pdf-toolkit

GitHub

提供确定性的PDF结构化操作技能,包括提取文本表格、合并/拆分页面、填充表单及从数据生成PDF。适用于需要精确程序化控制PDF内容的场景,支持pypdf等库。

src/opensquilla/skills/bundled/pdf-toolkit/SKILL.md TokenRhythm/opensquilla

Trigger Scenarios

用户需要从PDF中提取文本或表格数据 用户需要合并多个PDF文件或按页码范围拆分文件 用户需要填写PDF表单字段 用户需要根据JSON数据生成新的PDF文档

Install

npx skills add TokenRhythm/opensquilla --skill pdf-toolkit -g -y
More Options

Non-standard path

npx skills add https://github.com/TokenRhythm/opensquilla/tree/main/src/opensquilla/skills/bundled/pdf-toolkit -g -y

Use without installing

npx skills use TokenRhythm/opensquilla@pdf-toolkit

指定 Agent (Claude Code)

npx skills add TokenRhythm/opensquilla --skill pdf-toolkit -a claude-code -g -y

安装 repo 全部 skill

npx skills add TokenRhythm/opensquilla --all -g -y

预览 repo 内 skill

npx skills add TokenRhythm/opensquilla --list

SKILL.md

Frontmatter
{
    "name": "pdf-toolkit",
    "homepage": "https:\/\/pypdf.readthedocs.io\/",
    "metadata": {
        "platform": {
            "emoji": "📕",
            "install": [
                {
                    "id": "pypdf",
                    "kind": "uv",
                    "label": "Install pypdf (uv pip)",
                    "package": "pypdf"
                },
                {
                    "id": "reportlab",
                    "kind": "uv",
                    "label": "Install reportlab (uv pip)",
                    "package": "reportlab"
                }
            ],
            "requires": {
                "anyBins": [
                    "python",
                    "python3"
                ]
            }
        }
    },
    "invocation": "direct",
    "provenance": {
        "origin": "clawhub-mit0",
        "license": "MIT-0",
        "upstream_url": "https:\/\/clawhub.ai\/pdf",
        "maintained_by": "OpenSquilla"
    },
    "visibility": "public",
    "description": "Structured `.pdf` operations: extract text\/tables, merge pages from multiple PDFs, split a PDF by page ranges, fill PDF form fields, and generate fresh PDFs from JSON. Trigger when the user wants deterministic programmatic PDF work — examples: pull tables from a report, combine three PDFs, extract pages 5-12, fill a tax form, or build a new PDF from data. This is the single public PDF entry and uses pypdf, pdfplumber, and reportlab.",
    "description_zh": "结构化的 .pdf 操作:提取文本\/表格、合并多个PDF的页面、按页码范围拆分PDF、填写PDF表单字段以及从JSON生成新PDF。当用户需要确定性的程序化PDF处理时触发,例如从报告提取表格、合并三个PDF、提取第5-12页、填写税表或用数据构建新PDF。本技能是唯一公开的 PDF 入口,通过 pypdf、pdfplumber 和 reportlab 执行。"
}

pdf-toolkit

Deterministic, structural PDF operations. Use this skill for programmatic work where you know exactly what you want done. For a natural-language rewrite, first draft the replacement content with ordinary reasoning, then use the explicit extract/generate/merge operations here to create the final PDF.

Use the inline Python examples with execute_code in a restricted channel. Keep files in the active workspace and call publish_artifact with the finished PDF. Shell commands below require an available exec_command; they are optional shortcuts, not a reason to request host execution. If the sandbox or a required library is unavailable, report the limitation rather than retrying outside the sandbox.

Decide the operation

Goal Script
Get text or tables out of a PDF extract.py
Combine pages from multiple PDFs merge.py
Split a PDF by page ranges split.py
Fill /Tx form fields in a PDF form_fill.py
Build a new PDF from data inline reportlab snippet, see Path C below

Path A: Extract

python {baseDir}/scripts/extract.py /path/to/doc.pdf --json

Output:

{
  "pages": 12,
  "metadata": {"title": "...", "author": "..."},
  "text": [
    {"page": 1, "content": "..."},
    {"page": 2, "content": "..."}
  ],
  "tables": [
    {"page": 3, "rows": [["..."], ["..."]]}
  ]
}

Text uses pdfplumber (already in default dependencies) which preserves column layout better than naive PDF text extraction. Tables use pdfplumber.extract_tables() with default settings; for tricky layouts pass --tables-strategy lines|text|explicit to switch detection mode.

For OCR (scanned PDFs), this skill does not include Tesseract — use the sibling skill that wraps an OCR engine (out of scope here).


Path B: Merge / Split

Merge full files:

python {baseDir}/scripts/merge.py a.pdf b.pdf c.pdf --out combined.pdf

Or merge specific page ranges with the manifest form:

python {baseDir}/scripts/merge.py manifest.json --out combined.pdf

manifest.json:

[
  {"file": "a.pdf", "pages": "1-3"},
  {"file": "b.pdf", "pages": "5,7,9-11"},
  {"file": "c.pdf"}
]

Page ranges are 1-based, comma-separated, hyphen for ranges. Omit pages to include the whole file. Splits use the same syntax in reverse:

python {baseDir}/scripts/split.py input.pdf --pages "1-3,7,10-12" --out output_dir/

Each range writes one output file: output_dir/input_001.pdf, output_dir/input_002.pdf, …


Path C: Form fill

python {baseDir}/scripts/form_fill.py form.pdf data.json --out filled.pdf

data.json maps field name → string value:

{
  "applicant_name": "Wei E.",
  "submission_date": "2026-05-06",
  "agreed": "Yes"
}

The script discovers fields via pypdf.PdfReader.get_fields() and updates them with update_page_form_field_values(). Fields not present in the JSON are left untouched. Run with --list-fields to enumerate the form's fields without filling.

Caveats:

  • /Btn checkbox fields take the export value (often Yes, On, or 1) rather than true — inspect with --list-fields to discover.
  • AcroForm fills only. XFA forms (used by some legal templates) require Adobe-specific tooling and are out of scope.
  • Some signed PDFs invalidate the signature when fields change. Strip signatures explicitly with --clear-signatures if that is intended.

Path D: Generate from scratch

Use reportlab directly when you need a new PDF:

from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import LETTER
from pathlib import Path

c = canvas.Canvas(str(Path("out.pdf")), pagesize=LETTER)
c.setFont("Helvetica-Bold", 18)
c.drawString(72, 720, "Q3 Review")
c.setFont("Helvetica", 11)
c.drawString(72, 696, "Revenue grew 18% year over year.")
c.showPage()
c.save()

For Chinese text, register a CJK font instead of Helvetica. ReportLab's CID font works without downloading fonts or reading a user font directory:

from reportlab.pdfbase import pdfmetrics
from reportlab.pdfbase.cidfonts import UnicodeCIDFont
from reportlab.pdfgen import canvas

pdfmetrics.registerFont(UnicodeCIDFont("STSong-Light"))
c = canvas.Canvas("report.pdf")
c.setFont("STSong-Light", 14)
c.drawString(72, 760, "季度报告:收入增长")
c.save()

CID fonts rely on PDF reader CJK support. When an embedded font is required, use a licensed font already available inside the workspace or permitted system font roots. Validate the text with pypdf before publishing.

For tables, headers/footers, and multi-column layouts, switch to reportlab.platypus (SimpleDocTemplate, Paragraph, Table, PageBreak). See references/reportlab.md.


Natural-language changes

This public entry deliberately keeps the PDF mutation step deterministic. For requests such as "make the title shorter", inspect the source page, draft the replacement text with the model, and generate a new document with the reviewed content. Do not claim that arbitrary in-place page rewriting is available.


Common pitfalls

Symptom Cause Fix
Extracted text is empty Scanned PDF, no text layer OCR is out of scope; use a separate OCR skill
Garbled characters in extract PDF uses a custom font encoding Try pdfplumber.open(path, laparams={...}) with char_margin adjustments
Merged PDF is huge Underlying PDFs include large embedded fonts Subset fonts via pypdf compress_content_streams()
Form fill silently no-ops Field name in JSON does not match PDF field name Run with --list-fields first to see exact names
Pages out of order after split Range overlap collapsed unexpectedly Use disjoint ranges, e.g. 1-3,4-6 not 1-5,3-6

Boundaries

  • This skill works with text-based and form-based PDFs. Scanned image PDFs need OCR before any text path produces results.
  • Encrypted PDFs are read-only here. Decryption requires the user-supplied password and is out of scope for this skill.
  • For PDF-to-image rendering, use a separate skill that wraps Poppler or PyMuPDF.
  • Digital signature operations (signing, verifying, revoking) are out of scope.

Version History

  • 7e0b08e Current 2026-09-22 06:07

    更新描述以强调确定性操作与自然语言重写的区别;增加extract.py输出示例及merge/split详细用法说明;移除对nano-pdf的依赖引用并完善路径C的表单填充描述。

  • f662be3 2026-07-31 11:49
  • 7f72a32 2026-07-05 18:39

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Metadata

Files
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Version
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Hash
a9e013b1
Indexed
2026-07-05 18:39

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