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tmet
tmet에는 werlang에서 수집한 skills 7개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
Build and update TMET backend APIs in Express. Use when changing handlers in routes/*.js, file-backed business logic in models/*.js, queue-driven async jobs, scraping/upload integrations in helpers/*.js, or response contracts under /api/matches, /api/moodle, /api/suap, /api/ai, and /api/jobs.
Validate TMET API contracts and multi-step flows, especially async job polling, generated file artifacts, and extraction -> matching -> enrollment workflows. Use when verifying behavior across routes, models, helpers, queue progress, and persisted outputs in files/.
Write and maintain TMET Jest + Supertest tests. Use when changing routes, models, helpers, queue logic, file parsing, or API contracts and you need focused coverage under tests/routes, tests/models, tests/helpers, or tests/integration.
Diagnose TMET runtime, queue, scraping, upload, and file-artifact issues. Use when investigating failing routes, stuck jobs, broken Browserless/SUAP flows, malformed CSV or JSON outputs, Docker problems, or test regressions.
Run, debug, and validate TMET with Docker Compose. Use when bringing up the current node + chrome stack, checking logs, running tests in-container, or confirming Browserless-based scraping and upload workflows.
Operate and evolve the TMET extraction to matching to CSV to Moodle-upload pipeline. Use when changing or debugging EduPage extraction, SUAP scraping, manual course or student queues, subject matching, AI matching, student/professor extraction, generated files in files/, or end-to-end operator workflow behavior.
Implement and maintain the TMET static frontend in public/. Use when changing public/index.html, browser-native ES modules in public/js/, UI components, section controllers, or request/model adapters that drive the pipeline, matching, manual queue, and students/professors workflows.