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 litestar-org/litestar-skills --skill litestar-deploymentgit clone --depth 1 https://github.com/litestar-org/litestar-skillsWrote 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/litestar-org/litestar-skills/litestar-deployment)<a href="https://agentmods.dev/skills/litestar-org/litestar-skills/litestar-deployment"><img src="https://agentmods.dev/badge/skills/litestar-org/litestar-skills/litestar-deployment/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/litestar-org/litestar-skills/litestar-deployment"><img src="https://agentmods.dev/badge/skills/litestar-org/litestar-skills/litestar-deployment.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 | $0.00047 | $0.02508 |
| Opus 5 | $0.00023 | $0.01254 |
| Sonnet 5 | $0.00009 | $0.00502 |
| Haiku 4.5 | $0.00005 | $0.00251 |
Grade B, and why
litestar-deployment scanned grade B 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 11d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
- **Never run as root.** `USER nonroot` in Dockerfile. `runAsNonRoot: true` in K8s pod security context. How it starts
The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Litestar Deployment
Production deployment patterns for Litestar ASGI applications across Docker, Railway, Kubernetes/GKE, Cloud Run, and systemd. Covers multi-stage Dockerfiles, distroless images, asset pipelines, worker containers, and health-check integration.
All deployment paths use Granian (via litestar-granian) as the ASGI server, uv for Python package management, and Bun for frontend asset builds.
Build vs. deploy split: this skill is about running Litestar artifacts in production. For producing those artifacts — wheel bundling with embedded Vite assets, PyApp onefile binaries, GitHub Actions CI/release pipelines — see litestar-build.
Code Style Rules
from __future__ import annotationsis allowed in consumer-app modules (Dockerfiles, deploy scripts, settings).- All Python samples use PEP 604 unions (
T | None). - Granian over uvicorn in every CMD/entrypoint. Use
litestar run(which delegates to Granian whenlitestar-granianis installed). - Environment-driven configuration via
@dataclasssettings — never hardcode secrets or connection strings. - Shell scripts follow Google Shell Style Guide (set -euo pipefail, quoted variables).
Quick Reference
| Target | Reference | Key File |
|---|---|---|
| Docker (standard multi-stage) | references/docker-standard.md | Dockerfile |
| Docker (distroless production) | references/docker-distroless.md | Dockerfile.distroless |
| SAQ worker container | references/docker-workers.md | Dockerfile.worker |
| Docker Compose (app + infra) | references/docker-compose.md | docker-compose.yml |
| Railway | references/railway.md | railway.app.json |
| Kubernetes / GKE | references/kubernetes.md | deploy.py, templates/ |
| Cloud Run | references/cloud-run.md | service.yaml |
| systemd native | references/systemd.md | litestar.service |
What ships with it
9 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.
- references/cloud-run.md 4.3 KB
- references/docker-compose.md 4.5 KB
- references/docker-distroless.md 6.8 KB
- references/docker-standard.md 5.0 KB
- references/docker-workers.md 3.5 KB
- references/kubernetes.md 7.8 KB
- references/litestar-app.md 7.4 KB
- references/railway.md 3.7 KB
- references/systemd.md 3.5 KB
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.
- 11d ago First seen · 180 lines · 47 tokens per session scan B 8942919b927e
litestar-deployment is a skill published in the GitHub repository litestar-org/litestar-skills (14 stars, last pushed 21d ago), licensed MIT. It adds 47 tokens to every session and 2,508 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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