json-render is a framework where AI produces user interfaces as structured JSON constrained by a developer-defined component catalogue. It is for building dynamic interfaces from natural-language prompts across web and mobile frameworks.
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 vercel-labs/json-render --skill yamlgit clone --depth 1 https://github.com/vercel-labs/json-renderWrote 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/vercel-labs/json-render/yaml)<a href="https://agentmods.dev/skills/vercel-labs/json-render/yaml"><img src="https://agentmods.dev/badge/skills/vercel-labs/json-render/yaml/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/vercel-labs/json-render/yaml"><img src="https://agentmods.dev/badge/skills/vercel-labs/json-render/yaml.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00048 | $0.01144 |
| Opus 5.5 | $0.00019 | $0.00458 |
| Sonnet 5.5 | $0.00010 | $0.00229 |
| Haiku 4.5 | $0.00005 | $0.00114 |
Grade A, and why
yaml 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 15d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@json-render/yaml
YAML wire format for @json-render/core. Progressive rendering and surgical edits via streaming YAML.
Key Concepts
- YAML wire format: Alternative to JSONL that uses code fences (
yaml-spec,yaml-edit,yaml-patch,diff) - Streaming parser: Incrementally parses YAML, emits JSON Patch operations via diffing
- Edit modes: Patch (RFC 6902), merge (RFC 7396), and unified diff
- AI SDK transform:
TransformStreamthat converts YAML fences into json-render patches
Generating YAML Prompts
import { yamlPrompt } from "@json-render/yaml";
import { catalog } from "./catalog";
// Standalone mode (LLM outputs only YAML)
const systemPrompt = yamlPrompt(catalog, {
mode: "standalone",
editModes: ["merge"],
customRules: ["Always use dark theme"],
});
// Inline mode (LLM responds conversationally, wraps YAML in fences)
const chatPrompt = yamlPrompt(catalog, { mode: "inline" });
Options:
system(string) — Custom system message intromode("standalone" | "inline") — Output mode, default "standalone"customRules(string[]) — Additional rules appended to prompteditModes(EditMode[]) — Edit modes to document, default ["merge"]
AI SDK Transform
Use pipeYamlRender as a drop-in replacement for pipeJsonRender:
import { pipeYamlRender } from "@json-render/yaml";
import { createUIMessageStream, createUIMessageStreamResponse } from "ai";
const stream = createUIMessageStream({
execute: async ({ writer }) => {
writer.merge(pipeYamlRender(result.toUIMessageStream()));
},
});
return createUIMessageStreamResponse({ stream });
For multi-turn edits, pass the previous spec:
pipeYamlRender(result.toUIMessageStream(), {
previousSpec: currentSpec,
});
The transform recognizes four fence types:
yaml-spec— Full spec, parsed progressively line-by-lineyaml-edit— Partial YAML deep-merged with current spec (RFC 7396)yaml-patch— RFC 6902 JSON Patch lines; applied to the working spec, so lateryaml-editfences see themdiff— Unified diff applied to serialized spec
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.
- 15d ago Changed 1e1cbb293fec
- 2mo ago First seen · 142 lines · 48 tokens per session scan A 510a4898a18d
yaml is a skill published in the GitHub repository vercel-labs/json-render (19,433 stars, last pushed yesterday), licensed Apache-2.0. It adds 48 tokens to every session and 1,144 once invoked, about $0.0002 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.
yaml compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| yamlvercel-labs/json-render | Skill | 19k | yesterday | Apache-2.0 | A | 48 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |