xiaohongshu-search

Files (2)

• SKILL.md
• extract-search.py · scripts/

SKILL.md (first lines)

# Xiaohongshu — Search Notes

> keyword → list of notes with title, author, engagement stats, xsecToken

## Language

All process output to user (progress updates, process notifications) follows the user's language.

## Objective

Search Xiaohongshu notes by keyword and extract the result list including engagement metrics and tokens for downstream detail lookup.

## Prerequisites

- Browser opened to `https://www.xiaohongshu.com/search_result/?keyword={keyword}`
- User is logged in (avatar or username visible in the left sidebar)

## Pre-execution Checks

### 1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke `browser-act` via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

### 2. Login Verification

If login status for Xiaohongshu has been confirmed in the current session → skip this step.

Otherwise: open `https://www.xiaohongshu.com` and observe the left sidebar:
- User avatar or "Me" entry visible → logged in, continue execution
- "Login" button visible → not logged in, inform the user that login is required, use `remote-assist` to let the user scan the QR code

User refuses or cannot log in → terminate execution.

## Capability Components

> This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. Its role is equivalent to copy-pasting on the user's behalf — the data is already on screen, automation merely saves time. JS code is encapsulated in Python files under the `scripts/` directory, invoked via `eval "$(python scripts/xxx.py {params})"`. `$(...)` is bash syntax; it is recommended to use the bash tool for execution.

Below are all atomic capabilities discovered and verified during the exploration phase, listed by command template with parameters. Simply invoke them as needed — no need to read `scripts/*.py` source code or re-verify. Only inspect scripts when execution fails for troubleshooting. Combine freely as needed during execution.

### DOM: extract search results

Navigate to the search page (business parameters injected via URL), wait for the Vue SSR state to populate, then extract from `window.__INITIAL_STATE__.search.feeds`:

1. `navigate https://www.xiaohongshu.com/search_result/?keyword={keyword}`
2. `wait stable`
3. (optional) apply filters — see AI Workflow below
4. `eval "$(python scripts/extract-search.py --limit {limit})"`

Parameters:
- `{keyword}`: URL-encoded search keyword (e.g., `travel`, `coffee`)
- `--limit`: max items to return from current feeds buffer, default `20`

Output example:
```json
{
  "total": 44,
  "hasMore": true,
  "page": 2,
  "items": [
    {
      "id": "69d8cd8c0000000022002295",
      "xsecToken": "ABpK6gG0Dmt6MoVt60wJf-J0VMaCw5Y1Hi766ap7uWrxE=",
      "type": "normal",
      "title": "Not Switzerland! This is a natural grassland in Fujian!!",
      "userId": "5bac4e3f7a4c7300016a6b88",
      "nickname": "half-goose",
      "likedCount": "5149",       // likes
      "collectedCount": "4170",   // collects/saves
      "commentCount": "390",      // comments
      "coverUrl": "https://sns-..."
    }
  ]
}
```

Error handling: if `error: true` is returned, verify the page URL is a search result page and `wait stable` has completed before retrying.

### AI Workflow: apply sort and note-type filters (before extraction)

Run this workflow before the extraction step when the user specifies a sort order or note type. Uses the filter panel on the search result page:

1. `state` — locate the "Filter" button in the top-right area of the search content area → `click <index>`
2. Wait for filter panel to appear (visible on the right side of the page)
3. For **sort order** — `state` locate the desired sort tag in the "Sort By" row → `click <index>`

   | UI Label | filterParams value |
   |---|---|
   | General (default) | `general` |
   | Latest | `time_descending` |
   | Most Liked | `popularity_descending` |
   | Most Commented | `comment_descending` |
   | Most Collected | `collect_descending` |

4. For **note type** — `state` locate the desired type tag in the "Note Type" row → `click <index>`

   | UI Label | filterParams value |
   |---|---|
   | All (default) | — |
   | Video | `video-note` (site internal) |
   | Image-text | `image-text-note` (site internal) |

5. `state` locate the "Collapse" button at the bottom of the filter panel → `click <index>`
6. `wait stable`
7. Then run: `eval "$(python scripts/extract-search.py --limit {limit})"`

## Enum Parameters

[AI] sort — filterParams.tags[0] value for the sort_type filter. Acquisition: open filter panel via `state` + `click`, read "Sort By" row options. Verified values: `general`, `time_descending`, `popularity_descending`, `comment_descending`, `collect_descending`.

[AI] note_type — filterParams.tags[0] value for the filter_note_type filter. Acquisition: open filter panel via `state` + `click`, read "Note Type" row options. Verified values: video-note type (obtained by clicking "Video" option), image-text-note type (obtained by clicking "Image-text" option).

time_filter [collection failed]: time filter API parameter value not captured — UI interaction applies filter but POST body parameter mapping was not observed.

## Pagination

**DOM Pagination**: `scroll down --amount 3000` → `wait stable` → re-run `eval "$(python scripts/extract-search.py --limit {limit})"`. Each scroll loads ~20 more results into `feeds`. Termination: `hasMore: false` in extraction output.

From browser-act/skills, MIT.

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