Comparison
agentic-radar vs TradingAgents
Verdict
Pick agentic-radar when tags unique to agentic-radar: ai, agentic-framework, agentic-workflow, agentic-ai; pick TradingAgents when requirements: Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework..
Markdown twin · agentic-radar alternatives · TradingAgents alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | agentic-radar | TradingAgents |
|---|---|---|
| Maintenance | Slowing (225d since push) As of today · github_public_v1 | Very active (5d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No criticals As of today · mcp_manifest@v1 | No lockfile As of today · none |
Tagline
- agentic-radar
- A security scanner for your LLM agentic workflows
- TradingAgents
- Multi-Agents LLM Financial Trading Framework
Stars
- agentic-radar
- 997
- TradingAgents
- 92k
Forks
- agentic-radar
- 137
- TradingAgents
- 18k
Open issues
- agentic-radar
- 15
- TradingAgents
- 292
Language
- agentic-radar
- Python
- TradingAgents
- Python
Adopt for
- agentic-radar
- -
- TradingAgents
- Use TradingAgents for projects requiring a sophisticated framework to develop and deploy AI agents in financial market transactions leveraging Large Language Models. Avoid it if you need simpler tools or frameworks thatだ
Persona
- agentic-radar
- -
- TradingAgents
- -
Runtime
- agentic-radar
- -
- TradingAgents
- -
License
- agentic-radar
- Apache-2.0
- TradingAgents
- Apache-2.0
Last pushed
- agentic-radar
- Nov 27, 2025
- TradingAgents
- Jul 5, 2026
Categories
- agentic-radar
- Vector Databases, LLM Frameworks, AI Agents
- TradingAgents
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- agentic-radar
- Slowing (36%)
- TradingAgents
- Very active (96%)
Days since push
- agentic-radar
- 225d
- TradingAgents
- 5d
Open issues (now)
- agentic-radar
- 15
- TradingAgents
- 292
Security scan
- agentic-radar
- No criticals
- TradingAgents
- No lockfile
Full report
- agentic-radar
- Trust report
- TradingAgents
- Trust report
Choose agentic-radar if…
- Tags unique to agentic-radar: ai, agentic-framework, agentic-workflow, agentic-ai.
- Also covers Vector Databases.
- Leaner open-issue backlog (15).
When NOT to use agentic-radar
- Last GitHub push was 226 days ago (slowing maintenance, Nov 27, 2025). Validate activity before betting a new project on agentic-radar.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
Choose TradingAgents if…
- Requirements: Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework..
- Tags unique to TradingAgents: multiagent, llm, finance, trading.
- When your project involves complex multi-agent interactions specifically in the finance domain, utilizing LLMs to manage trading strategies.
When NOT to use TradingAgents
- If simplicity and ease of deployment are prioritized over advanced AI capabilities; TradingAgents' complexity might introduce unnecessary overhead.
- When the focus is on non-financial applications or when LLM integration isn't necessary, as this framework specializes in financial market trading with a multi-agent approach.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (splx-ai/agentic-radar) · observed Jul 11, 2026
- GitHub forks (splx-ai/agentic-radar) · observed Jul 11, 2026
- Last push (splx-ai/agentic-radar) · observed Nov 27, 2025
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (TauricResearch/TradingAgents) · observed Jul 11, 2026
- GitHub forks (TauricResearch/TradingAgents) · observed Jul 11, 2026
- Last push (TauricResearch/TradingAgents) · observed Jul 5, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentic-radar 997 · TradingAgents 92k (synced Jul 11, 2026).
Common questions
- What is the difference between agentic-radar and TradingAgents?
- agentic-radar: A security scanner for your LLM agentic workflows. TradingAgents: Multi-Agents LLM Financial Trading Framework. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentic-radar over TradingAgents?
- Choose agentic-radar over TradingAgents when Tags unique to agentic-radar: ai, agentic-framework, agentic-workflow, agentic-ai; Also covers Vector Databases; Leaner open-issue backlog (15).
- When should I choose TradingAgents over agentic-radar?
- Choose TradingAgents over agentic-radar when Requirements: Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework.; Tags unique to TradingAgents: multiagent, llm, finance, trading; When your project involves complex multi-agent interactions specifically in the finance domain, utilizing LLMs to manage trading strategies.
- When should I avoid agentic-radar?
- Last GitHub push was 226 days ago (slowing maintenance, Nov 27, 2025). Validate activity before betting a new project on agentic-radar. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- When should I avoid TradingAgents?
- If simplicity and ease of deployment are prioritized over advanced AI capabilities; TradingAgents' complexity might introduce unnecessary overhead. When the focus is on non-financial applications or when LLM integration isn't necessary, as this framework specializes in financial market trading with a multi-agent approach.
- Is agentic-radar or TradingAgents more popular on GitHub?
- TradingAgents has more GitHub stars (92,290 vs 997). Stars measure visibility, not whether either tool fits your constraints.
- Are agentic-radar and TradingAgents open source?
- Yes - both are open-source projects on GitHub (agentic-radar: Apache-2.0, TradingAgents: Apache-2.0).
- Where can I find alternatives to agentic-radar or TradingAgents?
- GraphCanon lists graph-backed alternatives at agentic-radar alternatives and TradingAgents alternatives (agentic-radar markdown twin, TradingAgents markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, agentic-radar or TradingAgents?
- agentic-radar: Slowing. TradingAgents: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for agentic-radar and TradingAgents?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentic-radar trust report; TradingAgents trust report.