Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/litestar-org/litestar-skillsnpx agentmods add skills/litestar-org/litestar-skills/litestar-buildWrote 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-build)<a href="https://agentmods.dev/skills/litestar-org/litestar-skills/litestar-build"><img src="https://agentmods.dev/badge/skills/litestar-org/litestar-skills/litestar-build/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-build"><img src="https://agentmods.dev/badge/skills/litestar-org/litestar-skills/litestar-build.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 MCP Rug Pull · line 205 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
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 | $0.00046 | $0.03823 |
| Opus 5 | $0.00023 | $0.01912 |
| Sonnet 5 | $0.00009 | $0.00765 |
| Haiku 4.5 | $0.00005 | $0.00382 |
Grade A, and why
litestar-build 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 12d 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 — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
litestar-build
Build-side packaging patterns for Litestar applications: how to produce a self-contained wheel that embeds the Vite/Bun frontend, how to wrap that wheel in a PyApp onefile binary, and how to wire the whole pipeline into GitHub Actions CI and releases.
This skill is the counterpart to litestar-deployment — build is about producing artifacts, deployment is about running them.
The Core Idea: One Wheel, Self-Contained
A Litestar wheel is the single source of truth for a release. It contains:
- Python code (
src/py/app/orapp/) - SQL migrations, Jinja templates, INI configs
- The built Vite/Bun frontend bundle (JS, CSS, HTML, images)
- Email templates rendered from React/MJX to static HTML
Once produced, that wheel can be:
pip installed into a container (litestar-deployment).- Wrapped in a PyApp binary (
dist/<app>,dist/app-x86_64-linux-gnu) for zero-dep distribution. - Uploaded to PyPI or a private index.
All three paths assume the wheel is already complete — no bun run build happens at deploy/install time.
Why bundle assets into the wheel (and not serve from a CDN)
| Property | Bundled wheel | External CDN |
|---|---|---|
| Deploy artifacts | 1 (.whl or binary) |
2+ (wheel + CDN upload) |
| Version alignment | Atomic — API and UI lock-step | Easy to skew; rollback is painful |
| PyApp onefile | Required — the binary embeds the wheel | Not possible — binary can't fetch CDN URLs at install time |
| Offline/air-gapped | Works | Doesn't |
| Dev server startup | Instant (files on disk next to package) | Fine |
| Frontend-only deploys | Rebuild + redeploy wheel | Push to CDN only |
For most Litestar apps that ship as a product (CLIs, internal tools, enterprise installers), bundled-in-wheel is correct. Projects like litestar-fullstack-inertia and litestar-fullstack all bundle.
Why litestar-vite configs look the way they do in reference apps
What ships with it
6 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.
- 12d ago First seen · 249 lines · 46 tokens per session scan A 81b4104a2b3e
litestar-build is a skill published in the GitHub repository litestar-org/litestar-skills (14 stars, last pushed 22d ago), licensed MIT. It adds 46 tokens to every session and 3,823 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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