{"slug":"opensensenova-sn-da-large-file-analysis","source_name":"opensensenova/sn-da-large-file-analysis","name":"Opensensenova/Sn Da Large File Analysis","description":"万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取（iter_rows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**：①数据行数 ≥ 10k（由 sn-da-excel-workflow 的行数评估步骤触发）；②用户出现触发词：大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing；③直接使用 pd.read_excel() 导致超时或内存溢出；④用户明确要求对大规模数据集进行高性能处理。仅不用于：小于 10k 行的常规 Excel 分析（使用 sn-da-excel-workflow 即可）。","version":1,"lift":{"pass_rate_delta_pts":27.27,"pass_rate_pct":86.4,"total_cases":22,"passed_cases":19,"tokens_delta_pct":145.1,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-04T18:28:13.830253+00:00"},"skill_score":0.8636,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":27.27,"with_pass_pct":86.4,"without_pass_pct":59.1,"tokens_delta_pct":145.1,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":22,"verdict":"mixed","never_hurt":true,"completed_at":"2026-08-04T18:28:13.830253+00:00","run_id":"2ead8c02-f044-4910-b9a2-6dc80106c288","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"MIT","install_count":0,"manifest_hash":"bb03e84439dad17982072fe985064f9e7b48a357592f2e0c12575d2d7df42310","raw_url":"https://app.decimal.ai/s/opensensenova-sn-da-large-file-analysis/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/opensensenova-sn-da-large-file-analysis"}