| name | linkfox-amazon-help-doc-changes |
| description | 监控亚马逊卖家帮助文档（帮助中心）的内容变更，经 AI 筛选后返回对卖家有价值的改动，支持按变更时间区间、标题关键词分页检索，并按变更记录 ID 获取 AI 变更摘要、具体改动点与最新文档全文。当用户提到亚马逊帮助文档变更、帮助中心更新、规则变动监控、政策/费用文档调整、合规预警、文档改了什么、最新文档全文，或 Amazon help doc changes, Seller Central help center updates, policy/fee documentation changes, compliance alert 时触发此技能。即使用户未明确提及"帮助文档变更"，只要其需求涉及亚马逊帮助中心文档的更新监控及变更详情，也应触发此技能。 |
Amazon Help Doc Change Monitor
This skill monitors changes to Amazon Seller Central Help documentation. An AI layer pre-screens edits and surfaces only the changes that actually matter to sellers. It is a two-step (list → detail) flow: first list AI-curated valuable changes by time window / title keyword, then fetch the change detail + latest full document by its id.
Core Concepts
- AI-curated, not raw diffs: results contain only changes the AI judges "valuable to sellers". Pure formatting / non-substantive edits are filtered out, so the returned count is usually far smaller than the document's actual edit count — this is by design, not missing data.
- Two coupled tools:
amazon/helpDocChanges — paginated list of valuable changes (structured), each with an AI-generated Chinese summary, ordered by change time (newest first).amazon/helpDocDetail — full change detail for one change id: AI summary + what specifically changed + the latest document body (Markdown).
- Coverage & timing: monitors English (
en-US) help docs by default. changedAt is the detection time (when the system detected the diff), not Amazon's official publish time. Change monitoring data starts from 2026-05-29. The Amazon backend original is authoritative.
Parameters
List (amazon/helpDocChanges)
| Parameter | Type | Required | Description | Default |
|---|
| keyword | string | No | Document-title fuzzy match (case-insensitive) | - |
| changedAtGte | string | No | Change-time lower bound (incl.), yyyy-MM-dd HH:mm:ss | last 3 months |
| changedAtLte | string | No | Change-time upper bound (incl.), yyyy-MM-dd HH:mm:ss | now |
| page | integer | No | Page number, starting at 1 | 1 |
| pageSize | integer | No | Items per page, 1-100 | 20 |
No parameter is required — call with no params to get the last 3 months of valuable changes.
Detail (amazon/helpDocDetail)
| Parameter | Type | Required | Description |
|---|
| id | integer | Yes | Change-record ID (≥1) from the list response data[].id |
API Usage
This skill calls the LinkFox tool gateway. See references/api.md for calling conventions, request parameters, response structure, and error codes. You can also run the scripts directly:
python scripts/amazon_help_doc_changes.py '{"keyword": "FBA", "pageSize": 20}'
python scripts/amazon_help_doc_detail.py '{"id": <id from the list response>}'
How to Build Queries
- Set the time window: convert "近一个月 / since 2026-03" into
changedAtGte / changedAtLte. Leave empty for the default last 3 months.
- Filter by keyword: pass topical terms (e.g.
FBA, fee, inventory) into keyword for title matching.
- Paginate: increase
page to scan more changes.
- Drill into a change: take a record's
id (integer) from the list and call the detail script to read the AI summary, the specific edits, and the latest document.
Usage Examples
1. Valuable changes in the last 3 months (default)
{}
2. FBA-related doc changes in a date range
{"keyword": "FBA", "changedAtGte": "2026-03-01 00:00:00", "changedAtLte": "2026-05-28 23:59:59"}
3. Page 2, 50 per page
{"page": 2, "pageSize": 50}
4. Full change detail of one record
{"id": 35}
Display Rules
- List view: present results as a table with title, breadcrumb (目录路径), change time, and the AI summary; include the original
url.
- Detail view: render the
stdout Markdown as-is; keep the leading change-summary / change-time / breadcrumb / source-link block.
- Set expectations on count: when results look sparse, remind the user that only AI-judged valuable changes are returned (formatting-only edits are filtered) — a low count is expected, not a data gap.
- Only present data: report what changed; do not add subjective business advice.
- Detection-time caveat: note that
changedAt is the detection time, not Amazon's official publish time; the backend original is authoritative.
- Error handling: on a failed call, explain the reason from the error response (e.g. invalid
id → re-fetch from the list).
Important Limitations
- AI-filtered results: only "valuable to sellers" changes appear; returned count is far smaller than the raw edit count (by design).
- English docs by default: monitors
en-US help documentation.
- Monitoring start: change data begins from 2026-05-29; earlier history is unavailable.
- Detail needs a valid list
id: amazon/helpDocDetail only accepts an integer id returned by amazon/helpDocChanges.
- Not for aggregation: detail returns long-form text and the list is change metadata — this skill's output is not suited for second-pass statistical/aggregation analysis.
User Expression & Scenario Quick Reference
Applicable — Amazon help-center documentation change monitoring:
| User Says | Scenario |
|---|
| "近一个月亚马逊帮助文档有哪些值得关注的变更" | Recent valuable changes by time |
| "亚马逊关于 FBA 的帮助文档改了什么" | Keyword-filtered doc-change lookup |
| "帮我看看这条文档变更的详情和最新全文" | Fetch change detail + latest doc by id |
| "帮助中心规则有更新吗" | Help-center rule-change monitoring |
| "费用相关的文档调整" | Fee/policy documentation change tracking |
Not applicable — beyond help-doc change monitoring:
- Amazon Seller News policy announcements → use the Amazon policy-news skill
- Product / keyword / sales analytics, listing optimization, review analysis
- Real-time storefront search results or product detail
- Account-specific notifications inside an individual seller account
Boundary judgment: if the user wants to know what changed in Amazon's help documentation (and the change detail / latest text), this skill applies. If they want Amazon's published Seller News policy announcements, use the policy-news skill; 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:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
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_help_doc_changes.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>" # or --path "<JMESPath>"
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_help_doc_changes.py, amazon_help_doc_detail.py. Pass --script scripts/<name>.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.
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