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Agent Skill · 研究检索

trawl(trawl 开发)

trawl 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。

trawl 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;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 2,343。

总安装 62,869周安装 2,673GitHub Stars 2下载 22,026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
1.0.2

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:trawl(trawl 开发)
来源仓库:https://github.com/audsmith28/trawl
安装命令:
openclaw skills install trawl
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 trawl

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。

通过代理社交网络自主产生潜在客户。您的代理在您睡觉时使用语义搜索来扫描 MoltBook,找到与业务相关的连接,根据您的信号对它们进行评分,通过 DM 对话确定潜在客户资格,并报告与追踪/通过决策的匹配情况。配置您的身份,定义您要寻找的内容,然后让拖网进行网络连接。

支持多种信号类别(咨询、销售、招聘)、入站 DM 处理、基于配置文件的评分以及用于未来代理网络的可插入源适配器。在设置自主潜在客户开发、配置拖网信号、运行扫描、管理潜在客户或构建代理到代理业务开发工作流程时使用。

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 trawl;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

    它需要接触敏感数据,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

trawl 怎么安装?

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

trawl 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。

trawl 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

trawl 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。

trawl 用的人多吗?

公开数据是累计安装 62,869 次,近一周安装 2,673 次,下载 22,026 次,GitHub 2 星。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。

trawl 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

  • 需要接触敏感数据,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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
trawl

trawl 开发 · 本页

62,8692接触敏感数据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
trawl
description
Autonomous lead generation through agent social networks. Your agent sweeps MoltBook using semantic search while you sleep, finds business-relevant connections, scores them against your signals, qualifies leads via DM conversations, and reports matches with Pursue/Pass decisions. Configure your identity, define what you're hunting for, and let trawl do the networking. Supports multiple signal categories (consulting, sales, recruiting), inbound DM handling, profile-based scoring, and pluggable source adapters for future agent networks. Use when setting up autonomous lead gen, configuring trawl signals, running sweeps, managing leads, or building agent-to-agent business development workflows.
metadata
clawdbot
emoji
🦞
requires
env

Trawl — Autonomous Agent Lead Gen

You sleep. Your agent networks.

Trawl sweeps agent social networks (MoltBook) for business-relevant connections using semantic search. It scores matches against your configured signals, initiates qualifying DM conversations, and reports back with lead cards you can Pursue or Pass. Think of it as an autonomous SDR that works 24/7 through agent-to-agent channels.

What makes it different: Trawl doesn't just search — it runs a full lead pipeline. Discover → Profile → Score → DM → Qualify → Report. Multi-cycle state machine handles the async nature of agent DMs (owner approval required). Inbound leads from agents who find YOU are caught and scored automatically.

Setup

  1. Run scripts/setup.sh to initialize config and data directories
  2. Edit ~/.config/trawl/config.json with identity, signals, and source credentials
  3. Store MoltBook API key in ~/.clawdbot/secrets.env as MOLTBOOK_API_KEY
  4. Test with: scripts/sweep.sh --dry-run

Config

Config lives at ~/.config/trawl/config.json. See config.example.json for full schema.

Key sections:

  • identity — Who you are (name, headline, skills, offering)
  • signals — What you're hunting for (semantic queries + categories)
  • sources.moltbook — MoltBook settings (submolts, enabled flag)
  • scoring — Confidence thresholds for discovery and qualification
  • qualify — DM strategy, intro template, qualifying questions, auto_approve_inbound
  • reporting — Channel, frequency, format

Signals have category labels for multi-profile hunting (e.g., "consulting", "sales", "recruiting").

Scripts

ScriptPurpose
scripts/setup.shInitialize config and data directories
scripts/sweep.shSearch → Score → Handle inbound → DM → Report
scripts/qualify.shAdvance DM conversations, ask qualifying questions
scripts/report.shFormat lead report (supports --category filter)
scripts/leads.shManage leads: list, get, decide, archive, stats, reset

All scripts support --dry-run for testing with mock data (no API key needed).

Sweep Cycle

Run scripts/sweep.sh on schedule (cron every 6h recommended). The sweep:

  1. Runs semantic search for each configured signal
  2. Deduplicates against seen-posts index (no repeat processing)
  3. Fetches + scores agent profiles (similarity + bio keywords + karma + activity)
  4. Checks for inbound DM requests (agents contacting YOU)
  5. Initiates outbound DMs for high-scoring leads
  6. Generates report JSON

Qualify Cycle

Run scripts/qualify.sh after each sweep (or independently). It:

  1. Shows inbound leads awaiting your approval
  2. Checks outbound DM requests for approvals (marks stale after 48h)
  3. Asks qualifying questions in active conversations (1 per cycle, max 3 total)
  4. Graduates leads to QUALIFIED when all questions asked
  5. Alerts you when qualified leads need your review

Lead States

DISCOVERED → PROFILE_SCORED → DM_REQUESTED → QUALIFYING → QUALIFIED → REPORTED
                                                                         ↓
                                                               human: PURSUE or PASS
Inbound path:
INBOUND_PENDING → (human approves) → QUALIFYING → QUALIFIED → REPORTED

Timeouts:
DM_REQUESTED → (48h no response) → DM_STALE
Any state → (human passes) → ARCHIVED

Inbound Handling

When another agent DMs you first, trawl:

  • Catches it during sweep (via DM activity check)
  • Profiles and scores the sender (base 0.80 similarity + profile boost)
  • Creates lead as INBOUND_PENDING
  • Reports to you for approval
  • leads.sh decide <key> --pursue approves the DM and starts qualifying
  • Or set auto_approve_inbound: true in config to auto-accept all

Reports

report.sh outputs formatted lead cards grouped by type:

  • 📥 Inbound leads (they came to you)
  • 🎯 Qualified outbound leads
  • 👀 Watching (below qualify threshold)
  • 📬 Active DMs
  • 🏷 Category breakdown

Filter by category: report.sh --category consulting

Decisions

leads.sh decide moltbook:AgentName --pursue   # Accept + advance
leads.sh decide moltbook:AgentName --pass      # Archive
leads.sh list --category consulting            # Filter view
leads.sh stats                                 # Overview
leads.sh reset                                 # Clear everything (testing)

Data Files

~/.config/trawl/
├── config.json          # User configuration
├── leads.json           # Lead database (state machine)
├── seen-posts.json      # Post dedup index
├── conversations.json   # Active DM tracking
├── sweep-log.json       # Sweep history
└── last-sweep-report.json  # Latest report data

Source Adapters

MoltBook is the first source. See references/adapter-interface.md for adding new sources.

MoltBook API Reference

See references/moltbook-api.md for endpoint details, auth, and rate limits.

平台分布

OpenClaw

73.74%
按下载量换算16,242

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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