教学过程中自动捕获和记录学习者的概念疑难点("为什么/是什么/怎么推/什么意思"类型的问题),保存到进度文件的"概念疑难点记录"区,形成考前回顾清单。
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只读检查一个已生成的备考工作区是否健康并报告问题,默认不做任何修改。核对 .ingest 原材料版本、 内容单元、接管队列与派生产物完整性,以及 wiki、题库、视觉证据、计划和进度的一致性。当用户怀疑 工作区有问题、建库 readiness 被阻断、或想在开始复习前体检时使用。
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Inspect a prep workspace built by exam-ingest and report health issues. This is a read-only inspector. Do NOT fix anything by default; only fix after the user explicitly grants permission. Emit a concrete issue report; never silently modify or delete files.
Activate when the user suspects the workspace is broken (missing chapters, ungradable quiz items, inconsistent progress), or when the user wants a pre-review health check before studying. Do not activate to build, teach, or grade.
references/wiki/ — chapter knowledge files (chN_*.md).references/quiz_bank.json — quiz items.references/teaching_examples.json — optional parallel teaching inventory; examples may remain here even when they are deliberately excluded from the gradable bank.references/teaching_baseline.json — append-only retention baseline for new workspaces; it must never shrink on re-ingest and must not be hand-edited.references/figure_page_index.json / references/image_question_index.json — regenerable three-sided visual coverage evidence (wiki / prompt / answer)..ingest/source_manifest.json — source-root-relative paths, source hashes, media types, and parse status..ingest/base_content_units.jsonl / content_units.jsonl — deterministic extraction baseline and the compiled view after replaying validated patches..ingest/base_chapter_phase_mappings.jsonl / chapter_phase_mappings.jsonl — explicit chapter-to-study-phase identity..ingest/review_queue.jsonl / review_patches.jsonl — typed issue lifecycle and append-only evidence-bound patch ledger..ingest/build_manifest.json / unbound_review.json — source root, page-quality accounting, input/derived hashes, and issues not yet bound to one source record.ingest_report.json — import counts, current-snapshot statistics, missing-answer alerts, and the legacy retention fallback.study_plan.md — phase plan with chapter anchors.study_state.json — the structured progress state (the SINGLE SOURCE OF TRUTH when present: phase_checklist, mistake_archive, confusion_log).study_progress.md — a GENERATED VIEW of the state (rendered phase checkpoints and recorded wrong-question IDs); stale/hand-edited when it drifts from study_state.json.Inspect read-only. Open and parse files; never write, rename, or delete. Check each item below and record every failure as a concrete issue (file path + what is wrong).
study_plan.md, confirm a matching references/wiki/chN_*.md file exists. Flag orphan chapters (wiki files no phase references) and broken links (phases pointing to absent chapters).references/quiz_bank.json: confirm type is one of the six allowed types (choice / subjective / diagram / fill_blank / true_false / code); confirm choice items carry options; treat missing keywords on subjective items as a grading-quality warning. An item without an answer must declare answer_status: unknown; in a structured workspace it also remains a blocking review issue until an evidence-backed official answer, an explicitly labeled AI answer, or an unrecoverable terminal decision is recorded.study_state.json exists, treat it as the source of truth: confirm study_progress.md is a faithful render of it (flag drift / stale hand-edits where the md disagrees with the state), and check the state's phase_checklist phases map to study_plan.md. When no study_state.json exists, audit study_progress.md directly. Either way, confirm each rendered phase-checkpoint line maps to a phase in study_plan.md and every wrong-question ID exists in references/quiz_bank.json. Note: the template anchor <!-- PHASE_CHECKLIST --> is replaced by scripts/ingest.py at generation time and is absent from a correct finished workspace — do NOT report its absence as a problem.references/teaching_baseline.json; validate its schema, exact per-chapter mapping, append-only policy, and require every baseline ID to have a same-chapter current snapshot in references/teaching_examples.json. Presence of the same ID in references/quiz_bank.json is diagnostic overlap only and never substitutes for that teaching snapshot. Only old workspaces without the baseline file may fall back to ingest_report.json.teaching_example_ids. It is valid for an ungradable worked example to be absent from the bank if the teaching layer retains it; disappearance from the current teaching layer is a blocking retention gap even when a quiz item survives. Validate the current teaching manifest's IDs, chapter/phase tags, source pages, answer source, and asset paths. Read it per chapter in tutoring; do not treat the whole manifest as a new answer source.figure_page_index.json.wiki_visual_coverage for detected material pages embedded in wiki, image_question_index.json.prompt_suspects for missing prompt context, and answer_suspects for missing answer context. A zero on one side is never evidence that the other two are complete. Require matching integrity snapshots and re-hash their declared quiz, teaching, wiki, and asset inputs; stale or missing freshness evidence blocks a new-manifest phase from being complete. Flag NUL/control-byte warnings and missing/capped pages. State that this is deterministic recall coverage, not semantic proof that every meaningful figure was found..ingest/ exists, strictly load every source, unit, mapping, issue, patch, unbound entry, and build-manifest section. Re-hash current source bytes; source drift invalidates patches and derived indexes. Require one page_anchor for every accounted page, including blank/scanned pages. Require blocking issues in pending / claimed / validated / blocked to keep readiness blocked; applied/resolved/superseded issues must agree with the ledger and compiled outputs, while unrecoverable issues remain visible warnings. Verify build-manifest hashes for the wiki, bank, retrieval index, visual/teaching manifests, and structured facts.phase_evidence plus a currently validated notebook/chNN.guide.json with profile=full; the typed validator owns the de-duplicated teaching-example + gradable-bank denominator and source-reference checks. Under standing visual, also require capabilities.artifact_ready.status=ready, matching receipt hashes, and accepted all-page QA before completion. Under chat, the typed manifest is still required but PDF is not. verified needs at least two distinct handled bank items and at least one passed; preferences.no_questions=true caps the phase at covered_unverified. A language change makes the old manifest/artifact stale until relocalized and, for visual output, rerendered and re-QA'd. Legacy workspaces without .ingest/ remain compatible but must be reported as lacking the structured completeness gate..ingest/build_manifest.json.source_root is intentionally an absolute materials-root binding and is not itself an error; report it only when missing, unreadable, moved, or inconsistent with source records.Run python <package-root>/scripts/validate_workspace.py <workspace> --json as the canonical static check and include its readiness in the report. ok=true means structurally runnable (no validation errors); it does not erase warnings or mean content-complete.
Emit a single issue list. Each entry contains: 【级别(阻断/警告/提示)】 (severity: blocker / warning / notice) + 【位置文件】 (file path) + 【现象】 (concrete symptom) + 【建议修法】 (suggested fix). End with exactly one readiness verdict: ready (no errors or warnings), usable_with_gaps (no errors, but warnings/incomplete evidence remain), or blocked (one or more errors). Never translate ok=true into ready without checking warnings.
Do NOT auto-fix. After reporting, fix item-by-item only if the user grants permission, or hand the workspace back to exam-ingest for rebuild.
Preserve these provenance labels VERBATIM when quoting them in findings: 🟢 来自资料 / 🟡 AI补充,可能与你老师讲的不完全一致 / ⚠️ AI生成答案,非老师/教材提供.
Student-facing output defaults to English (Simplified Chinese if the student opened in Chinese); the persisted study_state.json.language code (zh/en/bilingual) switches it per exam-cram's dispatch rule with single-language purity.
This skill produces no student-facing template; its report is agent-composed in the student's language. There are no locales/zh/skills/exam-audit.md or locales/en/skills/exam-audit.md pack files — compose the issue report directly in the language given by study_state.json.language:
中文 → Simplified Chinese, using the zh canonical wording in ../../docs/language-policy.mdEnglish → English, using the EN canonical vocabulary in ../../docs/language-policy.md双语 → compose zh-first with a > EN: mirror line per block (rules in ../../docs/language-policy.md)
Display aliases such as 中文, English, and 双语 are normalized by update_progress.py; route persisted state on zh, en, or bilingual. Unset language → the merged first-ask decides it; default English unless the student opened in Chinese.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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教学过程中自动捕获和记录学习者的概念疑难点("为什么/是什么/怎么推/什么意思"类型的问题),保存到进度文件的"概念疑难点记录"区,形成考前回顾清单。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
全员通关后把 错题本+笔记本+知识点窗口+wiki 编译成考前速记小抄 cheatsheet.md(每条要点带可溯源 锚点),并在视觉产物模式或用户明确要求 PDF/打印版时按指定页数渲染成打印级 PDF:按「必背结论/公式 → 有难度例题(必要时含题面图)→ 例题解答(代入公式、保留基础过程)→ 要点解释(同类题怎么办)」 四段组织。当复习收尾、用户要「考前小抄/速记/总结/打印版」时使用。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
临考前的极速备考总教练。把课件、大纲、重点与真题建成分章 wiki 和标准题库,再组织惰性授课、 题库判分、错题与疑难复盘及可选考前小抄,并持久化进度。用于期末、备考、突击、刷题、划重点、 错题与考前复习;不用于长期规划或与考试无关的写作/编程。
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备考教练的一屏速查卡:工作流、3×4 学习选择、产物偏好、工作区文件、6 大题型、来源规则与子技能路由。 用户问怎么用、有哪些模式、文件用途或支持题型时使用。
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从学生上传的课件/大纲/老师勾的重点/真题,一键初始化并验证备考工作区:解析 PDF、DOCX、PPTX、 XLSX、常见独立图片与 txt/md,建立分章节 LLM Wiki、标准题库、结构化接管队列与进度状态;仅在 Python 确实无法运行时 明确降级为手动写盘。当工作区尚未建立、资料发生变化、或建库 readiness 被阻断时使用。
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从 references/quiz_bank.json 抽取本章题目并按标准答案判分,支持选择、主观、画图、填空、判断、代码; 主观题按 keywords 要点覆盖判分,连续错两次提供提示/跳过/归档。禁止现场编题。用于阶段检查或模考。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.