AI Agents
TradingAgents-astock
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear deb…
★ 3.6k starsApache-2.0
View guide →Open-source AI job search agent and job finder: scan job boards, score each job 1-5 against your CV before you apply, tailor an ATS-friendly resume and cover…
career-ops is an open-source ai agents project by career-ops-hq (career-ops-hq/career-ops on GitHub). It has 73,398 GitHub stars and 13,797 forks, is released under the MIT license, and was last updated on GitHub on 3 October 2026.
Research, coding, browsing, or ops — agents work best with a clear goal.
From no-code builders to code-first SDKs, match complexity to the task.
Web search, code execution, and APIs are what make agents useful.
Watch the trace, approve consequential actions, iterate.
Scriptable from the terminal, so it drops straight into existing workflows.
Traces show exactly what the agent did and why.
Approval gates for actions that matter.
Long-term memory across sessions, not goldfish chat.
Specialized agents collaborate on bigger jobs.
Agents call real tools: browsers, terminals, APIs.
Download the source and move into the project folder.
git clone https://github.com/career-ops-hq/career-ops.git
cd career-opsEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at career-ops-hq/career-ops with 13,797 forks. Check the repo's contributors and recent commits to see how active maintenance is.
MIT licensed — use it commercially, no strings attached.
For bounded tasks with supervision, yes. Fully autonomous money-moves still need guardrails.
Sandboxing, approval gates, and least-privilege credentials.
Builders exist, but code-first frameworks go further.
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear deb…
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message…
Make humans and AI agents work as one team — open-source and self-hostable.
NVIDIA's security scanner for AI agent skills - check before you install
Scan your LLM for vulnerabilities before attackers do.
Exa's MCP server for web search and crawling — give your AI agent a live, high-quality web index.
The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if career-ops is not the right fit.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Free and open — grab the source, star the repo, and start creating.