tracelint is a deterministic linter that analyzes execution traces of tool-calling agents to identify structural bugs. By flagging issues like schema violations and ignored errors, it provides clear evidence alongside a CI exit code. This approach eliminates the need for unreliable model-based judgments, making trace analysis straightforward and effective.
tracelint is a specialized linter designed for agent runs, providing a deterministic solution to identify structural bugs within execution traces. It analyzes the actual actions performed by a tool-calling agent and flags significant issues, such as ignored errors, schema violations, loops, and redundant calls, complete with precise evidence from the execution trace and an appropriate continuous integration (CI) exit code. This functionality is critical for ensuring robustness in automated systems where tool behavior must be reliable and predictable.
Detailed Trace Analysis: tracelint meticulously examines tool-calling agent traces to uncover structural defects, including:
Evidence-Based Reporting: Each detected issue is accompanied by the exact lines from the execution trace, providing clear and actionable insights.
Deterministic Evaluation: Unlike other models that rely on subjective judgments to detect defects, tracelint operates deterministically, which enhances reliability and accuracy in identifying structural problems.
CI Integration: Designed to easily integrate with CI pipelines, tracelint returns exit codes that reflect the outcome of the linting process. The codes indicate a clean run (0), structural defects (2), or input errors (3).
To incorporate tracelint into a CI workflow, the following command can be executed:
tracelint check ./trace.json --tools ./tools.json
This command analyzes the specified trace JSON against the defined tool schema and returns the appropriate exit code based on the findings.
Additionally, tracelint offers a fault injector and a recovery scorecard that evaluates how the agent performs under specific injected faults. This feature aids in determining behavioral recovery rates, ensuring agents can handle errors gracefully:
tracelint scorecard --demo --faults timeout,error,rate_limit --runs 5
Traces should be structured as JSON objects following the prescribed format, which allows tracelint to evaluate each step effectively. Here's a sample input format:
{
"run_id": "run-1",
"steps": [
{"type": "message", "role": "user", "content": "cancel order 4521 if it hasn't shipped"},
{"type": "tool_call", "call_id": "c1", "name": "get_order_status", "args": {"order_id": "4521"}},
{"type": "tool_result", "call_id": "c1", "content": {"status": "processing"}, "status": "ok"},
{"type": "tool_call", "call_id": "c2", "name": "cancel_order", "args": {"order_id": "4521", "reason": "not_shipped"}}
],
"final": "Order 4521 has been cancelled."
}
Tool definitions also need to be provided in a complementary JSON format to allow tracelint to validate the tool calls against expected schemas.
tracelint stands out as a robust tool for developers and automation engineers who seek to enforce quality and reliability in agent-driven processes. By highlighting structural defects with the necessary evidence, this linter facilitates better debugging, enhances system resilience, and promotes confidence in tool performance.
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