
errrc/kaogong-shuati
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App (Assessment/gongkao/Student/Provincial/Enterprise): A library of studies. Chinese: I don't have the money to take the exam。
Overview
Chinese: Keywords: Examinations / Examinations / Brushing / Survey / Comment / Enterprise / Kaogong / Gongkao / xingce / Shenlun ⭐ If it helps you, welcome point / - This will allow more candidates to find it on GitHub. Zero reliance on the Node.js backend + full application of the local SQLite library: modular tree brush, error book, learning statistics, embedded interpolable AI smart body (methodology analysis, retrospectation of opposable points, transfer of graphic reasoning, study recommendations, import resolution). The same code serves both the browser and Android App (Capacitor). 📄: This warehouse code is open with MIT permission; public/vendor/, ref-skills/** Copyright and Compliance** is for personal study only and is not for commercial or secondary distribution**. Data acquisition tools are not distributed with the warehouse. tiku.db Node ends/reassemble-tiku.mjs can be restored at once (script with MD5 self-certification) because 100MB limits exceeding the GitHub single file have been cut into tiku.db.part-* part. - Modular tree encapsulation: knowledge tree for measuring six main modules (political theory/common sense judgement/linguistic understanding/quantitative relationship/judgmental reasoning/information analysis); Jurisprudence Standard Five (summarization/comprehensive analysis/formulation/implementation/article writing); Responsive/programming tree - number of nodes/real-time aggregations done/corrected - theme cover: single/multi-selection/judgment/uncertainty + statement/compulsory subject matter; answer card quality UI (Ocean Depths theme, two shallow modes, priority for moving end + desktop alignment) - record end-of-service library (practice.).
Overview (machine translated)
Chinese name: ** No money to take a test** Keyword: examination / assessment / encapsulation / survey / statement / enterprise / Kaogong / gongkao / xingce / Shenlun
If it helps you, welcome point Star / watch – this will allow more candidates to find it on GitHub.
Zero reliance on the Node.js backend + full application of the local SQLite library: modular tree brush, error book, learning statistics, embedded interpolable AI smart body (methodology analysis, retrospectation of opposable points, transfer of graphic reasoning, study recommendations, import resolution). The same code serves both the browser and Android App (Capacitor).
** Licence**: This warehouse code is open with MIT permission; copies of third-party components and skill packages in [[T0], [T1], [T2] and [T2] retain their respective upstream licences and are not subject to MIT authorization.
** Copyright and compliance**: copyrights are distributed to sources such as the repository data [[[T3] / [[T4] and the title schematics], with authorization from the source,** for personal study only, not for commercial or secondary distribution**. Data acquisition tools are not distributed with the warehouse. [[T5] Operation [[T7] after cloning] [Returnable once (script with MD5 self-certification) due to cutting of 100MB in excess of the GitHub single file into [[T6] volume.
Functional properties
** brush**
- Modular tree brushing: knowledge tree measuring six main modules (political theory/common sense judgement/verbal understanding/quantitative relationship/judgment/information analysis); Judicature Standard Five (summarizing/comprehensive analysis/formulation/implementation/article writing); Responsive/professive clustering - number of nodes/doed/corrected in real time
- Topical coverage: Single/multi-selection/judgement/uncertainty + opposability/ overall subject matter; answercard UI (Ocean Designs theme, Deep Two Modes, Move End Priority + Desktop Fit)
- Recording the end of the service ([[T8], cell phone/computer sync): error book, collection, redoing, statistical overview, nearly 7 days trend
- Custom repository: import of own-title (text pasting/PDF/Excel/photogram OCR), AI Auxiliary breaking into structured topics to support subject-based management
AI capabilities (five intelligents, OpenAI compatibility protocols, each independent base url / api key / model, effective as soon as it is replaced, the hint tape version history can roll back)
- System analysis AI: Injecting acoustic/survey methodology skills pool, presented in [examining point/correct item resolution/resolvertion techniques] format
- ** adjective revision AI**: rating by points, automatic extraction of dry points, with cross scoring of given material
This page was translated automatically. Technical details may differ from the original.
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Install
npx skillfish add errrc/kaogong-shuati