Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add eigenweltlabs/legalwork --skill pdf-toolsgit clone --depth 1 https://github.com/eigenweltlabs/legalworkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/eigenweltlabs/legalwork/pdf-tools)<a href="https://agentmods.dev/skills/eigenweltlabs/legalwork/pdf-tools"><img src="https://agentmods.dev/badge/skills/eigenweltlabs/legalwork/pdf-tools/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/eigenweltlabs/legalwork/pdf-tools"><img src="https://agentmods.dev/badge/skills/eigenweltlabs/legalwork/pdf-tools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00122 | $0.01548 |
| Opus 5.5 | $0.00049 | $0.00619 |
| Sonnet 5.5 | $0.00024 | $0.00310 |
| Haiku 4.5 | $0.00012 | $0.00155 |
Grade A, and why
pdf-tools scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF reading + actions (text / annotate / fill-form / sign)
This skill is how this firm reads, annotates, fills, and signs PDFs with AI. It is
self-contained: assets/pdf-agent.mjs imports vendored engines (pdf-lib for
actions, pdf.js for text — pure JS, no native deps), so it runs in any workspace
with no install. Do not hand-edit PDF bytes or reach for python or pdftotext
(they may not exist on the machine) — use this tool. Every editing command writes
a new file next to the source; the original PDF is never touched.
The tool
# ALWAYS FIRST: page count, page sizes (points), and every form field
# (name / type / current value / options) as JSON.
node .opencode/skills/pdf-tools/assets/pdf-agent.mjs inspect "<file.pdf>"
# READ the PDF: its text content per page as JSON ({ pageCount, pages: [{page, text}] }).
# All pages by default; --pages limits it ("3", "1-4", "1,3,7-9").
node .opencode/skills/pdf-tools/assets/pdf-agent.mjs text "<file.pdf>" --pages 1-4
# Sticky notes + highlight rectangles (plan JSON on stdin). Writes <base>.annotated.pdf.
echo '<plan-json>' | node .opencode/skills/pdf-tools/assets/pdf-agent.mjs annotate "<file.pdf>" --plan -
# Fill AcroForm fields from JSON key/values (stdin). Writes <base>.filled.pdf.
echo '{"Field Name":"value","Agree":true}' | node .opencode/skills/pdf-tools/assets/pdf-agent.mjs fill "<file.pdf>" --data -
# Stamp a signature block. Writes <base>.signed.pdf.
node .opencode/skills/pdf-tools/assets/pdf-agent.mjs sign "<file.pdf>" --name "Jane Doe" --date 2026-07-01
node .opencode/skills/pdf-tools/assets/pdf-agent.mjs sign "<file.pdf>" --name "Jane Doe" --image signature.png --page 3 --x 320 --y 90
Coordinates: pages are 1-based; x/y are PDF points (1/72 inch, US
Letter is 612×792) with the origin at the BOTTOM-LEFT of the page; (x, y) is
the bottom-left corner of the note/highlight/signature. Get each page's size from
inspect before placing anything.
Annotate — the plan
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 113 lines · 122 tokens per session scan A a2502b6f0325
pdf-tools is a skill published in the GitHub repository eigenweltlabs/legalwork (129 stars, last pushed today), licensed MIT. It adds 122 tokens to every session and 1,548 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
apify-youtube-transcript-scraper
Get YouTube captions, timestamped quotations, SRT/VTT and translated transcripts for videos, channels and playlists through the harshmaur/youtube-transcript-scraper Apify Actor.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
meta-web-to-pdf-briefing
Render a topic into a distributable PDF briefing in three steps: web search → bullet summary → styled PDF. Trigger when the user asks for a PDF briefing on a single topic.
pkf-writing
Author, update, convert, validate, persist, and render PKF (.pkf) content through message-inline, Library Asset, or Memory Page carriers. Use for structured reports, knowledge pages, delivery cards, or any .pkf body. NOT for recall, memory-graph placement, or curation decisions — those belong to the memory skill.
chat-complex-documents
Chat with and search your complex documents — ask questions, extract tables and fields, and get answers grounded in the source. Connects the hosted Unstructured Transform MCP server to parse, structure, and enrich PDFs, Word/Excel/PowerPoint, images, scanned files, emails, and 60+ other formats into clean, AI-ready…