HALO debugs local AI agent traces and suggests fixes
HALO is an tool for finding problems in the of . The workflow is simple: run the agent, send its traces to HALO, read the report, apply the suggested fixes, and run the agent again.
It can read OTEL traces from tools such as Langfuse and Arize/OpenInference, and it can also work with plain JSONL files. HALO uses an RLM to split large trace analysis into smaller problems, so it can look for repeated patterns and deeper issues that a regular LLM may miss.
It can also use the path to the agent’s code, which gives it more context for more specific advice. The includes a local that does not require signup or complex setup.
Key points
- HALO analyzes AI and returns a problem report.
- The intended loop is run, analyze, fix, and run again.
- It supports OTEL traces from tools like Langfuse and Arize/OpenInference.
- It can also read plain JSONL files.
- A local is included, with no signup or complex setup required.