Amazon Policy & Regulation Feed

This skill retrieves Amazon's latest policy & regulation feed for cross-border sellers. It is a two-step (list then detail) flow: first list feed items by site / time window, then fetch the full article body by its id.

Core Concepts

• Source: Amazon official policy & regulation updates for sellers, curated by AI to surface items valuable to cross-border operations.
• AI summary: Each feed item includes a summaryZh field — an AI-generated 1-3 sentence Chinese summary for quick scanning.
• Two coupled tools:
  1. amazon/policyFeed — paginated list; returns structured records with title, AI summary, original URL, and publish time.
  2. amazon/policyFeedDetail — full article body (Markdown) for a single record id obtained from the list.
• Time range: Defaults to the last 7 days; supports custom time windows via publishedAtGte / publishedAtLte.

Parameters

List (amazon/policyFeed)

Detail (amazon/policyFeedDetail)

Supported Marketplaces (for site)

US, JP, UK, AU, BE, BR, CA, EG, FR, DE, IN, IT, MX, NL, PL, SA, SG, ES, SE, TR, AE, ZA, IE. Default is US when not specified. Note: site filtering only applies to some feed item types; others are always returned regardless of site.

API Usage

See references/api.md for calling conventions, request parameters, response structure, and error codes. Run scripts directly:

python scripts/amazon_policy_feed.py '{"site": "US", "pageSize": 20}'
python scripts/amazon_policy_feed_detail.py '{"id": "\x3Cid from list>"}'

How to Build Queries

1. Set the time window: convert user's time reference into publishedAtGte / publishedAtLte. Leave empty for the default last 7 days.
2. Pick the marketplace: map user's target country to the site code (default US). Note this only filters some feed item types.
3. Paginate: increase page to scan deeper; max 100 items per page.
4. Drill into a record: take a record's id from the list and call the detail script to read the full body.

Usage Examples

1. Recent feed (last 7 days, US)

{"site": "US", "pageSize": 20}

2. Custom date range

{"site": "US", "publishedAtGte": "2026-05-01 00:00:00", "publishedAtLte": "2026-05-31 23:59:59"}

3. Japan site feed, page 2

{"site": "JP", "page": 2, "pageSize": 50}

4. Full body of one record

{"id": "a1b2c3d4e5f6a1b2c3d4e5f6a1b2c3d4"}

Display Rules

1. List view: present results as a table with title, AI summary (summaryZh), publish time, and original URL link.
2. Detail view: render the stdout Markdown as-is; the response also includes title and summaryZh for context.
3. Only present data: report what the feed says; do not add subjective business advice or speculate on future policy.
4. Timeliness note: data may lag the live page by a short period; the Amazon original is authoritative.
5. Error handling: on a failed call, explain the reason from the error response (e.g. invalid id -> re-fetch from the list) instead of guessing.

Important Limitations

• Default window is 7 days: without explicit time params, only the last 7 days are returned.
• Max 100 items per page: pageSize range is 1-100.
• Detail needs a valid list id: amazon/policyFeedDetail only accepts an id returned by amazon/policyFeed; unknown ids return an error.
• Not for aggregation: this skill's output is long-form text and metadata — not suited for second-pass statistical/aggregation analysis via _dataQuery_executeDynamicQuery.

User Expression & Scenario Quick Reference

Applicable — Amazon official policy & regulation feed:

Not applicable — beyond policy & regulation feed:

• Product / keyword / sales analytics, listing optimization, review analysis
• Real-time storefront search results or product detail
• Account-specific notifications inside an individual seller account
• Historical patent or trademark searches

Boundary judgment: if the user wants Amazon's officially published policy, regulation, or compliance updates for sellers (and its full text), this skill applies. If they want product/keyword/sales data, use the corresponding data skills.

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply:

1. The functionality or purpose described in this skill does not match actual behavior
2. The skill's results do not match the user's intent
3. The user expresses dissatisfaction or praise about this skill
4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

\x3C!-- LF_LARGE_RESPONSE_BLOCK -->

Handling Large Responses

To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:

python scripts/response_io.py run --script scripts/amazon_policy_feed.py --out-dir \x3CDIR> '\x3Cparams>'
python scripts/response_io.py read \x3Cfile> --fields "\x3Cpaths>"   # or --path "\x3CJMESPath>"

Pick --out-dir outside any git working tree (e.g. /tmp/... on Unix, %TEMP%/... on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.

This skill exposes multiple entry scripts: amazon_policy_feed.py, amazon_policy_feed_detail.py. Pass --script scripts/\x3Cname>.py to choose the one you need.

run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.

When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:

• High field count per record, or fields you don't need
• Batch/paginated results (multiple items per call)
• Long-text fields (descriptions, reviews, HTML, time series)
• Output reused across later steps rather than consumed immediately

For small, single-use responses, calling the main script directly is fine.

⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read. \x3C!-- /LF_LARGE_RESPONSE_BLOCK -->

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