About commerce-architecture
commerce-architecture documents the design of shopping and merchant agents for teams implementing or deploying them. It explains the shared execution loop, skill loading, backend interfaces, and delegation boundaries, including where different rules belong.
Key features
- 01Describe shopping and merchant agent loops
- 02Separate prompt, tool, and skill rules
- 03Define shopping and merchant backend interfaces
- 04Specify skill loading and deployment configuration
- 05Constrain delegate inputs and permissions
Use cases
- 01Implement a backend for a commerce agent
- 02Choose the architectural layer for a behavior rule
- 03Configure skills and available tools
- 04Plan model selection and evaluations for deployment
MCP support
The shopping and merchant MCP servers share their executor with the Messages API runtime and Agent SDK. The MCP servers route tool calls through role-specific executors.
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ anthropics/ commerce-agents --skill commerce-architectureAfter installing, type/commerce-architecturein Claude Code to confirm it loaded.
Details
From the project READMECommerce agent architecture
Paths are in the reference repo: commerce_common/ is commerce-common/commerce_common/, shopping_agent/ is
shopping-agent/core/shopping_agent/, merchant_agent/ is merchant-agent/core/merchant_agent/, and the runtimes are
shopping-agent/runtime-messages-api/shopping_agent_runtime/ and merchant-agent/runtime-messages-api/merchant_agent_runtime/.
One loop
- One model owns the conversation. A turn is
ShoppingAgent.stream_turnorMerchantAgent.stream_turn(each runtime'sorchestrator.py): the model reads the cached prompt, calls tools (one round's calls run concurrently), and ends with text plus presentation calls. There is no router, classifier, or hand-off. - Every call on every path runs through the role executor (
ShoppingToolExecutorinshopping_agent/executor.py,MerchantToolExecutorinmerchant_agent/executor.py) overBaseToolExecutorincommerce_common/execution.py. The Messages API runtime, the Agent SDK toolset, and the MCP server call the sameexecute, which never raises; aftermax_tool_iterationsrounds (commerce_common/config.py) the runtime forces a round without tools.
Where a rule lives
| A rule that applies | Lives in | Reference |
|---|---|---|
| While one call's arguments are being filled in | That tool's description | build_tools in each role's tools/registry.py |
| On most turns: cart and checkout, the staged-write contract, presentation grammar, tool order, trust rules | The static prompt | build_static_system in each role's prompt.py |
| On the minority of requests that need a multi-step procedure | A skill, loaded on demand | shopping-agent/skills/, merchant-agent/skills/ |
A rule the core journey needs on most conversations moves a layer down. This table is the one statement of the layering.
Skills
- A skill is a directory holding
SKILL.md: frontmatternameanddescription, then the body (parse_skill_mdincommerce_common/skills.py). The description names the request class; it carries no sample utterances. - The static prompt carries the index alone (
SkillRegistry.index_block, sorted by name) andload_skillreturns one body (_load_skillincommerce_common/execution.py). On the Agent SDK,ensure_project_skillslinks the same directories into.claude/skills/andSKILL_TOOL_ADAPTERpoints the model at the SDK'sSkilltool (commerce_common/agent_sdk.py); the hosted manifests list the directories underskills[]inagent.yaml.
The backend interface
A deployment implements one abstract class per role; nothing else reaches its systems.
StorefrontBackend(shopping_agent/backend.py): 11 abstract methods, catalog (2), cart (4), preferences (1), orders (2), policies (1), fulfillment (1);get_account_context,get_disclosure, andcheckout_handoffhave defaults. No method places an order or moves money;checkout_handoffnames where payment happens (a hosted checkout URL, or one per seller) and the host renders it.MerchantBackend(merchant_agent/backend.py): 16 abstract methods, reads (8: performance 3, catalog 2, inventory and order health 2, pricing 1) and the change lifecycle (8: fivestage_*,get_pending_changes,apply_change,discard_change);execute_analysis_query,get_analysis_schema,get_merchant_contexthave defaults.- A product or listing sold by size, color, or tier is a family record carrying
options, its variants each a record withoption_valuesandvariant_of; the cart and price or restock writes take a variant's id and the gates hold a family's.docs/backends.mdhas the mapping from common catalog models and what to return for a figure the platform cannot supply. - Eligibility, pricing, inventory, and quantity rules are enforced in the backend; the gates check provenance and caps (commerce-trust-safety). Everything a backend returns is fenced before the model reads it.
- A system that is not wired yet is a method that fails (merchant methods raise
ChangeNotApplicablefrommerchant_agent/changes.py); the tool stays registered, so prompt bytes do not change. A system the business does not have at all is absent: anenable_*switch on the role's config turned off, which removes its tools (absent_tools()), prompt lines, and grounding rule on all three paths, and the executor refuses those names; the skills that need it are parked underskills/_staged/, and the bytes are then fixed for that deployment.NotOffered(shopping_agent/backend.py) is the narrower signal: one item or seller the store does not serve while the system itself is on. executor_class=onShoppingAgent/MerchantAgent, the SDK toolsets, and the MCP servers'build_servertakes a subclass of the role's executor for a deployment's owndomain_errormapping or result wording.
Delegates
A second model call takes one shape: a DelegateExtension (commerce_common/delegation.py). It receives a brief
and the handles in DelegationContext, never the conversation or the executor; it returns one result validated
against result_model; it cannot write, present, or call a delegate; _run_delegate in commerce_common/execution.py
caps its calls per turn at max_delegate_calls_per_turn. MerchantAgent takes extra_delegates, and its
built-in instance is run_analysis (commerce-merchant-operations). ShoppingAgent registers none.
Model fields
model runs the turn loop and memory_model the post-turn extraction (BaseAgentConfig in commerce_common/config.py);
analysis_model runs the delegate, and None means model (MerchantAgentConfig in merchant_agent/config.py). The
SDK runtimes copy config.model into the options; the manifests set model:. Choose the values with your own evals.
Do not
- Vary
tools[]or the static prompt by request (commerce-prompt-caching). - Put a most-turns rule in a skill, or a one-tool rule in the prompt.
- Enforce a cap or a permission in prompt text alone; it belongs in the executor or the backend.
- Let the model author a price, a figure, or a term; components are joined from server records (commerce-ui-tools).
- Add a domain tool to a core package; a vertical adds UI through
PresentationExtensionand keeps the rest in its own code.