Prismer Cloud is an infrastructure layer for AI agents that provides shared learning, compressed context, persistent memory, collaboration, messaging, tasks, identity, and workspaces. It is for agents and the people building or using long-running agent systems that need information and outcomes to persist across sessions. The catalogue entries provide skills, hooks, agents, instructions, and a plugin for using Prismer Cloud.
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 Prismer-AI/PrismerCloud --skill liteparsegit clone --depth 1 https://github.com/Prismer-AI/PrismerCloudWrote 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/prismer-ai/prismercloud/liteparse)<a href="https://agentmods.dev/skills/prismer-ai/prismercloud/liteparse"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/liteparse/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/prismer-ai/prismercloud/liteparse"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/liteparse.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 14 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00173 | $0.02244 |
| Opus 5.5 | $0.00069 | $0.00898 |
| Sonnet 5.5 | $0.00035 | $0.00449 |
| Haiku 4.5 | $0.00017 | $0.00224 |
Grade A, and why
liteparse scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
fetch URLs; if you only have a URL, either `curl -sL <url> -o file` How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LiteParse (local-first document parsing)
LiteParse turns document files into text the model can read — on the
daemon machine, offline, zero cloud dependency. It ships as the
@llamaindex/liteparse npm package (CLI: lit) with PDFium and
Tesseract bundled inside the package — the digital-PDF and scanned-OCR
paths need no external system dependencies.
Upstream:
run-llama/liteparse
- skill
run-llama/llamaparse-agent-skills. Apache-2.0 (core) / MIT (skill), © LlamaIndex. Vendored as a Prismer built-in.
Capability tiers — what works where
| Tier | Inputs | External dep | Status |
|---|---|---|---|
| 1 — PDF | digital + scanned PDF | none (Tesseract + PDFium bundled) | Default, out of the box — lit is baked into the daemon image |
| 2 — Images | PNG / JPG / TIFF / … | ImageMagick | Install on demand |
| 3 — Office | DOCX / XLSX / PPTX / ODT | LibreOffice (~1GB) | Install on demand |
Only Tier 1 is guaranteed present. Tiers 2 and 3 pull large system dependencies that are deliberately not baked into the daemon image — install them yourself, only when the actual input requires it (see below). Do not assume they are already installed.
Tier 1 — PDF (default, ready to use)
lit is available on the daemon. Sanity-check once, quietly:
command -v lit && lit --version # baked into the image
If (and only if) it is somehow missing, install the package locally — it is ~38MB with the OCR/render binaries bundled and installs in a few seconds:
npm i @llamaindex/liteparse && npx lit --version
Do not rely on the CLI "self-installing on first use" — that path is unreliable (npm permission / cache conflicts). Either it is baked in, or you install the package explicitly as above.
Native text path vs OCR — pick deliberately, cost differs ~10×
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.
- yesterday Changed · +1 lines d212814c67f7
- 25d ago Changed · +20 lines · +83 tokens per session 13f0fb2dde8e
- 1mo ago First seen · 157 lines · 90 tokens per session scan A 13146dc9f970
liteparse is a skill published in the GitHub repository Prismer-AI/PrismerCloud (1,363 stars, last pushed 2d ago), licensed MIT. It adds 173 tokens to every session and 2,244 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
markitdown
Convert files, URLs, and documents to Markdown using the markitdown MCP server. Activate when the user asks to convert, extract, or read content from PDFs, Word docs, PowerPoints, spreadsheets, images, audio files, or any URL.
work-markitdown
A document conversion tool that turns files such as Word documents, PDFs, PowerPoint presentations, spreadsheets, images, HTML, and CSV files into Markdown. Markdown is plain text with simple symbols for headings, lists, and other structure.
Read, extract, merge, split, rotate, watermark, create, fill, encrypt, decrypt, and OCR PDF files. Use when the user mentions PDFs or needs any document workflow centered on .pdf files.
markitdown
A local document-conversion guide built around MarkItDown, a tool that turns files such as DOCX, PDF, PPTX, XLSX, images, HTML, and CSV into Markdown text.
ingest
Ingest a file or URL into the memory graph. Handles local files (text, PDF, DOCX, XLSX, images, etc.) and URLs (web pages, YouTube, Wikipedia, RSS). Use when the user wants to add any document or web content to their knowledge graph.
vision-augment
A visual and document-analysis service for agents that cannot directly understand images. It can inspect pictures, read text with OCR, and parse documents such as PDF, Word, PowerPoint, spreadsheet, and HTML files.