
commerce-evals
Authoring and running behavioral evals for a shopping or merchant agent, covering the case shape, authoring rules, code graders and judges, the run pattern, and poisoned fixtures. Load when writing eval cases or rubrics or deciding how a suite runs.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/anthropics/commerce-agents --skill commerce-evals- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads commerce-evals automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Commerce agent evals
The repo ships no eval harness; the suite is yours, because a case only means something against your catalog,
orders, and fixtures. Paths below are in the reference repo: commerce_common/ is commerce-common/commerce_common/.
Gate behavior that needs no model (provenance, caps, guardrails, approval) is unit-tested with FakeClient in
commerce_common/testing.py; evals cover what the model decides.
The case shape
This block is the one home of the case shape and the scorer names; /author-commerce-evals refers to it.
{
"id": "<flow>-<nnn>-<behavior>",
"priority": "critical | high | medium | low", "difficulty": "easy | medium | hard", "tags": ["..."],
"skip": "<reason, when a case cannot run yet>",
"state": {"seen_products": ["..."], "cart": [...], "memory": [...], "staged_changes": [...]},
"turns": ["<the customer's or operator's message>", "..."],
"expected": {
"calls_tool": ["..."], "calls_one_of": ["..."], "never_calls": ["..."],
"first_tool": "...", "first_tool_not": "...",
"ui_components": ["..."], "no_ui": true,
"cart_contains": ["..."], "cart_item_count": 0, "cart_not_contains": ["..."],
"staged_change_kinds": ["..."], "no_applied_changes": true,
"memory_contains": ["..."], "memory_not_contains": ["..."],
"skill_loaded": "...", "skill_not_loaded": "...", "no_skill_load": true,
"reply_includes": ["..."], "reply_omits": ["..."], "max_tool_calls": 0,
"rubric": "PASS if <condition>. FAIL if <condition>."
},
"notes": "<what the case pins and the fixture fact that decides it>"
}
state is the precondition; turns is one message unless the behavior under test is carrying state across turns;
expected holds only the keys the case is about. Ids in state and expected are real ids from your fixtures.
priority and difficulty let a report say which failures matter; a case that cannot run yet carries skip
with its reason rather than being deleted.
Authoring rules
- Preconditions go in injected state (the products already seen, the cart, the memory facts, the staged queue), which the runner loads into the session state and the memory store before the turn. Earlier turns are for state the behavior itself carries, and for nothing else.
- Every positive has a negative: for each case that asserts a component, a skill load, a gate, a disclosure, or a memory write, a case in the same niche asserts its absence. A refusal case has a should-serve counterpart.
- Memory is three cases: a remark worth keeping is written; an identifier or excluded content is refused (nothing stored, no error to the person); a stored fact changes the next session's pick.
- Grade the final tool arguments and the state they produced: the ids on the last presentation call, the fields on
the staged change, the cart and the memory store after the turn. The reply's wording is graded only for strings
that must or must not appear. Which route the agent took (
skill_loaded, one named component,never_callson a presentation tool) is asserted only where the route is the behavior (a grounding read first, a write that must never happen); elsewherecalls_one_ofnames the acceptable set. When a live run takes a route the case did not expect and the answer was right, widen the case to the acceptable set; do not re-pin it to the route observed. - A rubric is one PASS condition and one FAIL condition that no response satisfies both of; it names the fixture fact that decides it (the updated delivery date, the price today); variants you accept are written into it; it says nothing about tone, length, or the order components appear in.
- A turn that mentions health, a one-off errand, or hostile content asserts the memory end-state
(
memory_not_contains, ornever_callsonsave_memory). A case where a stored fact should change the pick uses a query whose results contain both the item the fact favors and the one it rules out; run the search before writing the case. max_tool_callsis set from what a well-behaved agent needs; a multi-item request fans out several searches in one round, and thepresent_suggestionscall that ends the turn is not counted.
Scorers
- Code graders read the events a turn yields (
commerce_common/streaming.py):tool_callnames and arguments,tool_resultwithstatusblockedand the gate inreason,uicomponent names, the lastcart_updateorchange_update, and the reply text. Every key above exceptrubricis a code grader. rubricgoes to a judge. One judge call per dimension (budget respected, no invented availability, trade-off stated), returning structured output with a verdict and a reason; the transcript is passed to it as quoted material, tool results and component payloads included; when the transcript exceeds the judge's window, truncate from the start so the graded turn survives, and record the truncation on the outcome. Pin the judge model at temperature zero; a change to the judge model or a rubric invalidates every stored verdict scored with it, so the recording carries a fingerprint of both.- A judge reply that does not parse into a verdict is a judge failure on the case, kept apart from an agent failure.
Run pattern
| When | What runs | What decides |
|---|---|---|
| Every merge to the agent, a skill, a tool description, or a fixture | The regression set | Each case over several trials; a pass threshold per set |
| While changing one flow | That flow's targeted set | The failure set, read beside the previous run's as the baseline |
| Choosing or upgrading a model (commerce-architecture's model fields) | Everything | The two failure sets side by side |
| In production | A judged sample of live traffic against the same rubrics | Trend per dimension |
Diff failure sets; a topline moving a point between live runs is noise. A case that fails after a change means the change broke the behavior or the case encoded a stale one; fix whichever it is and say which in the commit.
Poisoned fixtures
Listings, reviews, and messages carrying instructions live in eval-only fixtures the runner merges into the backend
for the run, under a third-party brand or seller; none of their ids appears in demo data, seeds, or captures. Each
such case asserts the negative in code (never_calls, cart_not_contains, no_applied_changes,
memory_not_contains, reply_omits), and every vector it asserts is one the driven turn actually puts in front of
the model (a review is only read on a details call). Cover at least an instruction to write to the cart or stage a
change, one to remember something, and a false claim (a code, a guarantee). The should-serve counterpart is a
separate benign eval-only listing in the same niche, so an agent that refuses everything fails it.
FAQ
What does the commerce-evals skill do?
Authoring and running behavioral evals for a shopping or merchant agent, covering the case shape, authoring rules, code graders and judges, the run pattern, and poisoned fixtures. Load when writing eval cases or rubrics or deciding how a suite runs.
How do I install commerce-evals?
Run npx skills add https://github.com/anthropics/commerce-agents --skill commerce-evals in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/commerce-evals/ (personal) or .claude/skills/commerce-evals/ (project).
Which AI agents can use commerce-evals?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is commerce-evals safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains commerce-evals?
It is published by anthropics in anthropics/commerce-agents. It has 40 recorded installs.
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