Borrowing it
Nothing to install: this file belongs to llama-farm/llamafarm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/llama-farm/llamafarm/main/.claude/skills/runtime-skills/SKILL.mdgit clone --depth 1 https://github.com/llama-farm/llamafarmWrote 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/llama-farm/llamafarm/runtime-skills)<a href="https://agentmods.dev/skills/llama-farm/llamafarm/runtime-skills"><img src="https://agentmods.dev/badge/skills/llama-farm/llamafarm/runtime-skills/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/llama-farm/llamafarm/runtime-skills"><img src="https://agentmods.dev/badge/skills/llama-farm/llamafarm/runtime-skills.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 | $0.00035 | $0.01251 |
| Opus 5 | $0.00017 | $0.00626 |
| Sonnet 5 | $0.00007 | $0.00250 |
| Haiku 4.5 | $0.00003 | $0.00125 |
Grade A, and why
runtime-skills 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 10d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Universal Runtime Skills
Best practices and code review checklists for the Universal Runtime - LlamaFarm's local ML inference server.
Overview
The Universal Runtime provides OpenAI-compatible endpoints for HuggingFace models:
- Text generation (Causal LMs: GPT, Llama, Mistral, Qwen)
- Text embeddings (BERT, sentence-transformers, ModernBERT)
- Classification, NER, and reranking
- OCR and document understanding
- Anomaly detection
Directory: runtimes/universal/
Python: 3.11+
Key Dependencies: PyTorch, Transformers, FastAPI, llama-cpp-python
Links to Shared Skills
This skill extends the shared Python practices. Always apply these first:
| Topic | File | Priority |
|---|---|---|
| Patterns | python-skills/patterns.md | Medium |
| Async | python-skills/async.md | High |
| Typing | python-skills/typing.md | Medium |
| Testing | python-skills/testing.md | Medium |
| Errors | python-skills/error-handling.md | High |
| Security | python-skills/security.md | Critical |
Runtime-Specific Checklists
| Topic | File | Key Points |
|---|---|---|
| PyTorch | pytorch.md | Device management, dtype, memory cleanup |
| Transformers | transformers.md | Model loading, tokenization, inference |
| FastAPI | fastapi.md | API design, streaming, lifespan |
| Performance | performance.md | Batching, caching, optimizations |
Architecture
runtimes/universal/
├── server.py # FastAPI app, model caching, endpoints
├── core/
│ └── logging.py # UniversalRuntimeLogger (structlog)
├── models/
│ ├── base.py # BaseModel ABC with device management
│ ├── language_model.py # Transformers text generation
│ ├── gguf_language_model.py # llama-cpp-python for GGUF
│ ├── encoder_model.py # Embeddings, classification, NER, reranking
│ └── ... # OCR, anomaly, document models
├── routers/
│ └── chat_completions/ # Chat completions with streaming
├── utils/
│ ├── device.py # Device detection (CUDA/MPS/CPU)
│ ├── model_cache.py # TTL-based model caching
│ ├── model_format.py # GGUF vs transformers detection
│ └── context_calculator.py # GGUF context size computation
└── tests/
What ships with it
4 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.
- 10d ago First seen · 152 lines · 35 tokens per session scan A 8d7e28f8f15b
runtime-skills is a skill published in the GitHub repository llama-farm/llamafarm (838 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 35 tokens to every session and 1,251 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.
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