Steer LLMs and Agents at the Token Level: An interactive tool for token visualization & control, model inspection and data annotation.
Time & source
Times shown in UTC
Display time zone: UTC
Local time zone unavailable; showing UTC.
PublishedOffset at this time: UTC+0Sep 19, 2026, 04:21 UTC
IngestedOffset at this time: UTC+0Sep 19, 2026, 13:00 UTC
- Published
- Sep 19, 2026, 04:21
- Ingested
- Sep 19, 2026, 13:00
- Source type
- Dev community
- Tier
- Community
- Source status
- Healthy
Tier is a per-source editorial setting, not a per-item score.
onPanda is designed for geeks, power users, curious minds, and engineers. Its UI is built for deep exploration and efficient data annotation.
- The core loop is simple: hover over a token → click an alternative or edit freely → continue generation. You can edit every part of model output exposed by onPanda, including reasoning and tool calls.
- Edit prompts directly, branch tool calls, and use a tree structure to record branch history. This makes onPanda useful for model inspection and prompt engineering.
- Support multiple modalities, including images, video, and audio; use tool calls and connect MCP servers to perform tasks in real environments.
- Connect popular harnesses such as Claude Code, Codex, and OpenCode to execute tasks. Explore and compare their tool sets, system prompts, skills, and memory mechanisms.
- onPanda includes browser-agent, an agent that runs in the user's browser without installation. It uses the browser as its harness and provides JavaScript execution, information retrieval, interface interaction, multimedia I/O, local file access, and persistent memory.
I have been building onPanda since 2024.09, it took two years for it to gradually enrich its functionality and ease of use. In my opinion, onPanda is very suitable for the r/LocalLLaMA community. Any feedback and evaluation are welcome.