cp-skill-snapshot-web

SkillDocs & knowledge

Snapshot a URL into the local kb/sources/.snapshots/ cache, routing GitHub, X/Twitter, PDF, and ordinary web sources to the appropriate capture path.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the cp-skill-snapshot-web skill

What this skill tells your AI

The instructions your AI receives, as published by zby/commonplace in kb/instructions/cp-skill-snapshot-web/SKILL.md and read by ahel’s review.

EXECUTE NOW

Target: $ARGUMENTS

If no URL provided, ask the user for one.

If URL provided, start Step 1 immediately.

START NOW.


Step 1: Verify Local Storage and Check for Duplicates

Keep the provided URL as source_url. Verify that kb/sources/.snapshots/ is ignored by the project. The shipped scaffold does this through kb/sources/.gitignore. If the directory is not ignored, stop before writing and report the missing rule.

Use Grep to search for an exact frontmatter source: {source_url} in existing Markdown files in kb/sources/.snapshots/. If found, compute the SHA-256 of the exact file bytes, tell the user, and stop:

Already snapshotted: kb/sources/.snapshots/{filename} SHA-256: {64-character lowercase checksum}

Step 2: Route by URL Type

Detect the source_url type and branch:

  • GitHub issue/PR (github.com/.../issues/N or github.com/.../pull/N) → Step 2a
  • X/Twitter (x.com/.../status/... or twitter.com/.../status/...) → Step 2b
  • arXiv abstract page (arxiv.org/abs/...) → Step 2c
  • PDF (URL ends in .pdf, or arxiv.org/pdf/) → Step 2c
  • Everything elseStep 2d

Step 2a: GitHub Issue/PR

Run:

commonplace-github-snapshot "{source_url}"

Parse either the Snapshot saved: or Already snapshotted: line from the output to get the file path. Tell the user and stop — the script handles metadata, formatting, and saving.

Step 2b: X/Twitter Post

Run:

commonplace-x-snapshot "{source_url}"

Parse either the Snapshot saved: or Already snapshotted: line from the output to get the file path. Tell the user and stop — the script handles metadata, formatting, and saving.

Step 2c: Resolve and Fetch PDF

Verify that the PDF capture prerequisites are available:

command -v curl
command -v pdfinfo
command -v pdftotext

If any command is missing, go to Step 3. Do not probe for an alternative converter.

Set pdf_url:

  • For an arXiv abstract URL, replace /abs/ with /pdf/ and discard any query string or fragment. Preserve an explicit terminal version such as v1. If the abstract URL has no terminal version, leave the PDF URL unversioned so arXiv serves the latest paper version. For example, https://arxiv.org/abs/2606.03979 becomes https://arxiv.org/pdf/2606.03979. Do not route the abstract page through ordinary HTML capture.
  • For an existing PDF URL, use source_url unchanged.

Run this as one Bash invocation. Retain the printed directory path as {snapshot_tmp}:

set -e
snapshot_tmp=$(mktemp -d)
printf 'Snapshot temp: %s\n' "$snapshot_tmp"
curl -fsSL -o "$snapshot_tmp/source.pdf" "{pdf_url}"
pdfinfo -isodates "$snapshot_tmp/source.pdf" > "$snapshot_tmp/pdfinfo.txt"
pdfinfo -meta "$snapshot_tmp/source.pdf" > "$snapshot_tmp/pdfmeta.xml" || true
pdftotext -enc UTF-8 -eol unix -nopgbrk \
  "$snapshot_tmp/source.pdf" "$snapshot_tmp/extracted.txt"

Use Read to inspect pdfinfo.txt, non-empty pdfmeta.xml, and a bounded beginning of extracted.txt. DOI metadata inspection is best effort and its failure does not make an otherwise successful capture fail. Treat PDF metadata fields as leads, not as authority: confirm the title and authors against the document text when available. Use Grep plus bounded Read ranges to locate an abstract, executive summary, introduction, or the source document's own DOI when the beginning does not supply enough metadata. Do not treat a DOI found only in the references as the paper's DOI. Do not read the whole extracted file merely to copy it. If extracted.txt is empty or contains no substantive text, go to Step 3.

Set capture_method to pdftotext, set body_file to {snapshot_tmp}/extracted.txt, and go to Step 4.

Step 2d: Fetch Web Page

Verify that the HTML capture prerequisites are available:

command -v trafilatura

If the command is missing, go to Step 3. Do not probe for another HTML converter.

Run this as one Bash invocation to download and extract the page. Retain the printed directory path as {snapshot_tmp}:

set -e
snapshot_tmp=$(mktemp -d)
printf 'Snapshot temp: %s\n' "$snapshot_tmp"
trafilatura -u "{source_url}" \
  --markdown --with-metadata --links --no-comments --recall \
  --backup-dir "$snapshot_tmp/raw" \
  > "$snapshot_tmp/extracted.md"

Use Read to inspect only the leading metadata and a bounded beginning of extracted.md. Its leading YAML block, when present, is Trafilatura metadata: retain it as input to Step 4 but do not copy that block into the snapshot body. Trafilatura also retains its downloaded HTML as a gzip file under {snapshot_tmp}/raw/. When gzip is available, decompress that file within {snapshot_tmp} and use Grep with bounded output to inspect article-level DOI metadata such as citation_doi, dc.identifier, prism.doi, or a JSON-LD doi property. DOI inspection is best effort: inability to inspect the raw HTML does not make an otherwise successful capture fail. Strip that block locally without re-emitting the document:

awk '
NR == 1 && $0 == "---" { in_metadata = 1; next }
in_metadata && $0 == "---" { in_metadata = 0; next }
!in_metadata { print }
' "{snapshot_tmp}/extracted.md" > "{snapshot_tmp}/body.md"

If body.md is empty or contains no substantive main content, go to Step 3.

Set capture_method to trafilatura, set body_file to {snapshot_tmp}/body.md, and go to Step 4.

Step 3: Handle Failures

If any fetch or extraction method fails (missing prerequisite, curl error, empty Trafilatura result, or PDF with no embedded text):

  • Tell the user exactly what happened.
  • For a missing prerequisite, name the canonical installation:
    • trafilatura: uv tool install "trafilatura>=2.2"
    • pdfinfo or pdftotext: install Poppler (poppler-utils on Debian/Ubuntu, poppler through Homebrew, or oschwartz10612.Poppler through WinGet)
    • curl: install curl
  • For an image-only PDF, say that this workflow has no OCR fallback.
  • Suggest they paste the content manually: "You can paste the text and I'll save it as a snapshot"
  • Remove {snapshot_tmp} if one was created.
  • Stop.

Step 4: Determine Metadata

(Only for PDF and web page paths — GitHub and X scripts handle their own metadata.)

This workflow supplies kb/sources/types/snapshot.md as the type. Open that path and verify from its own frontmatter that it is a type spec before determining metadata. Stop if it is missing or invalid.

From the bounded excerpts, extractor metadata, and source_url, determine:

  • title: The article/post title. Use the first H1 if present, otherwise derive from content.
  • author: If identifiable from the content or URL (e.g. simonwillison.net → Simon Willison)
  • doi: For a scholarly article or paper, try to identify the DOI from the source_url, extractor or document metadata, and the document's own title or citation block. Store the bare identifier beginning with 10.; remove a leading https://doi.org/ or doi: label and surrounding whitespace. Accept a candidate only when the source identifies it as the DOI of the captured work. A DOI found only in references is not sufficient. If candidates conflict or none is attributable to the captured work, omit doi; never guess or manufacture one.
  • genre: the source's genre per the snapshot type spec's vocabulary. This is a surface judgment of what kind of document the source is as evidence — ingestion may correct it later. Prefer a value from the type spec's list; a value outside it validates with a warning, so extend only for a genuinely new evidential kind, not a container.
  • capture_scope: full-source, partial-source, abstract, or excerpt under the snapshot type contract. Judge the retained body, not the success of the extraction command. In particular, label a publisher page that exposes only an abstract as abstract, even when that abstract is substantive.
  • description: One sentence describing what makes this source worth retrieving. Not a summary — a retrieval filter (e.g. "Anthropic CEO's capability-timeline predictions — verifiable domains get confident timelines, unverifiable ones get hedged"). Focus on what distinguishes this source from others on the same topic.
  • slug: Lowercase, hyphenated, max 63 chars. The paired ingest adds .ingest to the validated stem, so the snapshot basename must reserve those seven characters within the 70-character authored-artifact limit. Derive it from the title. Example: simon-willison-karpathy-claws.

For academic papers: prefer the title and complete author list printed in the paper over pdfinfo or Trafilatura metadata.

Step 5: Materialize the Snapshot

The extracted body must move from body_file to the snapshot through local byte copying. Never place the whole source body in a Write or Edit call.

Use Write to create {snapshot_tmp}/header.md with this content and no source body. End the file with the blank line after Date:

---
source: {source_url}
description: {description}
captured: "{YYYY-MM-DD}"
capture: {capture_method}
capture_scope: {capture_scope}
genre: {genre}
doi: "{bare DOI; omit this line when no DOI was verified}"
type: kb/sources/types/snapshot.md
---

# {title}

Author: {author}
Source: {source_url}
DOI: {bare DOI; omit this line when no DOI was verified}
Date: {publication date if known}

Trafilatura has already produced the web body as Markdown. A PDF body remains the complete plain text emitted by pdftotext; plain text is valid Markdown. Do not make model-mediated PDF cleanup a condition of capture. If the user explicitly requested cleanup, transform bounded chunks into a candidate body, never send the whole document through one Write, and retain the raw extracted.txt as fallback. Set body_file to the candidate only after every source chunk is present and in order; otherwise keep the raw body.

Assemble the snapshot without sending the extracted bytes through model output:

set -e
snapshot_path="kb/sources/.snapshots/{slug}.md"
cp "{snapshot_tmp}/header.md" "$snapshot_path"
cat "{body_file}" >> "$snapshot_path"
header_bytes=$(wc -c < "{snapshot_tmp}/header.md")
body_bytes=$(wc -c < "{body_file}")
snapshot_bytes=$(wc -c < "$snapshot_path")
test "$snapshot_bytes" -eq "$((header_bytes + body_bytes))"

Compute SHA-256 after the file is complete. Hash the exact .md bytes, including frontmatter, line endings, and the presence or absence of a final newline. Do not include a PDF, JSON, image, or other capture companion. Tell the user where the snapshot was saved, its lowercase checksum, and a one- or two-line preview.

Critical Constraints

Never:

  • Fabricate or hallucinate content not on the page
  • Add analysis or commentary — this is capture, not ingestion
  • Re-emit a complete extracted body through Write or Edit
  • Make model-mediated cleanup a prerequisite for saving a snapshot
  • Save to any directory other than kb/sources/.snapshots/
  • Install software — if a required tool is missing, bail with an error telling the user what to install

Always:

  • Copy every body_file byte in order on the default capture path
  • Include the source URL in frontmatter
  • Use today's date for captured
  • Check for duplicates before fetching
  • Keep the snapshot and every capture companion local and ignored
  • Remove the unique temporary download/extraction directory after the snapshot is written and hashed

Signals

GitHub stars
88
Forks
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Last commit
Sep 2026
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Catalog kind
skill
Gateway key
cp-skill-snapshot-web
Source
github.com/zby/commonplace