OpenSquilla is a token-efficient AI agent with a shared execution loop for CLI, web, and chat interfaces. It routes requests among language models, while providing persistent memory, sandboxing, web search, embeddings, and tool handling for agent-based tasks. Its catalogue entries are skills that extend the agent's workflows.
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 opensquilla/opensquilla --skill paper-delivery-summarygit clone --depth 1 https://github.com/opensquilla/opensquillaWrote 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/opensquilla/opensquilla/paper-delivery-summary)<a href="https://agentmods.dev/skills/opensquilla/opensquilla/paper-delivery-summary"><img src="https://agentmods.dev/badge/skills/opensquilla/opensquilla/paper-delivery-summary/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/opensquilla/opensquilla/paper-delivery-summary"><img src="https://agentmods.dev/badge/skills/opensquilla/opensquilla/paper-delivery-summary.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 | $0.00030 | $0.00229 |
| Opus 5 | $0.00015 | $0.00114 |
| Sonnet 5 | $0.00006 | $0.00046 |
| Haiku 4.5 | $0.00003 | $0.00023 |
Grade A, and why
paper-delivery-summary 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 9d 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
Paper delivery summary
Internal deterministic delivery formatter for meta-paper-write. It accepts
the paper contract, the runtime language instruction, compile_pdf output,
and citation_map output as JSON. It fails closed unless the PDF markers and
the complete, internally consistent citation SUMMARY are machine-readable.
The formatter never calls an LLM and never infers page or citation counts from prose. Chinese and English delivery text is selected from the confirmed paper language contract, cross-checked against the runtime language instruction.
What ships with it
1 file 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.
- 9d ago First seen · 29 lines · 30 tokens per session scan A 57f5a8d5e092
paper-delivery-summary is a skill published in the GitHub repository opensquilla/opensquilla (6,940 stars, last pushed 3d ago), licensed Apache-2.0. It adds 30 tokens to every session and 229 once invoked, about $0.0002 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
liteparse
Use this skill when the user asks to parse, perform multi-format document conversion or spatially extract text from an unstructured file (PDF, DOCX, PPTX, XLSX, images, etc.) locally without cloud dependencies.
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.
treatment-plans
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based…
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…
markitdown
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
pptx
Create and validate Microsoft PowerPoint presentations (.pptx), including structured slide decks, tables, workflows, metadata, and reproducible generation scripts. Use for presentation, slides, PowerPoint, PPT, or PPTX creation and verification tasks.