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Compute Peter Zhou learning overview reports. Use for total wrong counts, subject breakdown, mastery progress, repeat-correction markers, weak knowledge tags, correction candidates, and recent source/correction activity.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Generate and print correction practice, then grade returned answer sheets. Use for CorrectionPaper PDFs, PDF/PNG printing, original redo, generated similar practice, PracticeQuestionRecord lifecycle, returned scan/photo/PDF grading, and mastery counters.
Generate structured wrong-question explanations and rich local teaching pages. Use for ExplanationArtifact caching, crop re-interpretation, Xiaohei-style teaching illustration plans, verified optional video recommendations, and TeachAny-style local ExplanationPage output.
Create reusable graph-grounded system knowledge lessons for recurring weak topics. Use for learning-unit selection, agent teaching drafts, controlled explanatory animation, linked practice, and archived HTML courseware.
Store, validate, review, confirm, and query Peter Zhou mistake-bank records. Use for RawMistakeRecord persistence, SourceDocument status, is_wrong review, id allocation, crop refs, and script-owned JSON writes.
Recognize wrong questions from scanned/photo/PDF papers using model-native vision. Use for source manifests, page order reasoning, teacher-mark interpretation, unmarked-paper grading, and RecognitionResult creation.
Student-facing wrong-question super-teacher navigator for scanned/photo/PDF student papers. Use when the user starts Peter Zhou, asks for learning status or next actions, recognizes wrong questions, stores a mistake bank, explains mistakes, generates or prints correction practice, grades returned papers, learns a knowledge point, or reports a Peter Zhou problem from an installed user host.
| name | peter-zhou-overview |
| description | Compute Peter Zhou learning overview reports. Use for total wrong counts, subject breakdown, mastery progress, repeat-correction markers, weak knowledge tags, correction candidates, and recent source/correction activity. |
Use this subskill when the user asks for progress, mastery, weak points, or what to practice next.
Core contract:
scripts/knowledge_overview.py overview.scripts/chat_dashboard.py --data-dir <dir> --top-n 3. Send its Markdown directly, preserving emoji, action numbering, and links to existing local assets.⏱ 今日 10 分钟复习, route it to the resumable agent_chat_review workflow rather than generating a paper.data/; do not add these modules to the lightweight knowledge-pages/index.json.scripts/learning_profile.py show --data-dir <dir> --json when the user asks for personalized priorities or study advice. If the profile is missing, overview can still run, but personalized recommendations should ask the first-use interview first.is_wrong=true records for final wrong-question statistics.