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This release is a pre-release and may not be stable for production use.

E-commerce Eval

Business acceptance testing for everyday e-commerce agents.

One business acceptance standard, multiple execution methods and verifiable evidence. An agent saying "uploaded successfully" does not prove that the product data is correct or that the approved revision was actually used.

  • 32 starter cases across eight directions: intent, company rules, business dependencies, parameters, artifact review, conversation, recovery and safety.
  • A local visual platform: inspect traces, business conditions, artifacts, approvals, execution receipts, metrics and missing evidence.
  • An Onboarding Skill: investigate a product and draft its cases, contracts and evidence gaps. The Skill is installed separately from GitHub.

Install and run

Requires Python 3.10+. This is the 0.3.0rc2 Alpha candidate, not a stable release. In a virtual environment, install the exact candidate:

python -m pip install "commerce-agent-eval==0.3.0rc2"
commerce-eval demo

Open http://127.0.0.1:8770. The built web UI and demo data are included. Git and Node.js are not required for package installation. The no-key demo does not call a real model, run the entire bank against an agent or write to a production store.

The Python distribution is named commerce-agent-eval; its command is commerce-eval and its Python module is commerce_eval.

What acceptance means

Business conditions and explicit constraints decide the result. Tool names and counts are diagnostic by default, so packaged business tools and lower-level file tools can be judged against the same business conditions. Required evidence that is absent remains unverifiable, never an automatic pass.

Real integrations still need a controlled execution environment and evidence collectors. No universal zero-adaptation integration or production success rate is claimed. External model calls are explicit opt-in and may transmit inputs to the configured provider and incur charges.

Documentation

Metadata

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