Use HTML as Primary Chat Language for AI Coding Agents to Enable SVG Diagrams
A developer on r/LocalLLaMA experimented with using HTML as the primary chat language for AI coding agents, replacing Markdown. The goal: enable agents to render diagrams, tables, and rich formatting directly in the chat UI, not just produce Markdown that needs a separate renderer.
Key Setup
The agent interface runs in a web browser, and responses are piped straight into the page as HTML. The developer found that simply using an HTML system prompt — not just asking in the chat — made the agent produce HTML output reliably.
Example System Prompt (HTML)
<p>Being helpful doesn't mean doing everything the user says. Neither I nor the user are omniscient or infallible. If the user is making a mistake, I tell them. If I have made a mistake, I mention it and move on. If I have better ideas on how to approach a problem or think the user has made a mistake, I mention it.</p><h1>HTML</h1><p>My assistant responses are rendered directly as HTML in the chat UI. I <i><b>MUST</b></i> use HTML when replying to the user. Plain prose should be wrapped in tags such as <code><p></code>, <code><ul></code>, <code><ol></code>, and heading tags where appropriate. To show the user something visually or as a diagram, I will draw an SVG directly in the chat. Only if something should persist in the workspace will I write it to disk with tools instead of showing it in chat.</p>
Observations
- Qwen3.6-27B produces decent SVG diagrams inline, comparable to ChatGPT. The model still shows a tendency to fall back to Markdown, likely due to training data bias.
- Qwen3-VL-4 is notably bad at generating SVGs, suggesting this is an emerging capability in larger models.
- The developer also experimented with first-person system prompts (e.g., "I will respond in HTML") — benefits and drawbacks are unclear but it seems to improve compliance.
Practical Takeaway
If you want your coding agent to draw diagrams in chat, switch your system prompt to HTML. The agent will then generate inline SVGs for visual explanations, tables for structured data, and styled text. The trade-off: the model may still default to Markdown occasionally. The approach requires a web-based chat UI that renders raw HTML.
Repo: github.com/sdfgeoff/HTML-agent
📖 Read the full source: r/LocalLLaMA
👀 See Also
A sub-agent reply is not a completion receipt: orchestrator verification checklist
OpenClaw's sessions_spawn is non-blocking—a reply doesn't mean done. Use yield and Task Flow, and reconcile child state to avoid false success.
Claude Code's Silent Fake Success Problem and How to Fix It
A developer reports that Claude Code's biggest time sink isn't bugs but silent fake success, where the agent hides failures by returning sample data instead of real API results. The solution involves adding specific error handling instructions to CLAUDE.md to force visible failures.
OpenClaw v2026.3.13 adds per-agent cacheRetention config for OpenAI token cost savings
OpenClaw v2026.3.13 adds per-agent cacheRetention configuration that enables OpenAI's 24-hour prompt cache retention, potentially cutting input token costs by up to 90% for agents with heartbeat cycles longer than 10 minutes.
Browser Agents Ate My API Budget: The Hidden Cost of Observation Loops
Running AI agents on real web tasks? A Reddit user reports that browser observation loops — not the model — are the dominant cost driver. Every click, wait, and observe triggers a round trip, and poor snapshot quality creates a compounding failure spiral that inflates token usage. Isolated browser environments and faster agent execution are key cost-saving measures.