onPanda creator diyer22 claims its released interface lets users inspect token probabilities, edit exposed model outputs and tool calls, and resume generation from alternatives, enabling fine-grained agent debugging and data annotation.

state: watchingheat: lowuncertainty: mediumconvergesscott: mediumllm-tooling model-inspection agent-controldiyer22onPanda

What is this?

The supplied case identifies onPanda as an interactive LLM and agent tool by diyer22, presented in a Show HN submission as offering token-level steering. Its creator reportedly claims users can inspect token probabilities, edit exposed outputs and tool calls, and resume generation from alternatives for debugging and data annotation; a quoted X post says it took two years to build. None of the supplied web results directly covers onPanda or diyer22: they describe other inspection, replay, and token-steering tools, so onPanda’s release status and specific capabilities remain creator claims rather than independently corroborated facts.

Why it matters to Scott

onPanda’s claimed inspect–edit–resume workflow converges with Scott’s Observable Autonomy principle and offers a concrete debugging approach worth testing against Ask’s multi-format tool-call parsing and his trace-backed agent comparisons. The supplied radar pages track adjacent inspection and replay tools, not onPanda itself; its capabilities remain creator testimony, with no established compatibility with Scott’s harnesses or evidence that resuming edited generation safely restores external execution state.

ip:framework.12-factor-agents-frameworkdev:project.askdev:concept.trace-backed-agent-comparisonradar:logitscope-token-uncertainty-debuggingradar:rungraph-claude-code-session-replayradar:openai-codex-thread-revert-support

queries asked of Scott's wikis

agent harness debugging inspect edit replay execution
token probabilities logprobs generation steering
human intervention tool-call editing agent control
branching agent trajectories reproducibility state restoration
interactive annotation corrected model outputs training data

Measured heat

now 0 pts/hpeak 0 pts/hcomments 0/hpeers p14momentum: steady3 platformsage 549h

points/hour across evidence · reading as of 2026-10-12 02:59:37.977291+11:00 · deterministic, not a model opinion

How the heat travelled

09-18 18:49	⭐ origin echo-reconstructed	The original X post says: “I spent two years building this interactive tool to let you steer LLMs and agents at the token level.” It introdu Lei Yang (@diyerxx) on x (echo) · attributed from hn.story.49759013	—
09-18 19:26	first on hacker news · published · +0.6h	Show HN: OnPanda – Steer LLMs and agents at the token level diyer22	—
09-19 04:21	first on r/LocalLLaMA · published · +9.5h	Steer LLMs and Agents at the Token Level: An interactive tool for token visualization & control, model inspection and data annotation. Fancy_Fanqi77	—
09-18 19:26	amplified on hacker news	hn.story.49759013 diyer22	peak 5 · 0 comments · 5% of case engagement
09-19 04:21	amplified on r/LocalLLaMA 👑	reddit.post.1wkc4c9 Fancy_Fanqi77	peak 122 · 37 comments · 95% of case engagement
09-18 20:20	our radar first saw it · +1.5h	discovery anchor: hn.story.49759013	—

pace: p72 vs 1032 stories at the 336h mark (now 549h old) — ahead of cheatbench-reward-gaming-benchmark (1.0x), behind aether-agent-commerce-protocol (1.0x)

Evidence (3) — ⭐ canonical anchor

source	object	author	score	comments
🟧 hn	Show HN: OnPanda – Steer LLMs and agents at the token level Retrieved article excerpt Open article · Retrieved 2026-09-18T20:22:52.470751+00:00 English as Data Annotator: ## onPanda: on-Policy Alignment Data Annotator `Scaling up your data efficiency with token-level supervision.` [[Project Page](https://on-panda.github.io/research/)] onPanda: Token-Level Control for LLMs and Agents 👉 Usage: Please read the [introduction](https://on-panda.github.io/introduction/?lang=en-US) first ### onPanda Instructions: Basic Features - Probability visualization: responses are composed of token chunks; the color under each chunk reflects its probability (green = high, red = low) - Candidate continuations: hover over response text to see candidate chunks; click a candidate to continue from it - Double-click to edit: double-click a chunk to modify it, then the model continues from your edit Image Features - You can paste images, audio and video directly into the input box - Single-click an image to zoom in/out, double-click to open it - Note: only specific models support image inputs Getting Started Tips - Feel free to try any button, most of them come with built-in tooltips. - Recommend clicking all examples below in order to get familiar with onPanda Annotation Requirements - If you are not using onPanda for data annotation, you can ignore this section - Prefer “candidate continuation”; if no suitable candidate exists, use “double-click edit” for problematic chunks - Delete non-annotation-related history before saving Advanced Features - Select & rewrite: select a span of text to rewrite; rewritten text will be marked with a blue background - Candidate chunks: - Right-click or Ctrl+click a candidate to replace the current chunk - Middle-click or Alt+click a candidate to copy it to the clipboard examples: clearjoketools🤖 browser-agent🐱 petcodex/ccGUI-agenttokenizertemplatepoemcountAIMEimagevideocontinuemulti-turnannotate dialog: Tools configs empty candidate empty loaded empty system:[#1](https://onpanda.diyer22.com/#message-1) Send➡️ rendered markdown: <\|PLACEHOLDER\|> --- user:[#2](https://onpanda.diyer22.com/#message-2) Send➡️ rendered markdown: <\|PLACEHOLDER\|> --- unknown: model: `unknown_model` rendered markdown No.1request, waiting response from model: `cyankiwi/Qwen3.5-2B-AWQ-4bit` CancelEdit selection ``` [] ``` --- No.1request, waiting response from model: `cyankiwi/Qwen3.5-2B-AWQ-4bit` 1 new message: user: Send➡️ rendered markdown: <\|PLACEHOLDER\|> --- control parameter: - English - 中文 - endpoint-name—cyankiwi/Qwen3.5-2B-AWQ-4bit - on-panda-tag—cyankiwi/Qwen3.5-2B-AWQ-4bit - default-agent-tag—step-3.7-flash - audio-tag—stepaudio-3-chat-preview Change the control parameter: {"max\_tokens":1024}	diyer22	5	0
🟧 echo.x ⭐	The original X post says: “I spent two years building this interactive tool to let you steer LLMs and agents at the token level.” It introdu	Lei Yang (@diyerxx)	—	—
🟠 reddit	Steer LLMs and Agents at the Token Level: An interactive tool for token visualization & control, model inspection and data annotation. LocalLLaMA	Fancy_Fanqi77	121	37

source

object

author

score

comments

🟧 hn

Show HN: OnPanda – Steer LLMs and agents at the token level

Retrieved article excerpt

Open article · Retrieved 2026-09-18T20:22:52.470751+00:00

English

as Data Annotator:

## onPanda: on-Policy Alignment Data Annotator

`Scaling up your data efficiency with token-level supervision.` [[Project Page](https://on-panda.github.io/research/)]   
  

**onPanda: Token-Level Control for LLMs and Agents**

👉  Usage:   

**Please read the [introduction](https://on-panda.github.io/introduction/?lang=en-US) first**

  
         
  

### onPanda Instructions:

**Basic Features**

- Probability visualization: responses are composed of token chunks; the color under each chunk reflects its probability (green = high, red = low)
- Candidate continuations: hover over response text to see candidate chunks; click a candidate to continue from it
- Double-click to edit: double-click a chunk to modify it, then the model continues from your edit

**Image Features**

- You can paste images, audio and video directly into the input box
- Single-click an image to zoom in/out, double-click to open it
- Note: only specific models support image inputs

**Getting Started Tips**

- Feel free to try any button, most of them come with built-in tooltips.
- Recommend clicking all examples below in order to get familiar with onPanda

**Annotation Requirements**

- If you are not using onPanda for data annotation, you can ignore this section
- Prefer “candidate continuation”; if no suitable candidate exists, use “double-click edit” for problematic chunks
- Delete non-annotation-related history before saving

**Advanced Features**

- Select & rewrite: select a span of text to rewrite; rewritten text will be marked with a blue background
- Candidate chunks:
  - Right-click or Ctrl+click a candidate to replace the current chunk
  - Middle-click or Alt+click a candidate to copy it to the clipboard

examples:

clearjoketools🤖 browser-agent🐱 petcodex/ccGUI-agenttokenizertemplatepoemcountAIMEimagevideocontinuemulti-turnannotate

**dialog:**

Tools 

configs

empty

candidate

empty

loaded

empty

system:[#1](https://onpanda.diyer22.com/#message-1)

**Send➡️**

rendered markdown:

<|PLACEHOLDER|>

---

user:[#2](https://onpanda.diyer22.com/#message-2)

**Send➡️**

rendered markdown:

<|PLACEHOLDER|>

---

unknown:

model: `unknown_model` rendered markdown

**No.1**request, waiting response from model:  
`cyankiwi/Qwen3.5-2B-AWQ-4bit`

CancelEdit selection

```
[]
```

---

**No.1**request, waiting response from model:  
`cyankiwi/Qwen3.5-2B-AWQ-4bit`

1

new message:

user:

**Send➡️**

rendered markdown:

<|PLACEHOLDER|>

---

**control parameter:**

- English
- 中文

- endpoint-name—cyankiwi/Qwen3.5-2B-AWQ-4bit
- on-panda-tag—cyankiwi/Qwen3.5-2B-AWQ-4bit
- default-agent-tag—step-3.7-flash
- audio-tag—stepaudio-3-chat-preview

Change the control parameter: {"max\_tokens":1024}

diyer22

🟧 echo.x ⭐

The original X post says: “I spent two years building this interactive tool to let you steer LLMs and agents at the token level.” It introdu

Lei Yang (@diyerxx)

—

🟠 reddit

Steer LLMs and Agents at the Token Level: An interactive tool for token visualization & control, model inspection and data annotation.

LocalLLaMA

Fancy_Fanqi77

121

Interpretation history

2026-09-19T05:27:12Z
Reddit adds distribution and a creator-supplied self-hosting command, not independent validation of the inspect–edit–resume workflow. The tool remains a concrete candidate for hands-on testing, with model logprob availability and safe agent-state restoration unresolved.
2026-09-19T05:21:32Z
evidence attached: reddit.post.1wkc4c9 — This is direct coverage of the existing onPanda release, describing its token editing, branching, tool-call control, and harness integrations.
2026-09-18T20:55:30Z
grounded: converges/medium — onPanda’s claimed inspect–edit–resume workflow converges with Scott’s Observable Autonomy principle and offers a concrete debugging approach worth testing again
2026-09-18T20:50:26Z
origin walked (codex/luna, conf 0.99): anchor hn.story.49759013 -> echo.x.9403e44cdc by Lei Yang (@diyerxx)
2026-09-18T20:48:39Z
case created — The builder's announcement and accessible application establish a usable artifact with concrete controls, distinct from passive token-uncertainty visualization.

Decision trace

10-07 02:36drop_targetsquiet through full ladder or over cap 8
09-20 08:23review_screenThe added comment only restates the already documented token editing and resumed-generation behavior without independent verification or a consequential new fact.
09-20 05:20sensor_dirtycomment_update
09-19 23:31review_screenThe changes add positive reactions and a suggestion about diffing artifacts, while retaining existing comments; they provide no new implementation result, contradiction, release, access change, or con
09-19 22:20sensor_dirtycomment_update
09-19 15:27repriceReddit adds distribution and a creator-supplied self-hosting command, not independent validation of the inspect–edit–resume workflow. The tool remains a concrete candidate for hands-on testing, with m
09-19 15:21attachThis is direct coverage of the existing onPanda release, describing its token editing, branching, tool-call control, and harness integrations.
09-19 15:21propose_attachThis is direct coverage of the existing onPanda release, describing its token editing, branching, tool-call control, and harness integrations.
09-19 06:55groundonPanda’s claimed inspect–edit–resume workflow converges with Scott’s Observable Autonomy principle and offers a concrete debugging approach worth testing against Ask’s multi-format tool-call parsing
09-19 06:50promote_anchororigin walk conf 0.99
09-19 06:48createThe builder's announcement and accessible application establish a usable artifact with concrete controls, distinct from passive token-uncertainty visualization.