agentleFS
hranesshraness/atet/.agents/skills/save-pdf-kb/SKILL.md

save-pdf-kb

Skill7 starsChanged 48 days agoMITView on GitHub

Convert a local or public remote PDF into an auditable Markdown knowledge-base bundle with the original document, inferred headings, page provenance, OCR text, image metadata, and local visual assets. Use when the user asks to save, import, archive, extract, or turn a PDF into KB Markdown, especially scanned documents and PDFs containing screenshots, Slack messages, charts, photos, or a mix of native text and images.

4 other projects use a version of this, 1 of them edited.

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Most recently taken up by

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 5 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use the installed wordcell CLI.

    line 16
  2. Distinctive:

    Check the local conversion routes, then capture the PDF:

    line 20
  3. Distinctive:

    Treat native PDF text and image text as two independent extraction surfaces.

    line 56
  4. Distinctive:

    Use only IDs and SHA-256 values from the first manifest.

    line 97
  5. Very specific:

    Use complete only when every page was processed and every extracted image was classified.

    line 117
  6. Distinctive:

    Check that source-image links accompany OCR-derived text.

    line 128
  7. Distinctive:

    After adding or linking the capture, run the vault's normal refresh and check:

    line 132

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Save a PDF to the knowledge base

Use the installed wordcell CLI. Resolve <vault> to the directory containing its authored or managed index.md front door, then set the shell-local KB_ROOT to that path (KB_ROOT=kb from a typical repository root).

Check the local conversion routes, then capture the PDF:

wordcell doctor
wordcell pdf "/absolute/path/to/document.pdf" --output "$KB_ROOT/articles"
wordcell pdf "https://example.com/document.pdf" --output "$KB_ROOT/articles"

Pass a stable slug or replace a prior tool-owned bundle only when needed:

wordcell pdf "/absolute/path/to/document.pdf" --slug ben-leaves-zo --output "$KB_ROOT/articles"
wordcell pdf "/absolute/path/to/document.pdf" --output "$KB_ROOT/articles" --force

The command installs one atomic bundle:

<slug>/
  <slug>.md
  capture.json
  source.pdf
  annotations.json  # present after a reviewed annotation pass
  assets/

source.pdf is the byte-identical input. The manifest records its original name, hash, byte count, page count, bounded document metadata, processed-page and block counts, image geometry, OCR status, and warnings without retaining the original absolute path. A reviewed second pass also retains the exact normalized annotation array as annotations.json; the manifest records its path, count, byte count, and SHA-256 so the image interpretation remains reproducible.

Preserve text and visual evidence

Treat native PDF text and image text as two independent extraction surfaces. Native text supplies layout, heading, link, and reading-order evidence. Local OCR supplies candidate text for scans and screenshots. Keep every extracted image as an asset even when its text is converted to Markdown.

For recognizable conversations, review the source image and turn OCR into readable message blocks with available platform, author, channel, and timestamp metadata. Preserve uncertain words explicitly instead of silently repairing them. Read references/review.md before refining screenshot-heavy or mixed-media PDFs.

The first capture supplies stable image IDs and hashes in capture.json. For screenshot-heavy documents, write reviewed interpretations to a JSON array and rerun the capture:

[
  {
    "id": "page-5-image-1-0123456789ab",
    "sha256": "0123456789abcdef0123456789abcdef0123456789abcdef0123456789abcdef",
    "kind": "mixed",
    "method": "agent",
    "markdown": "> bg @ Oct 15, 2024 at 4:26 PM\n> Message text",
    "metadata": {
      "platform": "Slack",
      "contentType": "message screenshot",
      "author": "bg",
      "timestamp": "Oct 15, 2024 at 4:26 PM",
      "participants": ["bg"]
    }
  }
]
wordcell pdf "/absolute/path/to/document.pdf" \
  --output "$KB_ROOT/articles" \
  --annotations /tmp/pdf-image-annotations.json \
  --force

Use only IDs and SHA-256 values from the first manifest. The command rejects a stale interpretation if the extracted image changed. Omit metadata fields that are not visible, and use kind: "visual" with an optional alt instead of inventing a transcription for a non-text image. Put only the transcribed body in markdown; the renderer owns the image embed, “Text visible in…” heading, and visible metadata line.

Embed primarily visual images in the Markdown. For text-bearing or mixed images, keep the source image embedded beside the transcription so diagrams, photos, UI state, and spatial meaning remain inspectable. The embed is the source-image reference; do not duplicate it inside an annotation.

Heading inference follows native font, emphasis, spacing, and page geometry. Review semantic hierarchy separately: typography can identify a heading without proving whether it is a peer or a child of the preceding section. Report an ambiguous or incorrect level instead of silently treating the inference as source truth.

Report completeness literally

Use complete only when every page was processed and every extracted image was classified. Preserve partial when a tool, page, image, byte, time, or OCR boundary was reached. A usable native-text extraction does not make unprocessed screenshot pages complete.

Review:

  1. Compare the manifest page count with the PDF.
  2. Review inferred headings and report ambiguous or incorrect hierarchy.
  3. Sample native-text, screenshot, scanned, and visual-only pages.
  4. Confirm every retained asset resolves from the Markdown or manifest.
  5. Check that source-image links accompany OCR-derived text.
  6. Report the output path, status, page and image counts, OCR coverage, and unresolved warnings.

After adding or linking the capture, run the vault's normal refresh and check:

wordcell percolate "<maintained-note-id>" --root "$KB_ROOT" --limit 25 --json
wordcell refresh --root "$KB_ROOT"
wordcell check --root "$KB_ROOT"

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