docs/submission-notes.md

Build Small submission notes

Project

• Name: Trace Field Notes
• Track: Backyard AI
• Space: https://huggingface.co/spaces/build-small-hackathon/trace-field-notes
• Runtime: https://build-small-hackathon-trace-field-notes.hf.space/
• GitHub: https://github.com/JacobLinCool/trace-field-notes
• Demo video: https://youtu.be/1QNZlqkl8zo
• Demo MP4 asset: https://huggingface.co/spaces/build-small-hackathon/trace-field-notes/resolve/main/assets/trace-field-notes-demo.mp4
• X post: https://x.com/JacobLinCool/status/2066160425952334155

Official pre-flight checklist

• Every model is under 32B total parameters:
  • openbmb/MiniCPM5-1B
  • nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16
  • openai/privacy-filter
• Gradio app deployed as a Space in build-small-hackathon.
• Demo video produced and uploaded to YouTube.
• Backup demo MP4 hosted as a public Space asset.
• X post published and linked from README.
• ZeroGPU usage is one Space for this app.
• README frontmatter includes track / quest tags and model metadata.

Quest / challenge eligibility

• Backyard AI: eligible. The app solves a concrete workflow problem for coding agent users.
• Best Use of Codex: eligible. Codex helped build, package, document, demo, and verify the project; GitHub commits include Codex co-author trailers.
• Best MiniCPM Build: eligible. Quick analysis uses openbmb/MiniCPM5-1B.
• Nemotron Hardware Prize: eligible. Deeper analysis uses nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16.
• Off Brand: eligible. The UI is a custom React field-notebook/trail-map experience served through gradio.Server, not stock Gradio components.
• Best Demo: eligible. The YouTube demo, backup MP4 asset, and public X post are prepared.
• Tiny Titan: not eligible because the project offers an optional 30B Nemotron path.
• Best Use of Modal: not eligible; the runtime is Hugging Face ZeroGPU / CPU.
• Best Agent: not targeted. The app is agent-callable, but the app itself is not a multi-step autonomous tool-use agent.

Submission-form summary

Trace Field Notes is a Build Small Backyard AI app for people using coding agents. Upload a Codex, Claude Code, or Pi Agent session log and the app turns the agent's visible narrative messages into a qualitative field report: where it got stuck, how it detoured, how it recovered, and whether its final claim matched its own evidence. It uses a custom React UI served by gradio.Server, a deterministic codebook analyzer, optional MiniCPM5 1B quick analysis, optional Nemotron 3 Nano 30B-A3B deeper analysis, and privacy redaction before analysis. Codex helped build, debug, document, deploy-package, and produce the narrated demo video, with Codex-attributed commits in the connected GitHub repository.