← 返回 Skills 市场
linkfox-ai

Ehunt Temu Category Search

作者 linkfox-ai · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
30
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install linkfox-ehunt-temu-category-search
功能描述
通过 EHunt Temu 品类检索(网关路由 `ehunt/temu/temuCategorySearch`)在已同步到本地库的 EHunt Temu 类目数据中按关键词检索类目中文名、英文名与类目 id,用于商品/店铺筛选的类目 id。当用户提到 EHunt Temu 类目、Temu category id、...
使用说明 (SKILL.md)

EHunt Temu 类目检索(ehunt/temu/temuCategorySearch

在具备 LinkFox「第三方数据服务」MCP 时,对应网关路由 ehunt/temu/temuCategorySearch 调用(MCP 展示名:Temu 品类查询,确切工具名以当前环境下发的工具元数据为准)。数据来自 本地库检索

前置条件

库内须已有 ehunt/temu/syncTemuCategory(MCP 展示名:Temu 品类同步)写入的全量类目。若无数据或结果为空,应先完成同步再检索。

要点

  • 必填keyword(子串匹配类目中文名、英文名、类目 id)。
  • 分页page 从 1 起;pageSize 默认 50、最大 200。
  • 返回的 id / categoryId 可作为 Temu 商品查询的 categoryHome/categoryBackend、店铺查询的 category 等入参的类目标识(与具体工具 schema 一致即可)。

脚本(可选)

命令行调试:python scripts/ehunt_temu_category_search.py '\x3CJSON>'(需 LINKFOXAGENT_API_KEY)。详见 references/api.md 末尾。

参考

入参/出参表见 references/api.md

\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/ehunt_temu_category_search.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.

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 -->

安全使用建议
Install only if you are comfortable with a LinkFox credential-backed Temu lookup skill that includes a broad local response helper. Use the direct category-search script or MCP tool when possible, keep response output in a temporary directory, delete saved files after use, and do not use response_io.py with scripts or JSON files outside the intended task.
能力标签
requires-sensitive-credentials
能力评估
Purpose & Capability
The main Temu category search script is purpose-aligned: it posts keyword parameters to the LinkFox gateway using LINKFOXAGENT_API_KEY. The concern is the bundled response_io.py helper, which is generic and can execute any existing script path supplied to --script, exceeding a narrow category lookup capability.
Instruction Scope
The SKILL.md example points response_io.py at the bundled category-search script, but the helper itself does not enforce that scope. It also accepts arbitrary files for the read command, creating a broad local inspection utility not limited to files produced by this skill.
Install Mechanism
No package installation, persistence installer, startup hook, or dependency-fetching behavior was found. Metadata, static scan, and VirusTotal telemetry were clean.
Credentials
Use of LINKFOXAGENT_API_KEY and network access to the LinkFox tool gateway is expected for this integration. The script also permits base URL and route overrides via environment variables, so users should avoid untrusted overrides because the API key is sent in the Authorization header.
Persistence & Privilege
The large-response helper writes captured stdout to a user-selected directory and does not auto-delete it. The SKILL.md discloses this and warns not to commit sensitive output, but the behavior can still retain more data than needed, including failed or partial outputs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install linkfox-ehunt-temu-category-search
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /linkfox-ehunt-temu-category-search 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release
元数据
Slug linkfox-ehunt-temu-category-search
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Ehunt Temu Category Search 是什么?

通过 EHunt Temu 品类检索(网关路由 `ehunt/temu/temuCategorySearch`)在已同步到本地库的 EHunt Temu 类目数据中按关键词检索类目中文名、英文名与类目 id,用于商品/店铺筛选的类目 id。当用户提到 EHunt Temu 类目、Temu category id、... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 30 次。

如何安装 Ehunt Temu Category Search?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install linkfox-ehunt-temu-category-search」即可一键安装,无需额外配置。

Ehunt Temu Category Search 是免费的吗?

是的,Ehunt Temu Category Search 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Ehunt Temu Category Search 支持哪些平台?

Ehunt Temu Category Search 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ehunt Temu Category Search?

由 linkfox-ai(@linkfox-ai)开发并维护,当前版本 v1.0.0。

💬 留言讨论