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 OpenKnots/okcode --skill pdfgit clone --depth 1 https://github.com/OpenKnots/okcodeWrote 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/openknots/okcode/pdf)<a href="https://agentmods.dev/skills/openknots/okcode/pdf"><img src="https://agentmods.dev/badge/skills/openknots/okcode/pdf/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/openknots/okcode/pdf"><img src="https://agentmods.dev/badge/skills/openknots/okcode/pdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00010 | $0.00467 |
| Opus 5.5 | $0.00004 | $0.00187 |
| Sonnet 5.5 | $0.00002 | $0.00093 |
| Haiku 4.5 | $0.00001 | $0.00047 |
Grade A, and why
pdf 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Skill
When to use this skill
- Use when the task involves creating, editing, reviewing, splitting, merging, or extracting content from PDF files.
- Use when the user needs to understand whether a PDF can be edited directly or must be converted first.
- Use when the task depends on preserving layout, images, pagination, or annotation fidelity.
- Use when OCR may be required because the PDF contains scanned pages rather than selectable text.
What this skill does
- Chooses the safest PDF workflow based on the user's goal: review, extraction, transformation, or generation.
- Distinguishes between text-based PDFs and image-only scanned PDFs before proposing edits.
- Preserves fidelity when layout matters and explicitly calls out any tradeoff when converting to another format.
- Prefers repeatable tools and scripted operations over manual one-off desktop steps.
Implementation
- Start by identifying the real goal: review content, extract data, annotate, merge, split, redact, or convert.
- Determine whether the PDF is text-based or scanned. If the content is image-only, state that OCR may be required.
- If the user needs edits that preserve layout, avoid lossy conversions unless they explicitly accept them.
- If extracting text, note whether the output should preserve reading order, tables, headings, or page boundaries.
- If generating a PDF from another source, preserve the source of truth in an editable format whenever possible.
- When tools are limited, explain the limitation clearly and offer the safest fallback rather than implying full fidelity.
- Summarize important tradeoffs before carrying out destructive or lossy transformations.
Best practices
- Never imply that all PDFs are safely editable; many require conversion or specialized tooling.
- Call out OCR accuracy risk explicitly for scanned documents.
- Preserve the original file before transformations that may alter layout or metadata.
- Prefer deterministic, scriptable workflows for extraction and generation.
- Tell the user when tables, forms, annotations, or embedded fonts may not round-trip cleanly.
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 · 50 lines · 10 tokens per session scan A c873a5cb9147
pdf is a skill published in the GitHub repository OpenKnots/okcode (24 stars, last pushed 5mo ago), licensed MIT. It adds 10 tokens to every session and 467 once invoked, about $0.0000 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
document-metadata-review
Inspect PDFs, DOCX, PPTX, and XLSX files for share-readiness, metadata, links, comments, and hidden content.
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as reportlab, pdfplumber, and pypdf for generation and extraction.
pdf-brain-ingest
Ingest PDF/Markdown/TXT files into joelclaw's docs memory pipeline with Inngest durability, durable NAS artifacts, and OTEL verification. Use when adding docs, running batch reindex, reconciling coverage, or recovering stuck runs. Triggers on: 'ingest pdf', 'ingest markdown', 'docs add', 'pdf-brain ingest', 'backfill…
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.
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.
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…