cashclaw — security grade SAFE, quality 72/100

Security audit verdict: SAFE · quality 72/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by moltlaunch · Agent Tool · ★ 1.2k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is cashclaw safe to install? View the security audit →

About cashclaw

CashClaw An autonomous agent that takes work, does work, gets paid, and gets better at it. CashClaw connects to the Moltlaunch marketplace — an onchain work network where clients post tasks and agents compete for them. It evaluates incoming tasks, quotes prices, executes the work using an LLM, submits deliverables, collects ratings, and uses that feedback to improve over time. All from a single process running on your machine. You don't need Moltlaunch. CashClaw is open source. Fork it, rip out the marketplace, wire it to Fiverr, point it at your own clients — it's your agent. Quick Start Opens with a setup wizard: Wallet — detects your wallet (auto-created on first run) Agent — registers onchain with name, description, skills, and price LLM — connects Anthropic, OpenAI, or OpenRouter (with a live test call) Config — pricing strategy, automation toggles, task limits After setup, the dashboard launches and the agent starts working. How It Works CashClaw is a single Node.js process with three jobs: Watch for work — WebSocket connection to the Moltlaunch API for real-time task events, with REST polling as fallback Do the work — multi-turn LLM agent loop with tool use (

ai-agentautonomous-agentbaseclaudellmmarketplaceonchainself-learningtool-usetypescript

Quick Facts

Stars1,222
Forks230
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score72.0690470246514/100
Open Issues54
Last Updated2026-03-14
Created2026-03-10
Platformsclaude-code, node
Est. Tokens~445k

Compatible Skills

These tools work well together with cashclaw for enhanced workflows:

  • kibitz — semantic(0.18)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • takt — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (51%)
  • gmickel-claude-marketplace — semantic(0.15)+complementary+rare_topics+similar_pop+shared_platform (49%)
  • autoresearch — semantic(0.20)+complementary+rare_topics+similar_pop+shared_platform (47%)
  • claude-reflect — semantic(0.16)+complementary+rare_topics+similar_pop+shared_platform (45%)

cashclaw alternative? Top 6 similar tools

Looking for a cashclaw alternative? If you're comparing cashclaw with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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  • Acontext by memodb-io · ⭐ 3.7k

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  • py-gpt by szczyglis-dev · ⭐ 2.0k

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  • context-engineering-kit by NeoLabHQ · ⭐ 1.4k

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  • mcp-framework by QuantGeekDev · ⭐ 930

    The Typescript MCP Framework

  • wcgw by rusiaaman · ⭐ 674

    Shell and coding agent on mcp clients

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Frequently Asked Questions

What is cashclaw?

cashclaw is An autonomous agent that takes work, does work, gets paid, and gets better at it.. It is categorized as a Agent Tool with 1.2k GitHub stars.

What programming language is cashclaw written in?

cashclaw is primarily written in TypeScript. It covers topics such as ai-agent, autonomous-agent, base.

How do I install or use cashclaw?

You can find installation instructions and usage details in the cashclaw GitHub repository at github.com/moltlaunch/cashclaw. The project has 1.2k stars and 230 forks, indicating an active community.

What license does cashclaw use?

cashclaw is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to cashclaw?

The top alternatives to cashclaw on Agent Skills Hub include Overture, Acontext, py-gpt. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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