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 agentmods add skills/roomi-fields/rtfm/install-pdf-fullnpx skills add roomi-fields/rtfm --skill install-pdf-fullgit clone --depth 1 https://github.com/roomi-fields/rtfmWrote 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/roomi-fields/rtfm/install-pdf-full)<a href="https://agentmods.dev/skills/roomi-fields/rtfm/install-pdf-full"><img src="https://agentmods.dev/badge/skills/roomi-fields/rtfm/install-pdf-full.svg" alt="Measured on agentmods" 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 | $0.00061 | $0.00205 |
| Opus 5 | $0.00030 | $0.00102 |
| Sonnet 5 | $0.00012 | $0.00041 |
| Haiku 4.5 | $0.00006 | $0.00020 |
Grade A, and why
install-pdf-full scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Warn the user first: this downloads ~1.5 GB (torch CPU-only build is ~500 MB, marker-pdf and its deps add the rest). Confirm they want to proceed before running.
If confirmed, run this command via the Bash tool:
"${CLAUDE_PLUGIN_ROOT}/bin/rtfm-install-extras" pdf-full
After it completes, tell the user to restart Claude Code, then run rtfm_sync to re-index PDFs with the richer parser.
The install uses the PyTorch CPU index (https://download.pytorch.org/whl/cpu) to avoid pulling the default 5 GB CUDA build. No GPU required.
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.
- 3d ago First seen · 16 lines · 61 tokens per session scan A 9569667037fb
install-pdf-full is a skill published in the GitHub repository roomi-fields/rtfm (24 stars, last pushed 3d ago), licensed MIT. It adds 61 tokens to every session and 205 once invoked, about $0.0003 per session on Opus 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
parse-document
Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.
superlinked-docs
Offload document, image, and structured-output work to the Superlinked inference cluster: convert PDF/DOCX/PPTX/XLSX/HTML/scans to clean markdown, describe an image (caption + tags), or produce schema/grammar-constrained JSON off the cluster — instead of ingesting the file directly, which can reduce the tokens billed…
haypile
Search the user's local documents (PDF, docx, pptx, markdown, text, HTML, mbox email) through Haypile, a local search daemon. Use when the user asks what their files say, wants passages from contracts, papers, or notes, or wants a folder indexed for search. Every result carries a file and page citation. Runs entirely…
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.
n8n-binary-and-data
Handle files and binary data in n8n correctly. Use when working with files, images, PDFs, attachments, uploads or downloads, base64, vision/multimodal input, or when an AI agent needs a file as tool input or output — and whenever the user mentions $binary, binaryPropertyName, "read the PDF", "attach the file", "send…
format-specific-extraction
Format-specific document extraction workflows.