Project Info

NerTzh Metrics Control Plane

Devpost

NerTzh Metrics Control Plane NerTzh is an evidence-first local developer control plane for inspecting Bybit spot market metrics, reconciliation state, Context Bridge evidence, and optional protected GPT-5.6/Codex-assisted analysis. What it solves Trading systems expose several independent states: market data, generated signals, database rows, exchange orders, and project-agent context. NerTzh makes those states inspectable from one judge-facing surface without pretending that saved evidence is a live trade or an AI decision. How it works FastAPI control plane and responsive local viewer on port 8081. Optional attended Bybit demo engine isolated on port 8082. PostgreSQL for engine state and reconciliation. DuckDB plus Markdown for the local Context Bridge. Read-only health, metrics, validation, order-status and context routes. Protected chat boundary requiring an explicit local control token. Virtual local TP/SL monitoring; native exchange TP/SL orders are disabled in the judge path. Demo-safe configuration with live trading disabled by default. The viewer does not start the trading engine, call a remote model, or spend API credits when opened. The optional analysis route is explicit and protected. Bybit execution remains outside the judge-facing read-only surface. Codex and GPT-5.6 Codex was used to audit the architecture, reconcile WebSocket/PostgreSQL/Bybit state, simplify the delivery path, harden the demo boundary, prepare documentation, and verify the captured walkthrough. GPT-5.6/Codex-assisted analysis is integrated as an optional protected capability, not as an automatic trading dependency. The submitted video and repository describe those boundaries explicitly. Evidence and delivery Repository: https://github.com/NerTzhuLz/NerTzh Demo release and video assets: https://github.com/NerTzhuLz/NerTzh/releases/tag/v0.1.0-build-week The release includes a verified 1080p H.264/AAC render with English narration and burned-in subtitles, plus a 4K upscale. Safety The repository defaults to demo mode and excludes secrets. The engine is attended and separated from the judge surface. No live/mainnet execution, autonomous profit claim, or native TP/SL claim is made by this submission. Built during OpenAI Build Week The project demonstrates how Codex and GPT-5.6-assisted engineering can turn a trading prototype into a reproducible, auditable developer tool.

Analysis

Compare with all teams

View

Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • FastAPIIn code
  • HTMLIn code
  • OpenAIIn code
  • PythonIn code
  • PostgreSQLClaimed

4 of 5 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

  • CodexConfig

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

555 KB

Source files

105

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

0 stars