Language: English · 中文

yotta-mirror · 元镜 (YuanJing)

YottaMeta's deterministic learning-diagnostics skill: turn a score / answer sheet plus an item-to-knowledge map into a reproducible diagnosis report where every weak-point conclusion carries its item ids, sample size, rate and threshold.

Pure Python 3.8+ standard library, zero external dependencies; Windows + Linux + macOS; student data stays on your machine — no network, no model calls, no upload.

What it is

yotta-mirror reads a structured score sheet (CSV / TSV / stdin) and an item-to-knowledge map, then runs a deterministic pipeline: data gate → per-item statistics → score-weighted knowledge mastery → student layers and borderline students → weak-point diagnosis with evidence → Markdown / JSON report.

It is a teaching-improvement aid, not a student evaluation tool. It never produces rankings, comments, or predictions, and every conclusion can be re-computed from the archived inputs.

Core value

• Evidence for every conclusion — each weak point lists its items, respondents, rate and the threshold used.
• Deterministic — the same data and thresholds produce the same report; only `generated_a