acp-intent-traces
Implement ACP intent traces — structured cart abandonment signals with reason codes for analytics and automated recovery workflows. Use when building abandonment tracking, recovery automation, or conversion optimization.
Best use case
acp-intent-traces is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Implement ACP intent traces — structured cart abandonment signals with reason codes for analytics and automated recovery workflows. Use when building abandonment tracking, recovery automation, or conversion optimization.
Teams using acp-intent-traces should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/acp-intent-traces/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How acp-intent-traces Compares
| Feature / Agent | acp-intent-traces | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Implement ACP intent traces — structured cart abandonment signals with reason codes for analytics and automated recovery workflows. Use when building abandonment tracking, recovery automation, or conversion optimization.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# ACP Intent Traces
## Before writing code
**Fetch live docs**:
1. Web-search `site:github.com agentic-commerce-protocol rfcs intent_traces` for the intent traces RFC
2. Fetch `https://developers.openai.com/commerce/specs/checkout/` for how intent traces integrate with checkout
3. Web-search `site:github.com agentic-commerce-protocol spec json-schema intent` for the schema
## Conceptual Architecture
### What Intent Traces Are
Intent traces are a **built-in ACP extension** that provides structured cart abandonment signals. When a buyer abandons a checkout, the agent sends a trace explaining why — enabling merchants to understand conversion barriers and automate recovery.
### 10 Reason Codes
| Code | Meaning |
|------|---------|
| `price_sensitivity` | Total was too expensive |
| `shipping_cost` | Shipping cost was a barrier |
| `shipping_speed` | Delivery time was too slow |
| `product_fit` | Product didn't match buyer's needs |
| `trust_security` | Buyer didn't trust the merchant/payment |
| `returns_policy` | Return/refund policy was inadequate |
| `payment_options` | Preferred payment method unavailable |
| `comparison` | Buyer is comparison shopping |
| `timing_deferred` | Buyer wants to purchase later |
| `other` | Doesn't fit other categories |
### How It Works
1. Buyer initiates checkout but doesn't complete
2. Agent detects abandonment (session timeout, explicit cancellation, navigation away)
3. Agent sends intent trace via `POST /checkout_sessions/{id}/cancel`, including a single `reason_code` (required enum string, exactly one per trace)
4. Merchant receives the trace and can:
- Aggregate for analytics
- Trigger automated recovery (email, discount offer)
- Adjust pricing/shipping strategy
### Privacy Considerations
- Intent traces contain behavioral signals — handle per GDPR/CCPA
- Only collect traces when the buyer has consented to data collection
- Don't store personally identifiable information in trace metadata
- Aggregate traces for analytics rather than individual tracking
### Extension Negotiation
Like all extensions, intent traces must be negotiated:
1. Agent includes `intent_traces` in `capabilities.extensions[]`
2. Merchant confirms support
3. Only then are traces exchanged
### Use Cases
- Cart abandonment analytics dashboards
- Automated recovery email workflows
- Dynamic pricing based on price sensitivity signals
- Shipping strategy optimization
- A/B testing checkout flows
- Conversion funnel analysis
### Additional Trace Fields
- **`trace_summary`** — Optional free-text summary of the abandonment reason (max 500 characters)
- **`metadata`** — Optional flat key-value map for additional context (string keys and string values only)
### Write-Only Behavior
Intent traces are **write-only** — they are sent on the `POST /checkout_sessions/{id}/cancel` endpoint and are never echoed back in GET responses. This prevents information leakage and ensures traces are used only for analytics and recovery workflows.
### Best Practices
- Send traces on every abandonment — even `other` is better than no signal
- Each trace has a single `reason_code` (required enum string); if the buyer has multiple reasons, choose the most significant one
- Process traces asynchronously — don't block the cancellation flow
- Build aggregate dashboards before automated recovery
- Test trace collection end-to-end with the agent platform
- Respect buyer privacy — anonymize before long-term storage
Fetch the intent traces RFC for exact trace payload structure, reason code definitions, and integration points before implementing.Related Skills
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