startup_website_import · git:20260907.65e4374 · 2026-09-07 · sha256 fbca6734ad9483ae
startup_website_import git:20260907.65e4374A
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--- name: startup_website_import description: Import a startup website as Markdown pages and linked PDFs into its dataset. Use for an explicit public-website crawl. --- # Startup website import Collect website source material for later dataset ingestion. ## Operations and effects The synchronous `startup_website_import(startup_name, url, ...)` returns `WebsiteImportResult` with paths and counts, not insight artifacts. It creates the dossier without activating it, then stages the crawl before replacing `datasets/website/`. The crawler queues same-host links, excludes configured low-value path segments, and defaults to depth 1 and 50 HTML pages. PDFs default to enabled, with 20 files and 25 MB per file. Robots rules are used when available; failure to load them does not stop the crawl. Requests follow normal HTTP redirects. Save Markdown pages with source metadata, PDFs under `website/pdfs/`, plus `linkedin-urls.md` and `linkedin-and-resume-links.md`. These are discovered links and possible-resume hints, not verified person identities. Failed pages/PDFs are logged and skipped. Zero saved HTML pages raises and leaves the existing website snapshot intact. Once a crawl succeeds, replacement removes the old directory before copying staged files; this copy is not transactional. Other dossier data is retained. There is no indexing, profile generation or LinkedIn enrichment, and no harness/bulk registration. ## Usage ```bash conda run -n sictic-env python -m skills.startup_website_import example https://example.org --depth 1 ``` The direct CLI takes positional `STARTUP` and `URL` arguments and exposes `--depth`, `--max-pages`, `--pdfs/--no-pdfs`, `--max-pdfs`, `--max-pdf-mb` and `--respect-robots/--ignore-robots`. ## References - [Implementation](startup_website_import.py), [CLI](__main__.py) - [Dataset paths and storage](../standards_and_architecture/SKILL.md#datasets-and-storage)