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.
git clone --depth 1 https://github.com/OthmanAdi/openui-forgeWrote 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/commands/othmanadi/openui-forge/openui-prompt)<a href="https://agentmods.dev/commands/othmanadi/openui-forge/openui-prompt"><img src="https://agentmods.dev/badge/commands/othmanadi/openui-forge/openui-prompt/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/commands/othmanadi/openui-forge/openui-prompt"><img src="https://agentmods.dev/badge/commands/othmanadi/openui-forge/openui-prompt.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 | $0.00010 | $0.00669 |
| Opus 5.5 | $0.00004 | $0.00268 |
| Sonnet 5.5 | $0.00002 | $0.00134 |
| Haiku 4.5 | $0.00001 | $0.00067 |
Grade A, and why
openui-prompt 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 1mo 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate the system prompt that tells the LLM which components are available and how to use OpenUI Lang.
Step 1 — Detect the approach
Check the project to determine which prompt generation method to use:
- Non-JS backend (Python, Go, Rust, or no backend yet): Use the CLI approach
- JS/TS backend that imports the library at runtime: Use the runtime approach
- If unclear, default to CLI — it works universally
Step 2a — CLI approach (recommended, required for non-JS backends)
Find the component library file (search for createLibrary calls).
Run:
npx @openuidev/cli generate ${LIBRARY_PATH} --out ${OUTPUT_PATH}
Typical paths:
- Library:
./src/lib/library.ts - Output:
./src/generated/system-prompt.txtor./system-prompt.txt
For JSON Schema output (useful for structured generation or validation):
npx @openuidev/cli generate ${LIBRARY_PATH} --json-schema --out ${OUTPUT_PATH}/schema.json
After running, verify:
- The output file exists
- The output file is non-empty (at least a few hundred bytes)
- The file contains component names that match the library
Step 2b — Runtime approach (JS/TS backends)
If the backend already imports the library, the system prompt can be generated at runtime using library.prompt(). Verify this is set up in the API route:
import { myLibrary } from "./lib/library";
const systemPrompt = myLibrary.prompt({
preamble: "You are a helpful assistant that generates interactive UIs.",
additionalRules: [
"Always use Stack as root when combining multiple components.",
"Prefer existing components over generating raw text.",
],
examples: [
'root = Stack([title, chart])\ntitle = Header("Sales")\nchart = BarChart(labels, [s1])\nlabels = ["Q1","Q2"]\ns1 = Series("Rev", [100, 200])',
],
});
Verify:
- The library import path resolves correctly
.prompt()is called with at least apreamble- The result is passed as the system message to the LLM call
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.
- 1mo ago First seen · 89 lines · 10 tokens per session scan A ed560b0000fd
openui-prompt is a command published in the GitHub repository OthmanAdi/openui-forge (22 stars, last pushed 2mo ago), licensed MIT. It adds 10 tokens to every session and 669 once invoked, about $0.0000 per session on Opus 5.5. 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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