scrape-review-schema

Original：🇺🇸 English

Translated

3 scripts

Generate an HTML review page for schema and extracted data verification

1installs

Sourcezytedata/skills

Added on2026-09-02

NPX Install

npx skill4agent add zytedata/skills scrape-review-schema

SKILL.md Content

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You are generating a review page that lets the user verify the proposed schema and extracted values in their browser.

Read

${CLAUDE_SKILL_DIR}/../scrape/references/python-environments.md

.

Input

The raw argument string is

$ARGUMENTS

. Split it into up to 5 positional arguments. The 1st, 2nd and 4th are whitespace-separated tokens; the 3rd and 5th are JSON literals that may contain whitespace — recognize their boundaries by matching brackets (and strip outer single/double quotes if the caller quoted them):

spec_path: path to the spec folder, e.g.
```
.scrape/books-toscrape
```
work_path: path to the working directory, e.g.
```
.scrape/.work/books-toscrape
```
schema: JSON object literal with the proposed schema (starts with
```
{
```
, ends with the matching
```
}
```
)
html_variant: which HTML to use —
```
raw
```
or
```
rendered
```
changes (optional): JSON array literal of change descriptions from the previous round (starts with
```
[
```
, ends with the matching
```
]
```
), e.g.
```
["Re-analyzed price across all pages","Dropped field isbn"]
```

The schema JSON uses JSON Schema format (see

${CLAUDE_SKILL_DIR}/../scrape/references/extraction-spec.md

for full details):

json

{
  "type": "object",
  "properties": {
    "price": {
      "type": "string",
      "description": "Product price"
    }
  }
}

Fields may also carry a

source

annotation: "requested" (user asked for it) or "discovered" (AI found it).

Process

1. Read analysis data

List page subdirectories in

{spec_path}/pages/

(each subdirectory is a page). For each page, read

{spec_path}/pages/{page_id}/meta.json

for metadata and

{work_path}/analyze-page/{page_id}.{html_variant}.json

for analysis data.

2. Create temp directory

Create a temporary directory named

scrape-review-XXXXXX

(where

XXXXXX

is a random suffix). Keep track of the resulting path as

{review_dir}

and use it in subsequent steps.

3. Copy static assets

Copy the bundled assets from this skill's directory to the temp dir:

```
review.html
```
```
style.css
```
```
review.js
```

Use

${CLAUDE_SKILL_DIR}/assets/

as the source path.

4. Copy saved HTML pages

For each page directory in

{spec_path}/pages/

, copy the chosen variant's HTML to

{review_dir}/pages/{page_id}.html

:

bash

cp {spec_path}/pages/{page_id}/{html_variant}.html {review_dir}/pages/{page_id}.html

This flattens the directory structure for the review page's iframes.

5. Generate data.js

Build and write

{review_dir}/data.js

with all the data the review page needs. Use the literal placeholder

AGENT_PORT_PLACEHOLDER

for the port — the server replaces it after binding. If

changes

was passed (the optional 5th argument), include

REVIEW_CHANGES

so the page shows what the agent did:

javascript

const AGENT_URL = "http://127.0.0.1:AGENT_PORT_PLACEHOLDER/feedback";
const REVIEW_CHANGES = ["Re-analyzed price across all pages", "Dropped field isbn"];
const REVIEW_DATA = {
  fields: [
    {
      name: "price",
      type: "str",
      description: "Product price",
      source: "requested",
      values: {
        "detail-1": {"value": "$29.99", "url": "https://..."},
        "detail-2": {"value": "$49.99", "url": "https://..."}
      }
    }
  ],
  pages: {
    "detail-1": {
      url: "https://...",
      html_file: "pages/detail-1.html"
    }
  }
};

6. Open in browser and wait for feedback

Run exactly the command below and wait for it to finish before doing anything else: