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crw-crawl

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Crawl an entire website or section and extract content from every page. Use when you need content from many pages under a common URL prefix: "crawl the whole site", "get all docs pages", "scrape every blog post", "download the full docs for RAG", "extract all pages under /api". Async BFS — starts a job and polls for results. Step 4 of the crw workflow ladder.

QUICK START

How to use this skill

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  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
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Source SKILL.md: https://github.com/us/crw/blob/HEAD/skills/crw-crawl/SKILL.md

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Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

crw-crawl — bulk page extraction

When to use

  • You need content from many pages under a site or section, not just one.
  • Step 4 in the crw ladder: if you only need a handful of known URLs, use crw-scrape in a loop instead — it's simpler and gives you content immediately. Use crawl when the set of URLs is unknown or large.
  • Always map first (crw-map) to estimate page count before committing. A misconfigured crawl on a 50 000-page site is expensive; a map call is cheap.
  • Start conservative: depth 1, limit 10. Scale up once you verify scope.

Quick start

CLI (synchronous streaming output):

crw crawl "https://docs.example.com" -d 2 -l 50         # markdown to stdout
crw crawl "https://docs.example.com/api" -d 1 -l 20 --format json
crw crawl "https://example.com" --js --rate-limit 1.0 --concurrency 3

MCP (async — returns a job ID, poll for results):

# Start the crawl
crw_crawl(url="https://docs.example.com", maxDepth=2, maxPages=50)
→ { "id": "a1b2c3d4-..." }

# Poll until status == "completed"
crw_check_crawl_status(id="a1b2c3d4-...")
→ { "status": "scraping|completed|failed", "data": [...] }

REST (async — POST to start, GET to poll, DELETE to cancel):

# Start
curl -X POST "$CRW_API_URL/v1/crawl" -H "Authorization: Bearer $CRW_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"url":"https://docs.example.com","maxDepth":2,"maxPages":50}'
# → {"id":"a1b2c3d4-..."}

# Poll
curl "$CRW_API_URL/v1/crawl/a1b2c3d4-..." \
  -H "Authorization: Bearer $CRW_API_KEY"
# → {"status":"completed","data":[...]}

# Cancel
curl -X DELETE "$CRW_API_URL/v1/crawl/a1b2c3d4-..." \
  -H "Authorization: Bearer $CRW_API_KEY"

Options

NeedCLI flagMCP / REST field
Max depth-d/--depth N (default 2)maxDepth (default 2)
Max pages-l/--limit N (default 10)maxPages
Output format--format markdown|json|html|rawhtml|text|links—
Structured JSON per page—jsonSchema: {...}
JS rendering--jsrenderJs: true (null = auto)
Wait after load—waitFor: 2000 (ms)
Renderer override—renderer: "lightpanda|chrome|playwright"
Rate limit--rate-limit N (default 2.0 req/s)—
Concurrency--concurrency N (default 5)—
Per-page timeout--timeout MS (default 30 000)—
Proxy--proxy URL—
Stealth mode--stealth—
Strip nav/footer(on by default; --raw to disable)—

Polling loop (MCP / REST)

The MCP and REST crawl is async. Poll crw_check_crawl_status (MCP) or GET /v1/crawl/{id} (REST) every few seconds. The job expires after 1 hour.

loop:
  status = crw_check_crawl_status(id=job_id)
  if status.status == "completed":  break
  if status.status == "failed":     raise error
  wait(3s)

pages = status.data   # list of {url, markdown, html, links, metadata, ...}

MCP truncates each page's content to ~15 000 chars by default. Pass maxLength: 0 to opt out.

Saving crawl output to local files

Never stream a whole crawl into model context. Write pages to .crw/ and read incrementally.

CLI (streams pages as they arrive — redirect or tee):

crw crawl "https://docs.example.com" -d 2 -l 100 \
  --format json > .crw/crawl-raw.jsonl

# One markdown file per page from the JSON lines
grep '^{' .crw/crawl-raw.jsonl | jq -r '"\(.metadata.sourceURL)\n\(.markdown)"' \
  | split - .crw/pages/page-

MCP / REST (after polling completes):

# REST: save the full result
curl "$CRW_API_URL/v1/crawl/$JOB_ID" -H "Authorization: Bearer $CRW_API_KEY" \
  | jq -c '.data[]' > .crw/pages.jsonl

# Write one .md per page
jq -r '.markdown' .crw/pages.jsonl | split -l 1 - .crw/pages/page-

Then grep, head, or pass individual files to the model — never the whole blob.

Recommended workflow

1. crw map  "https://docs.example.com" --format json > .crw/urls.json
             → see how many pages exist (check last line: "Discovered N URLs")

2. crw crawl "https://docs.example.com/api" -d 1 -l 20
             → start narrow, verify output quality

3. Scale up: -l 100, -d 2, or scope to a sub-path if needed

4. Write to .crw/, read with grep/jq

Tips

  • Map first. crw map docs.example.com | wc -l in 3 seconds beats a cancelled 10-minute crawl.
  • Start at depth 1, limit 10. Confirm you're in the right section before widening scope. Most docs sets are fully reachable at depth 2-3.
  • JS auto-detects. crw's renderer fallback handles most SPAs without --js. Add it only if you see blank pages or loading skeletons.
  • Rate-limit aggressively for production sites. Default 2 req/s is polite; drop to 0.5 on fragile targets. --concurrency 2 + --rate-limit 0.5 is a safe baseline for external sites.
  • jsonSchema turns every page into a typed object. Pass a JSON schema via MCP/REST to extract structured data from every crawled page — useful for price monitoring, job listings, or any repeating schema.
  • Building a knowledge base? Load crw-knowledge-base (coming soon) — it wraps the crawl → chunk → embed → index pipeline end-to-end.

See also

  • crw-map — discover URLs before crawling
  • crw-scrape — single-page extraction (faster for known URLs)
  • crw — hub skill with the full workflow ladder