v1.1.0 — Learning mode for evidence-aware mastery evaluation

RedJudge v1.1.0 adds the learning mode — an evidence-aware adversarial review of a learner's mastery of a knowledge point. Its failure target is false mastery (能背公式但换问法就崩): the learner repeats the standard answer but breaks on counter-examples, edge cases, and transfer problems.

What's new

Learning mode (new object type)

• 4-level mastery verdict bound to weighted score: 已掌握 / 部分掌握 / 表面掌握 / 未掌握 (mastered / partial / shaky / not_learned).
• 已掌握 is intentionally hard to earn: weighted total ≥ 75 AND 反混淆 ≥ 7 AND no dimension below 6.
• Default starting assumption is 表面掌握, not "probably fine". Verification is required to upgrade.

5-dimension mastery rubric

Dimension	Weight	What it checks
概念清晰度	25%	Can the learner state the concept in own words and name its preconditions?
边界精度	20%	Can the learner name where the concept stops being valid?
程序熟练度	20%	Can the learner execute the standard procedure on a fresh problem?
迁移	20%	Can the learner apply the concept to a differently phrased problem?
反混淆	15%	Can the learner name an adjacent concept and articulate the difference?

反混淆 (Anti-Confusion) is the core dimension — false mastery hides here. The learner must distinguish the target concept from at least one adjacent one. If they cannot, the verdict cap is 部分掌握.

Mandatory output blocks (non-negotiable even in quick mode)

• 🎯 薄弱点 — concrete sub-skills or sub-steps where the learner failed, with evidence (which problem, which mistake).
• 🔀 混淆点 — adjacent concepts the learner appears to conflate with this one, with the specific mis-pairing and the discriminator that would break the tie.
• 📋 重学补丁 — concrete exercises or checks for re-study. Not "review chapter X" — a specific re-do.

Diagnostic lenses (Multi-Perspective Review)

Replaces stakeholder roles (target user, investor, editor) with: 严苛考官, 前置知识核查, 相邻概念对比者, 迁移出题人, 课标对齐.

Chinese-only naming

All learning-mode verdict names, dimension names, block names, role names, and template headers are now Chinese. The new references/localization-rules.md codifies this convention for Chinese-facing artifacts. English terms preserved only where they are established RedJudge vocabulary or trigger tokens: Type: learning, Red Scan, Evidence Boundary, weighted total, continue / revise / abandon (legacy 3-tier).

New artifacts

• references/learning-dimensions.md — full rubric + scoring anchors + verdict mapping + anti-false-mastery rules.
• references/learning-output-format.md — full template + quick template + self-check.
• references/localization-rules.md — Chinese-only naming convention.
• examples/learning-review.md — worked example grading a learner's self-claim of mastering the quadratic formula (verdict: 表面掌握).

Trigger phrases

• RedJudge learning：判一下我对 X 掌握得怎么样
• 批改一下我做的这道题
• 我这样算掌握 X 了吗
• RedJudge learning strict (5 failure modes, ≥ 2 confusion points required)
• RedJudge learning quick (skip multi-perspective and value confirmation; keep 薄弱点 / 混淆点 / 重学补丁)

Validation

• python scripts/check-redjudge-evals.py: PASS (extended to require learning references, learning example, four-level verdict term, and 薄弱点/混淆点 terms).
• English-leakage audit on 5 learning artifacts: clean (no bilingual aliases, no English template headers).
• GitHub Actions Validate RedJudge workflow: ✅ success on commit 55e4158.
• New regression prompts added to evals/evals.json (now 8 total): learning-shaky-false-mastery, learning-mastered-real-mastery, learning-not-learned-empty-evidence.

Scope boundary

RedJudge learning mode grades and diagnoses only — it does not write lessons, examples, or step-by-step tutorials. For fresh teaching material, hand off to a teaching skill.

Links

• Changelog: https://github.com/gaoyechen/redjudge/blob/main/CHANGELOG.md
• Repository: https://github.com/gaoyechen/redjudge
• Install: npx skills add gaoyechen/redjudge

v1.0.0

RedJudge v1.0.0 is the first public GitHub release.

What this release includes

• Public packaging assets: README.md, LICENSE, evals/evals.json, showcase card, and GitHub Actions validation workflow.
• Real public install path: npx skills add gaoyechen/redjudge.
• Versioning surface: version badge, current version note, versioning section, release notes, and CHANGELOG.md.
• Agent-facing review protocol in SKILL.md with evidence boundary, red scan, multi-perspective review, value confirmation, and verdict flow.

Validation

• python scripts/check-redjudge-evals.py passed locally.
• Public clone validation passed.
• GitHub Actions validation succeeded.

Links

• Changelog: https://github.com/gaoyechen/redjudge/blob/main/CHANGELOG.md
• Repository: https://github.com/gaoyechen/redjudge