Web Scrape To Md

Web Scrape to Markdown

Purpose

Collect high-signal website content into local markdown files using WebSearch and WebFetch — markdown-first, goal-aligned extraction, minimal token waste.

Not this skill:

• Site inventory only — use [Site Content Catalog](../../marketing/skills/site-content-catalog/) for URL lists, page_type labels, and SEO signals without full content extraction.
• Batch reproducible crawls — use a dedicated scraper CLI when you need raw/, manifest.jsonl, or resume logic at hundreds of URLs.
• Live SERP scoring — use [Information Gain Evaluator](../../marketing/skills/information-gain-evaluator/) for citation-fit analysis.

Reference: REFERENCE.md · Examples: EXAMPLES.md

Input policy (non-negotiable)

• Domain or URL list — from the user only. Never infer from workspace, examples, or prior runs.
• Goal — from the user (audit, research, brief, competitor analysis, corpus). If missing, ask once.
• Coverage target — user number or default 10 pages.
• Output directory — user path when saving files; if omitted, return handoff + page markdown in chat only.

If missing domain/URLs, ask once:

> Which domain or URLs should I scrape? What is the goal, and how many pages should I target? (Optional: output folder path.)

Modes

| Mode | When | Output | |------|------|--------| | corpusrun | User wants local .md files | Per-page files + INDEX.md + handoff JSON | | summaryonly | Quick triage, no files | Handoff JSON + run summary in chat |

Completion criterion for mode: handoff.mode matches what you did; corpus_files[] populated only in corpus_run.

Quick start

1. Confirm domain/URLs, goal, coverage target, mode, optional output_dir.
2. Step 1 — markdown-first discovery + sitemap/blog fallbacks (REFERENCE.md).
3. Step 1b — freshness pass when goal requires recent posts (REFERENCE.md § Freshness).
4. Step 2 — curate URL set with intent + source tags.
5. Step 3 — fetch with WebFetch tactics; batch parallel independent URLs.
6. Step 4 — write page markdown per template; assess quality (Q-layer).
7. Step 5 — emit handoff JSON v1.1 + INDEX.md when corpus_run.

Workflow

Web Scrape to MD Progress
- [ ] Step 1: Markdown-first discovery (+ sitemap/blog fallbacks)
- [ ] Step 1b: Freshness pass (when goal requires)
- [ ] Step 2: URL curation
- [ ] Step 3: Fetch (efficient, parallel)
- [ ] Step 4: Page markdown + quality pass
- [ ] Step 5: Handoff + INDEX

Step 1 — Markdown-first discovery

Before bulk HTML page fetches:

1. WebFetch in order: /llms.txt, /llms-full.txt, /llms.md, /sitemap.xml.
2. Record discovery_summary.llms_endpoints_checked: true and sitemap_root_status (ok | http_error | missing).
3. Sitemap root failure — if /sitemap.xml returns HTTP error, try child sitemaps from node scripts/wp-sitemap-fallback.mjs --domain (REFERENCE.md § Sitemap fallback).
4. llms.txt blog/archive links — when llms lists a blog or content archive URL, fetch that index for child post links even though other archive indexes are normally excluded (REFERENCE.md § llms archive rule).
5. Blog archive fallback — when root + child sitemaps fail or omit posts, fetch archive URLs: llms-seeded archive links first, then blogArchiveCandidates(domain, seeds) (REFERENCE.md).
6. WebSearch only when llms, sitemap, and archive passes still leave gaps.

Completion criterion: sitemap_child_urls_tried[] populated when root sitemap failed; llms-seeded archive URLs fetched for discovery when present.

Step 1b — Freshness pass (when required)

Set discovery_summary.freshness_goal: true when the goal mentions blog, articles, corpus, research, content, publish, recent, or latest (scripts/wp-sitemap-fallback.mjs goalNeedsFreshness()).

When freshness_goal is true:

1. Prefer newest posts from child post sitemap `` order or archive index (top 3 by default).
2. Archive link extraction — on each archive index fetch, run extractArchivePostUrls() on the raw response (REFERENCE.md § Archive link extraction). Use discovered hrefs before any slug guessing.
3. Add discovered post URLs to recent_posts_discovered[] and the curated fetch set.
4. Do not skip the archive index solely as "low-signal" when freshness is required.
5. Slug recovery (last resort only) — when link extraction finds teasers but no URLs (REFERENCE.md § Slug recovery):

• Derive pathPrefix from blog_archive_url via blogPathPrefixFromArchiveUrl() — never hardcode a site path.
• Run slugCandidatesFromTeaser() and postUrlsFromSlugs(domain, candidates, pathPrefix).
• If slug attempts fail, WebSearch with the exact teaser sentence in quotes.

Completion criterion: recent_posts_discovered[] lists every post visible on the archive index; unresolved only after link extraction + slug candidates + exact-title search.

Step 2 — URL curation

• Dedupe URLs; tag source and intent (REFERENCE.md).
• Exclude tag/author archives, auth/checkout, faceted noise — except llms-seeded blog indexes and URLs needed for freshness_goal.
• Trim to coverage target — highest-signal URLs first; include newest posts when freshness_goal.

Completion criterion: every planned fetch URL has source_tag + intent; completed_total equals curated attempt count.

Step 3 — Fetch (efficient, parallel)

Apply REFERENCE.md § WebFetch:

• Batch independent URLs in parallel WebFetch calls; retry individually if a batch times out.
• Follow redirects; store final_url.
• Prefer markdown page variants when llms or sitemap hints allow.
• Set fetch_format per page fetch only (markdown | html).
• Status: ok | http_error | blocked_or_empty | unresolved (after one retry + alternative path).

Completion criterion: each url_results[] row has status, fetch_format when ok, and final_url when ok.

Step 4 — Page markdown + quality pass

For corpus_run, one file per page ({slug}.md) using REFERENCE.md template.

• Extract for the declared goal — not full page dumps.
• Q-layer checklist in REFERENCE.md.
• Cap ~80–120 lines per page unless user requests full capture.
• Prefer post body files over archive index files when coverage is tight — document discovery in limitations[] instead of a dedicated archive-index corpus file unless the user asks for one.

Completion criterion: every ok URL in corpus_run has a corpus_files[] entry passing Q-layer; archive post URLs extracted before slug recovery when freshness applies.

Step 5 — Handoff + INDEX

Emit handoff JSON v1.1 (REFERENCE.md). Reconcile counts:

• completed_ok = count of url_results with status: ok
• completed_total = url_results.length
• markdown_direct_count / html_fallback_count = ok page fetches by fetch_format only (not llms.txt discovery)

For corpus_run, write INDEX.md. Every recommended_keep URL should appear in successful url_results or be documented in limitations[].

Return in chat: attempted vs succeeded, efficiency summary, keep/drop, next step.

Decision rules

• WebSearch/WebFetch default for quick and medium runs.
• Skip extra search rounds when llms + sitemap + archive already map the goal-aligned set.
• Never skip an llms.txt Blog/archive link without fetching it once for child URLs.
• Escalate to programmatic scraping only for large page counts, resume needs, or explicit batch artifact requests.
• Do not claim full-site coverage unless planned URL classes were attempted.

Quality guardrails

• Separate found URL from successfully fetched content.
• Do not treat discovery snippets as page body.
• If a URL fails twice, mark unresolved and document one alternative in limitations[].

Ship bar (regression)

node scripts/verify-handoff.mjs
node scripts/verify-scorecard.mjs
node scripts/wp-sitemap-fallback.mjs --domain example.com

Golden fixtures: examples/example-saas.handoff.fixture.json, examples/example-sitemap-fail.handoff.fixture.json. See examples/SCORECARD-example-saas.md.

Done definition

• [ ] User inputs echoed in handoff.inputs — no invented domain
• [ ] llms_endpoints_checked true; sitemap_root_status recorded
• [ ] Sitemap root HTTP error → child sitemaps tried and/or blog archive fetched
• [ ] Archive fetch → extractArchivePostUrls() on raw response before slug recovery
• [ ] Every curated URL in url_results[]; counts reconciled (completed_ok, format counts)
• [ ] markdown_direct_count counts page fetches only — not llms.txt
• [ ] corpus_run: each ok URL has corpus file meeting Q-layer
• [ ] Child verifiers exit 0 on golden fixtures

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Roots-and-Fruit
• Source: Roots-and-Fruit/skills
• License: MIT

Install and usage instructions live in the source repository linked above.