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SKILL.md
npx skills add linkfox-ai/linkfox-skills --skill linkfox-product-title-analyze
对产品标题进行分词分析，提取词频、场景词、人群词、材质词等属性维度。当用户想分析产品标题、提取标题高频词、进行标题分词、发现场景词或人群词、对比不同商品的标题关键词用法、基于词频优化Listing标题、识别一组ASIN中的常见属性规律、title tokenization, word frequency analysis, scene keyword extraction, audience keyword analysis, title optimization, attribute keyword extraction, keyword frequency时触发此技能。即使用户未明确说"标题分析"，只要其需求涉及将产品标题拆解为有意义的词组、统计关键词频率或按提取的属性对商品分组，也应触发此技能。
npx skills add linkfox-ai/linkfox-skills --skill linkfox-product-title-analyze
This skill guides you on how to tokenize and analyze product titles from previously queried products, helping Amazon sellers extract keyword patterns, scene words, audience words, and other attribute dimensions from product listing titles.
Product Title Analysis performs intelligent tokenization on product titles that have already been retrieved in the current conversation. It uses LLM-powered analysis to extract structured attributes (scene words, audience words, materials, colors, etc.) from free-text titles, then groups and counts them for pattern discovery.
Automatic data aggregation: The tool automatically collects products from all prior steps in the current conversation turn -- even across paginated queries. You do NOT need to manually pass product data unless you are referencing data from a previous conversation turn.
One dimension per request: Each call should analyze exactly ONE attribute dimension (e.g., scene words OR audience words). Do NOT request multiple dimensions in a single call.
| Field | API Name | Required | Description | Example |
|---|---|---|---|---|
| Analysis Request | tokenizationAndCountingRequest | Yes | Natural-language instruction describing which attribute dimension to extract from titles | "Count scene words in product titles" |
| Output Mode | outputMode | No | How multi-value attributes are returned. MULTIPLE_RECORDS (default): one record per value. COMMA_SEPARATED: all values in one record | MULTIPLE_RECORDS |
| Reference Data | refResultData | No | Externally supplied product data (only needed when referencing data from a previous conversation turn) | (JSON string) |
| Field | API Name | Description | Example |
|---|---|---|---|
| ASIN | asin | Product ASIN identifier | B0XXXXXXXX |
| Product Title | title | Original product title | Portable Camping Lantern... |
| Attribute Name | attributeName | Extracted attribute category | Scene Word |
| Attribute Value | attributeValue | Extracted attribute value | Outdoor / Camping |
| Price | price | Product price | 29.99 |
| Monthly Sales | monthlySalesUnits | Monthly unit sales | 1200 |
| Monthly Revenue | monthlySalesRevenue | Monthly sales revenue | 35988 |
| Rating | rating | Product rating | 4.5 |
| Rating Count | ratings | Number of ratings | 3820 |
| Available Date | availableDate | Listing date | 2024-03-15 |
| Brand | brand | Brand name | BrandX |
| Image URL | imageUrl | Main product image | https://... |
| Field | API Name | Description |
|---|---|---|
| Attribute Name | attributeName | The attribute category for this group (e.g., "Scene Word") |
| Attribute Value | attributeValue | A specific value within the group (e.g., "Outdoor") |
| Count | count | Number of products sharing this attribute value |
| ASIN List | asins | List of ASINs that share this attribute value |
| Field | API Name | Description |
|---|---|---|
| Render Type | type | UI rendering style |
| Columns | columns | Column definitions for table rendering |
| Source Type | sourceType | Data source type |
| Token Cost | costToken | Total LLM tokens consumed (input + output) |
The tokenizationAndCountingRequest parameter is a natural-language instruction telling the tool which dimension to analyze. Keep it focused on a single dimension.
Scene words (where / when the product is used)
Audience / target-user words (who the product is for)
Material words
Function / feature words
Incorrect -- multiple dimensions in one request (do NOT do this)
Split this into two separate calls instead.
| Value | Behavior | When to Use |
|---|---|---|
| MULTIPLE_RECORDS | Each attribute value becomes its own record (default) | Most analysis -- easier to count, sort, and group |
| COMMA_SEPARATED | Multiple values stay in one record, comma-separated | When you want to see all attributes per ASIN at a glance |
attributeGroups is returned, present the grouped summary before the per-product detailcostToken; do not display it unless the user asks about usage| User Says | Scenario |
|---|---|
| "What scene words appear in these titles?" | Scene-word extraction |
| "Analyze title keywords", "title word frequency" | General title tokenization |
| "What audience are these products targeting?" | Audience-word extraction |
| "Common materials in these listings" | Material-word extraction |
| "Help me optimize my title based on competitors" | Competitive title keyword analysis |
| "What words do top sellers use in titles?" | High-frequency keyword discovery |
| "Group these products by title attributes" | Attribute-based product grouping |
POST /product/titleAnalyze（完整参数/响应/错误码见 references/api.md）python scripts/title_analyze.py '<JSON 参数>' [--inline]输出策略（脚本默认行为）：
<cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-product-title-analyze-<timestamp>.json（<cwd> 为脚本执行时的工作目录，在 Claude Code 里即当前项目目录；<session> 取自环境变量 SESSION_ID，按用户任务自动聚合；禁止写入 /tmp，当前目录不可写则报错）total/costToken、最大列表字段的长度 + 前 3 条样本）--inline 强制全量打印到 stdout（同样落盘）读数据建议：先看摘要判断是否足够；需要具体字段时优先用 jq或ConvertFrom-Json 从保存的 json 文件按需抽取，避免整份 JSON 进入上下文。
发生以下异常情况时，采用 references/onboarding.md 引导解决问题：
LINKFOX_AGENT_API_KEY，也未配置 LINKFOXAGENT_API_KEY。按动态规则计费：消耗算力 = sum(所有被处理商品标题的(输入消耗的算力 + 输出结果消耗的算力))。
重要：本技能的服务按倍数动态计算，可能一次性消耗大量算力，必须提醒用户，由用户决定是否继续。