = "wss://oo.openonion.ai"

keys = address.load(Path(".co")) or address.load(Path.home() / ".co")

def _sort_endpoints(endpoints):
    def priority(url):
        if "localhost" in url or "127.0.0.1" in url:
            return 0
        if any(x in url for x in ("192.168.", "10.", "172.16.", "172.17.", "172.18.")):
            return 1
        return 2
    return sorted(endpoints, key=priority)

def discover_direct_ws(target, relay_url):
    """Query relay API for endpoints and find a working direct WebSocket."""
    https_relay = relay_url.replace("wss://", "https://").replace("ws://", "http://").rstrip("/")
    try:
        resp = httpx.get(f"{https_relay}/api/relay/agents/{target}", timeout=5)
        if resp.status_code != 200:
            return None
        info = resp.json()
    except Exception:
        return None

    endpoints = info.get("endpoints", [])
    if not endpoints:
        return None

    http_endpoints = [ep for ep in _sort_endpoints(endpoints)
                      if ep.startswith("http://") or ep.startswith("https://")]

    for http_url in http_endpoints:
        try:
            r = httpx.get(f"{http_url}/info", timeout=3, proxy=None)
            if r.status_code == 200 and r.json().get("address") == target:
                ws_url = http_url.replace("https://", "wss://").replace("http://", "ws://")
                if not ws_url.endswith("/ws"):
                    ws_url = ws_url.rstrip("/") + "/ws"
                return ws_url
        except Exception:
            continue
    return None

async def direct_connect(ws_url, target, keys, task, timeout):
    """Connect directly to agent WebSocket, send task, return result."""
    async with websockets.connect(ws_url, proxy=None) as ws:
        # Signed CONNECT
        ts = int(time.time())
        payload = {"to": target, "timestamp": ts}
        canonical = json.dumps(payload, sort_keys=True, separators=(",", ":"))
        signature = address.sign(keys, canonical.encode())
        connect_msg = {
            "type": "CONNECT", "timestamp": ts, "to": target,
            "payload": payload, "from": keys["address"], "signature": signature.hex()
        }
        await ws.send(json.dumps(connect_msg))

        # Wait for CONNECTED
        raw = await asyncio.wait_for(ws.recv(), timeout=10)
        event = json.loads(raw)
        if event.get("type") == "ERROR":
            raise ConnectionError(f"Auth error: {event.get('message', event.get('error'))}")
        if event.get("type") != "CONNECTED":
            raise ConnectionError(f"Unexpected: {event.get('type')}")

        # Signed INPUT
        ts2 = int(time.time())
        input_id = str(uuid.uuid4())
        input_payload = {"prompt": task, "timestamp": ts2}
        input_canonical = json.dumps(input_payload, sort_keys=True, separators=(",", ":"))
        input_sig = address.sign(keys, input_canonical.encode())
        input_msg = {
            "type": "INPUT", "input_id": input_id, "prompt": task, "timestamp": ts2,
            "payload": input_payload, "from": keys["address"], "signature": input_sig.hex()
        }
        await ws.send(json.dumps(input_msg))

        # Stream until OUTPUT
        while True:
            msg = await asyncio.wait_for(ws.recv(), timeout=timeout)
            ev = json.loads(msg)
            t = ev.get("type")
            if t == "OUTPUT":
                return ev.get("result", ""), True
            elif t == "ask_user":
                return ev.get("text", ""), False
            elif t == "ERROR":
                raise ConnectionError(f"Agent error: {ev.get('message', ev.get('error'))}")

# --- Main ---
result_text, done = None, None

# Step 1: Try direct connection
ws_url = discover_direct_ws(TARGET, RELAY_URL)
if ws_url:
    try:
        result_text, done = asyncio.run(direct_connect(ws_url, TARGET, keys, TASK, TIMEOUT))
        print(f"CO_METHOD: direct", flush=True)
    except Exception as e:
        print(f"CO_DIRECT_FAIL: {e}", flush=True)

# Step 2: Fallback to relay
if result_text is None:
    try:
        from connectonion import connect
        agent = connect(TARGET, keys=keys)
        response = agent.input(TASK, timeout=TIMEOUT)
        result_text, done = response.text, response.done
        print(f"CO_METHOD: relay", flush=True)
    except Exception as e:
        print(f"CO_RELAY_FAIL: {e}", flush=True)
        sys.exit(1)

print(f"CO_RESPONSE: {json.dumps(result_text)}", flush=True)
print(f"CO_DONE: {done}", flush=True)

Execute via your shell tool. Parse stdout — only lines starting with CO_ matter, ignore all others. The CO_RESPONSE value is JSON-encoded (to handle multi-line responses). Decode it before presenting to the user.

  • CO_DONE: True → return CO_RESPONSE content to the user. Done.
  • CO_DONE: False → the remote agent is asking a follow-up question. See Multi-turn Task below.
  • CO_METHOD: direct → connected directly (fastest path).
  • CO_METHOD: relay → connected via relay fallback.
  • CO_DIRECT_FAIL: ... → direct failed, trying relay next.
  • CO_RELAY_FAIL: ... → both methods failed. Report error to user.

For long-running tasks, increase timeout to 300.

Multi-turn Task

Multi-turn requires maintaining session state. Use separate one-shot calls per turn since stdin interaction is unreliable in agent environments. Each turn is a new connection but passes context through the conversation.

For the first turn, use the one-shot script above. For follow-up turns, include conversation context in the prompt (e.g., prepend prior exchanges).

Response Handling

After each round, parse stdout — only CO_ prefixed lines matter, ignore all others:

  • CO_DONE: True → return CO_RESPONSE content to the user. Done.
  • CO_DONE: False → the remote agent asked a follow-up question:

- If you can answer from context (file contents, prior conversation, your own knowledge) → answer automatically. Do not bother the user. - If you need the user's input → show CO_RESPONSE to the user, wait for their reply, then send another round. - Loop until CO_DONE: True or 10 rounds.

Error Handling

If the script fails, check stderr for these patterns:

Error in stderrCauseAction
ImportError: No module named 'connectonion'Not installedRun pip install connectonion
address.load() returns NoneNo identityRun co init
TimeoutErrorRemote agent unreachable or slowVerify address, check network/proxy, increase timeout
ConnectionRefused or relay lookup failAgent offlineConfirm remote agent is running with host()
CO_DIRECT_FAIL + CO_RELAY_FAILBoth paths failedAgent likely offline — check with operator
Trust/permission errorNot authorizedTell user to contact the remote agent admin for access
InsufficientCreditsErrorNo credits for co/ modelsRun co status to check balance
Script hangs (no output for >90s)Remote agent requesting onboard (invite code/payment)Kill script, tell user the remote agent requires onboarding

平台分布

OpenClaw

96.7%
按下载量换算908

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install oo 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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