Who it is forA developer debugging a failing test or wrong output in a Python project who needs to know which path delivered the bad value.
The problemTracing a wrong value by hand means opening every caller and following arguments through several files.
The outcomeThe headless agent reports where the bad value originated and the call chain that carried it, with the runtime evidence it gathered.
What you need first
- Python 3.11 to 3.14 on Windows, macOS or Linux, for the pip install
- An email address for the one-time login code
- An API key from Anthropic or a non-Anthropic provider (DeepSeek, Groq, Kimi and others) for the Benzi agent, or an existing MCP-capable agent such as Claude Code or Cursor for the MCP server
Steps
- Run
pip install benzi. - Run
benzi-login --login [email protected], then type the one-time code emailed to you. - Run
benzi-login --model deepseek. - Run
benzi-login --nonanthropic-key YOUR_KEYwith your own key, or usebenzi-login --anthropic-key YOUR_KEYfor Claude models. - Run
benzi-headless . "find where the wrong value in <symptom> comes from"from the repo root. (inferred, check the README)
Prompt for your agent
In the repo at <repo path>, use Benzi to trace where the wrong value in <symptom or variable name> originates. Expected output: the origin file and line plus the call chain that carried the value. Verify the origin by checking that the cited line produces the value when the repro runs.
Caveat. The runtime tracer is temporarily broken as of October 14, 2026, and misses calls inside comprehensions, lambdas and generator expressions, so some traces may be incomplete.
Use this in your AI agent
Ask your agent
Using the Deduped MCP, get the setup steps for oooscoos/Benzi and "Trace a wrong value back to where it came from"
Add Deduped to Claude Code once
claude mcp add --transport http deduped https://dedupedai.com/mcp
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