Three CN Lite tasks have prompt/manifest inconsistencies (tasks 23, 127, and 386)

Confronta il data_manifest e il file_dep_graph di CN Lite con gli input impacchettati e l’indice completo del workspace per i task 23, 127 e 386. Controlla la cartella di lavoro mancante del task 23, il conteggio dei file Python del task 127 e le trascrizioni e i metadati forniti per il task 386. Il lavoro è completato quando prompt, manifest, grafi delle dipendenze e input visibili al solver descrivono in modo coerente i file disponibili.

Summary

Three Chinese Workspace-Bench Lite tasks contain inconsistencies between their prompts, manifests, and the files available in the full workspace image:

• opendatabox-workspace-bench-23
• opendatabox-workspace-bench-127
• opendatabox-workspace-bench-386

I checked each task's CN Lite metadata and packaged inputs, the complete filename index of filesys_cn.zip, and the repository's workspace construction logic.

1. Task 23: the current-inventory workbook is missing from the task manifest

The prompt asks the agent to correlate the stocktaking report, current inventory list, and inbound/outbound logs. However, the task's data_manifest and file_dep_graph omit:

当前库存物品总清单_2024-12.xlsx

The workbook does exist in the full CN workspace image at:

LogisticsManager_Workdir/后勤/库存/物品清单/当前库存物品总清单_2024-12.xlsx

The original runner normally copies the complete raw persona workspace before overlaying manifest files, so the file may remain visible in the original full-workspace evaluation. Nevertheless, the task package is not self-contained, the declared dependency graph is incomplete, and manifest-only conversions omit a source explicitly required by the prompt.

Suggested fix

Add the existing workbook to:

• data_manifest
• file_dep_graph
• Any generated setup/input manifest or solver-visible input list

No workspace image rebuild should be necessary because the workbook is already present in filesys_cn.zip.

2. Task 127: prompt says 10 Python files, but only 8 exist

The prompt says:

测试项目文件夹的python目录下有10个python文件

However, all other sources consistently show 8 files:

• The Lite data_manifest contains 8 Python files.
• The file_dep_graph contains 8 Python source nodes.
• The packaged task data contains 8 Python files.
• Research_Workdir/桌面/项目/测试项目/python/ in the full CN image contains 8 Python files.
• One rubric explicitly refers to all 8 Python files.

The files are:

1. data_process.py
2. database.py
3. image.py
4. machine_learning.py
5. parsing.py
6. utils.py
7. visualization.py
8. web_network.py

Suggested fix

Change the task text from 10 Python files to 8. No image, manifest, dependency-graph, or rubric change is otherwise required.

3. Task 386: the prompt requires transcription of four absent .m4a recordings

The prompt describes four .m4a recordings and explicitly asks the system to perform:

音频→文字→结构化决策表

The complete CN workspace image contains no .m4a files. It contains only:

• 会议录音元数据.json
• D1_上午场_转写稿.txt
• D2_下午场_转写稿.txt
• The five spreadsheet inputs used by the task

The metadata describes four recording sessions and marks ASR as completed for all four. It references four transcript paths, but only two transcript TXT files are actually supplied: D1 morning and D2 afternoon. The D1 afternoon and D2 morning transcript files are also absent.

The existing rubrics evaluate conclusions derived from the supplied transcripts, recording metadata, NPS survey, DAU logs, CRM data, and competitor report. They do not evaluate audio decoding or ASR execution.

Suggested fix

Revise the prompt to describe the supplied recording metadata and the available completed ASR transcripts, and remove the unsupported requirement to transcribe four recordings. To avoid implying that all four transcripts exist, wording such as the following would be accurate:

Analyze the supplied recording metadata and the available completed ASR transcripts.

Alternatively, add the four original .m4a files and the two missing transcript files if audio transcription is intended to remain part of the task.

Expected outcome

Please align these task prompts and manifests with the actual workspace inputs so that each task is self-contained and does not claim unavailable input files or incorrect file counts.