Data Profile for This Category
Data for game industry intelligent due diligence reports primarily comes from the National Press and Publication Administration game license filing database, public monthly revenue reports from game developers, survey data from third-party user behavior analysis agencies, and public disclosure information from compliance regulatory authorities. Update rhythms vary significantly: license filing information updates quarterly, monthly revenue data syncs monthly, user profile data updates weekly, and compliance risk disclosures are pushed in real time.
A single report document typically includes six core modules: basic project information, R&D team qualification certificates, license filing documents, category-by-category revenue breakdowns, compliance risk point list, and competitive benchmarking analysis. Fields include license number (string type), monthly revenue (unit: ten thousand yuan), registered user scale (unit: ten thousand people), compliance status (enumerated type), and more. Some reports also include high-definition game screenshots and financial attachments.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
These data characteristics impose multiple constraints on multi-turn dialogue and prompt engineering workflows. First, individual reports are lengthy and include extensive tables and attachments. Multi-turn dialogue context windows must support long-text processing to avoid truncating core data. Second, data update frequencies vary widely. Prompts must explicitly require calling the latest license and revenue data while restricting recall of outdated information. Third, fields have specific business units. Prompts must strictly mandate adherence to unit standards in responses to avoid unit confusion. Fourth, compliance risk points are core verification content. Multi-turn dialogue must track across three dimensions: license, revenue, and user data to ensure no gaps in the verification process.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Individual game due diligence reports often contain over 5000 characters of core business data, requiring complete chapter retention to avoid truncation |
UPLOAD_FILE_MAX_SIZE | 200 MB | Game due diligence reports often include high-definition game screenshots, multi-page revenue reports and other attachments, requiring support for larger file uploads |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Parsing due diligence documents with multi-page tables and attachments requires a longer parsing wait time |
segment length | 1000–1500 characters | Game due diligence data has many closely related fields, so segments must retain complete business units to improve recall accuracy |
recall count | Top 6 | Core game due diligence data covers six dimensions: license, revenue, compliance, users, R&D, and competitors, requiring sufficient relevant fragments to be recalled |
similarity threshold | 0.75 | Low-relevance general game information must be filtered out to retain precise data highly matched to the target due diligence project |
The parameter values provided on this page are standard recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Issue: When importing a Markdown-formatted game due diligence report, the domain prefix of embedded screenshots is lost, preventing images from loading normally during dialogue. Cause: The
IMAGE_DOMAIN_AUTO_ADDconfiguration item is not enabled, or the base path of image resources is not correctly configured during import. - Issue: After calling the revenue data query tool, the response includes the tool call JSON log at the same time, instead of only outputting the AI-organized due diligence conclusions. Cause: The
SHOW_TOOL_CALL_LOGparameter is not disabled, or the prompt does not explicitly require hiding tool execution details. - Issue: When uploading a game due diligence report that exceeds the model's context limit, a
context window exceedederror occurs, or core revenue data is truncated. Cause: Theauto_splitparameter is not set to enabled, or the segment length is set too large.
How to Confirm Configuration Is Complete
- Upload a due diligence report containing multiple game screenshots and revenue tables, check if all image links and table fields are fully retained in the parsed document.
- Initiate a multi-turn dialogue, sequentially query the project license number, monthly revenue data, and compliance risk points, check if the response covers all query dimensions without redundant tool logs.
- Upload a due diligence report with more than 100 pages, check if automatic slicing is completed and relevant data is recalled normally, with no context limit exceeded errors.
- Enter the dialogue log management page, confirm that executable log cleanup operations are available, and that the retention duration and count meet preset business requirements.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.