Official agent skill

Commerce Prompt Caching

by anthropics in anthropics/commerce-agents

The reference agents' cache-stable request assembly, covering the static system and per-request context split, the fixed tool list, the rolling conversation breakpoint, which config fields are…

OfficialApache-2.0Auto-check passedFrontend & Design

Install Commerce Prompt Caching

skills CLI
$ npx skills add anthropics/commerce-agents --skill commerce-prompt-caching -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install anthropics/commerce-agents commerce-prompt-caching --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/anthropics/commerce-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/commerce-builder/skills/commerce-prompt-caching .claude/skills/commerce-prompt-caching && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
commerce-prompt-caching
GitHub stars
3.2k
Token cost
~2k tokens
SKILL.md length
1,017 words
Files
1
Skills in repo
16
Repo updated
First seen
Licence
Apache-2.0

At a glance

The reference agents' cache-stable request assembly, covering the static system and per-request context split, the fixed tool list, the rolling conversation breakpoint, which config fields are…

  • Works in 3 steps: The last tool:… → The static system text:… → The newest persisted message:…
  • Tasks that involve Responsive design
  • SKILL.md covers The three breakpoints, The split as implemented, When the rolling marker is… and When the conversation is…, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Commerce Prompt Caching is an agent skill from anthropics/commerce-agents, published by the product's own GitHub organization. The reference agents' cache-stable request assembly, covering the static system and per-request context split, the fixed tool list, the rolling conversation breakpoint, which config fields are prompt bytes, and verification. Load when writing or reviewing a commerce agent's prompt assembly, when cache reads are zero, or when a turn's latency or cost is the question.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Frontend & Design, covering Responsive design and LLM cost and token optimization. The repository describes itself as: Reference blueprint for building shopping and merchant agents with Claude. Examples in retail, commerce, telecom, and entertainment included. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Responsive design
  • Tasks that involve LLM cost and token optimization

Example prompts

  • “s prompt assembly, when cache reads are zero, or when a turn”
  • “/commerce-prompt-caching”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. The last tool: with_tool_cache_control(tools).
  2. The static system text: build_system_blocks(static, context) marks it and appends the context block unmarked.
  3. The newest persisted message: build_request_messages(messages, rolling_breakpoint=...) marks the last persisted

What it can do on your machine

Read from SKILL.md and the folder at commit fd4d592. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Commerce Prompt Caching loads about 2k tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 1,017 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from anthropics/commerce-agents at commit fd4d592, republished under its Apache-2.0 licence (© anthropics). 1,017 words, ~2,022 tokens.

Download SKILL.mdSave it as .claude/skills/commerce-prompt-caching/SKILL.md (or your agent's skills folder).
name
commerce-prompt-caching
description
The reference agents' cache-stable request assembly, covering the static system and per-request context split, the fixed tool list, the rolling conversation breakpoint, which config fields are prompt bytes, and verification. Load when writing or reviewing a commerce agent's prompt assembly, when cache reads are zero, or when a turn's latency or cost is the question.

Cache-stable request assembly

commerce_common/ is commerce-common/commerce_common/, shopping_agent/ is shopping-agent/core/shopping_agent/, and merchant_agent/ is merchant-agent/core/merchant_agent/.

The three breakpoints

A request's cacheable prefix runs tools, then system, then the messages; a breakpoint ends a span the next call reads back. The reference agents place three, all from commerce_common/prompt_assembly.py:

  1. The last tool: with_tool_cache_control(tools).
  2. The static system text: build_system_blocks(static, context) marks it and appends the context block unmarked.
  3. The newest persisted message: build_request_messages(messages, rolling_breakpoint=...) marks the last persisted block on the outgoing request only; the next call then reads the earlier rounds, search payloads included, from cache.

Everything per request goes in the context block, which the role's build_dynamic_context(...) renders once per turn. In the static block or the tool list, those bytes would break the system or tool span on every request; in the context block they cost one re-read of the conversation on a turn whose cart, page, or facts moved, and the rolling marker holds from that turn's next round. The clock renders to the hour (context_clock), so a new minute moves nothing.

The split as implemented

  • build_static_system(config, skills) in each role's prompt.py renders identity, the most-turns rules, the fence notice, and the skill index from the config and the installed skills: the same bytes for the life of a deployment.
  • build_dynamic_context(...) in the same module renders the per-request material inside the role's data fence: shopping takes preferences, memory facts, the cart, the page, the account block, and the time; merchant takes the store context, memory facts, and the time. Backend context blocks have their own size cap.
  • ShoppingAgent.__init__ and MerchantAgent.__init__ (each role's runtime-messages-api orchestrator.py) build _static_system and _tools once per process; stream_turn renders the context block per turn and calls build_request_messages per model call.
  • build_tools in each role's tools/registry.py emits the built-ins in a fixed order (the merchant builder adds run_analysis after them when enabled), the load_skill enum sorted, then extensions in the order given, then web_search when enabled; every registered tool ships on every request, and the executor decides on arrival whether a call can be served.
  • The Agent SDK runtimes pass the same static text (plus SKILL_TOOL_ADAPTER) and the same contracts, and the SDK caches them; the hosted manifests carry the text as system.md, which scripts/check.py compares with the builder.

When the rolling marker is skipped

Two rounds carry no marker. A bare first call (one message): a one-shot session would pay the write without a read, and the second call's marker covers the first message anyway. A round whose tool_choice is other than auto (the grounding-forced first iteration and the forced-text last one): tool_choice keys the messages span, so an entry written under a forced round is unreadable by the auto rounds after it; the system and tool spans still hit. Both live in build_request_messages and the loops' rolling_breakpoint= argument; rolling_conversation_cache turns the marker off for debugging.

When the conversation is compacted

When a turn's last call was given compact_history_above_tokens or more (its usage says; the default is the platform's own tool-result-clearing default, a tenth of the window), the turn ends with compact_history in commerce_common/turn.py, which replaces the oldest tool results in the stored conversation with a one-line marker until the conversation is half its previous size. The next turn's first round rewrites the messages span once and later rounds read the shorter one; turn_complete.results_cleared tells a host that appends its transcript to rewrite it. The system and tool spans, the messages, and the write gates are unaffected; provenance lives on the session state.

Show full SKILL.md (438 more words)Show less

Config fields that are prompt bytes

The fields marked (prompt) in commerce_common/config.py and the role configs, plus enable_analysis and max_items_per_change, which the merchant tool builder reads, render into the static text or the tool list; changing one is a redeploy and a miss on the next request:

ConfigFields
BaseAgentConfig (commerce_common/config.py)brand_name, assistant_name, brand_voice, enable_web_search
ShoppingAgentConfig (shopping_agent/config.py)domain_search_notes, enable_disclosures, and the system switches enable_cart, enable_orders, enable_policies, enable_fulfillment
MerchantAgentConfig (merchant_agent/config.py)enable_analysis, require_host_approval, approval_surface, stage_shows_preview, and the system switches enable_listing_edits, enable_inventory, enable_pricing, enable_campaigns; max_items_per_change and max_search_results set maxItems and maximum on tool schemas

Skills, presentation extensions, and delegates are prompt bytes too. Gate lexicons, guardrail limits, memory settings, the latency knobs (eager_tool_dispatch, rolling_conversation_cache, eager_partial_frames, close_on_presentation), cart caps, and compact_history_above_tokens are not; tests/test_role_registries.py asserts it for each.

What breaks a hit

  • Anything per request in the static block or the tool list: a name, a cart count, a page, a clock, a request id. The context block takes the first four; a request id belongs nowhere.
  • A set or dict iterated into prompt text or a schema without sorting.
  • tools[] membership decided per request (a flag read per request instead of once at construction).
  • Rebuilding the static text or the tool list inside the turn instead of in the constructor.
  • Persisting the rolling marker into the stored conversation, which then gains one marker per turn.
  • Toggling a (prompt) field, a skill, or an extension on a running deployment; each is a redeploy.
  • A prompt variant chosen per request instead of per deployment.
  • A prefix under the model's minimum cacheable length, which writes nothing.
  • A forced tool_choice (grounding first, none last) misses the messages span only; the loops skip the marker there.

How to verify

  • turn_complete carries usage (usage_totals in commerce_common/turn.py, the turn's calls summed) and elapsed_ms; every call also logs one line with the same counters and its own time (log_model_call, on shopping_agent_runtime.orchestrator and merchant_agent_runtime.orchestrator). Zero cache reads on the second turn of a conversation means the prefix changed. The counters worth charting per config version are cache reads as a share of input, elapsed_ms, rounds per turn, and blocked tool_result events by gate.
  • tests/test_role_registries.py builds each role's prompt and tools twice and compares bytes, checks the cache marks, and checks that non-prompt settings change nothing; commerce-common/tests/test_prompt_assembly.py covers the block builders, the context clock, the rolling marker, and the skip cases; tests/test_turn_loop.py pins both loops to the same blocks, marker, and clean history. A deployment's tests carry the same three checks.
  • In a deployed environment, run one three-turn conversation and read the second and third turns' usage; a proxy or retry layer that rewrites requests shows up here and nowhere else.

© anthropics, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/commerce-builder/skills/commerce-prompt-caching of anthropics/commerce-agents.

Open the folder on GitHubat commit fd4d592

Compare with similar skills

Commerce Prompt Caching next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Commerce Prompt Caching compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Commerce Prompt Caching this skillanthropics/commerce-agents3.2k—~2kAutomated safety check: PassApache-2.0
Prompt Caching Patternssoftspark/ai-toolkit179—~1.1kAutomated safety check: PassApache-2.0
UI StylingOhh-889/skyroc79513 repos~2.5kAutomated safety check: PassMIT
Material 3hamen/material-3-skill1.5k2 repos~7.8kAutomated safety check: PassMIT
Trip Map Builderhiyeshu/trip-map-builder244—~1.7kAutomated safety check: PassNone
Antislop Layoutmobilemiqdadbadjuber/anti-slop5.7k—~4.1kAutomated safety check: PassMIT

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  • Commerce Merchant Operations

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  • Commerce Trust Safety

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Questions about Commerce Prompt Caching

What does Commerce Prompt Caching do?

The reference agents' cache-stable request assembly, covering the static system and per-request context split, the fixed tool list, the rolling conversation breakpoint, which config fields are…. Commerce Prompt Caching is an agent skill from anthropics/commerce-agents, published by the product's own GitHub organization. The reference agents' cache-stable request assembly, covering the static system and per-request context split, the fixed tool list, the rolling conversation breakpoint, which config fields are prompt bytes, and verification.

When should I use Commerce Prompt Caching?

Commerce Prompt Caching fits situations like: tasks that involve Responsive design; tasks that involve LLM cost and token optimization.

How do I install Commerce Prompt Caching in Claude Code?

Run `npx skills add anthropics/commerce-agents --skill commerce-prompt-caching -a claude-code`. Or copy the skill folder (plugins/commerce-builder/skills/commerce-prompt-caching in anthropics/commerce-agents) into .claude/skills/commerce-prompt-caching in your project. Claude Code loads it when a task matches its description.

How do I install Commerce Prompt Caching in Codex?

Run `npx skills add anthropics/commerce-agents --skill commerce-prompt-caching -a codex`. Or copy the skill folder (plugins/commerce-builder/skills/commerce-prompt-caching in anthropics/commerce-agents) into .agents/skills/commerce-prompt-caching in your project. Codex loads it when a task matches its description.

Can I use Commerce Prompt Caching in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add anthropics/commerce-agents --skill commerce-prompt-caching -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/commerce-prompt-caching, .gemini/skills/commerce-prompt-caching, .github/skills/commerce-prompt-caching and .opencode/skills/commerce-prompt-caching in your project.

What does Commerce Prompt Caching need to run?

SKILL.md names no scripts, command-line tools or credentials: Commerce Prompt Caching is instructions for the agent only.

Does Commerce Prompt Caching access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Commerce Prompt Caching safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Commerce Prompt Caching use?

Commerce Prompt Caching is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Commerce Prompt Caching use?

About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Commerce Prompt Caching?

Skills that share tags, products or a category with Commerce Prompt Caching: Prompt Caching Patterns (softspark/ai-toolkit, 179 stars), UI Styling (Ohh-889/skyroc, 795 stars), Material 3 (hamen/material-3-skill, 1.5k stars) and Trip Map Builder (hiyeshu/trip-map-builder, 244 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Commerce Prompt Caching?

anthropics (a GitHub organization, an official publisher) maintains it in anthropics/commerce-agents, which has 3,198 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on October 2, 2026.

Source: anthropics/commerce-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.