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-integrate)<a href="https://agentmods.dev/commands/othmanadi/openui-forge/openui-integrate"><img src="https://agentmods.dev/badge/commands/othmanadi/openui-forge/openui-integrate/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-integrate"><img src="https://agentmods.dev/badge/commands/othmanadi/openui-forge/openui-integrate.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 | $0.00011 | $0.01277 |
| Opus 5.5 | $0.00004 | $0.00511 |
| Sonnet 5.5 | $0.00002 | $0.00255 |
| Haiku 4.5 | $0.00001 | $0.00128 |
Grade A, and why
openui-integrate 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 — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
This is the core command. It connects the component library to an LLM backend and creates the streaming pipeline.
Read references/adapter-matrix.md before starting — it contains the full adapter internals and compatibility details.
Step 1 — Detect or ask the stack
Check the project for clues about the backend:
- Look for existing API routes (app/api/, pages/api/, server/*)
- Check package.json for
openai,@anthropic-ai/sdk,ai(Vercel AI SDK),@langchain/openai - Check for non-JS backends: requirements.txt (Python), go.mod (Go), Cargo.toml (Rust)
If the stack cannot be determined automatically, ask the user:
- What is your backend language? (TypeScript/JavaScript, Python, Go, Rust)
- What LLM provider or SDK? (OpenAI, Anthropic, Vercel AI SDK, LangChain, other)
Step 2 — Follow the integration matrix
Read references/adapter-matrix.md for the full adapter details.
TypeScript / JavaScript backends
OpenAI SDK (Chat Completions):
- Frontend adapter:
openAIReadableStreamAdapter() - Frontend format:
openAIMessageFormat - Read and adapt:
templates/api-route-openai.ts.template - Install:
npm install openai
Anthropic SDK (Claude):
- Frontend adapter:
openAIAdapter() - Frontend format:
openAIMessageFormat - Read and adapt:
templates/api-route-anthropic.ts.template - Install:
npm install @anthropic-ai/sdk - Note: The backend converts Anthropic streaming events into OpenAI-compatible SSE (
data: {json}\n\nlines terminated bydata: [DONE])
Vercel AI SDK:
- Frontend: native (uses
useChatorprocessMessage) - Read and adapt:
templates/api-route-vercel-ai.ts.template - Install:
npm install ai @ai-sdk/openai - Note: Uses
streamText+toUIMessageStreamResponse()
LangChain / LangGraph:
- Frontend adapter:
openAIAdapter() - Frontend format:
openAIMessageFormat - Read and adapt:
templates/api-route-langchain.ts.template - Install:
npm install @langchain/openai @langchain/core - Note: The backend converts LangChain stream chunks into OpenAI-compatible SSE
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 · 117 lines · 11 tokens per session scan A 71a52386fd07
openui-integrate is a command published in the GitHub repository OthmanAdi/openui-forge (22 stars, last pushed 2mo ago), licensed MIT. It adds 11 tokens to every session and 1,277 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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