alirezarezvani--claude-skills/docs/commands/cs-scrape.md

title, description

title	description
/cs-scrape — Slash Command for AI Coding Agents	Route, extract, and validate a scraping job (URL or local file) via the universal-scraping-architect skill — refuses to deliver unvalidated data.. Slash command for Claude Code, Codex CLI, Gemini CLI.

/cs-scrape

:material-console: Slash Command :material-github: Source

Run a gated extraction pipeline for $ARGUMENTS using skills/universal-scraping-architect/SKILL.md.

Pre-flight gates (stop if any fails)

1. Target stated? If $ARGUMENTS is empty, ask for the URL or file path plus the desired output format — do not guess.
2. Live-site etiquette: for URLs, check robots.txt and plan rate limits; refuse disallowed targets.
3. Privacy: if the target is a local/sensitive file, do not send it to an external API — force Mode 2 (local Python).
4. Secrets: Firecrawl key only via os.getenv('FIRECRAWL_API_KEY'); if a key appears inline anywhere, fix that first.

Workflow

1. Route — state the mode and why (per the skill's routing rules): Mode 1 Firecrawl (public/JS-heavy URL, bulk crawl) · Mode 2 local Python (local files, private data, simple static HTML) · Mode 3 hybrid (Firecrawl extract + pandas clean).

2. Budget — estimate API quota / token limits before multi-page jobs; add checkpointing + pagination.

3. Extract — start from the matching runner template (run from the plugin root; --sample previews the summary shape offline):

   python3 skills/universal-scraping-architect/scripts/firecrawl_example.py --sample
   python3 skills/universal-scraping-architect/scripts/local_bs4_example.py --sample
   

4. Validate (mandatory, exit-code gated):

   python3 skills/universal-scraping-architect/scripts/validate_extraction.py extracted_output.json --json
   

   • exit 0 (status: ok) → continue
   • exit 1 (warning = empty output, error = malformed JSON) → fix and re-extract; never deliver unvalidated data

   Then check required fields and duplicates against the job spec.

5. Deliver — CSV (tabular) / JSON (nested) / Markdown (docs, chunked), per the user's requested format, with a summary of mode chosen, row counts, empty values, and the validation verdict.