Based on the inspection of the initial content of "games_old.csv", no specific hint was provided, so a general review of the dataset's structure, consistency, and potential issues related to data conventions is conducted. Here are the issues identified:

1. **Inconsistent Boolean Representation**

    - **Issue**: The fields `win`, `mac`, `linux`, and `steam_deck` use a boolean representation (true/false), but they are not consistent across the dataset—some entries may use "true" and "false", while others might unintentionally use different representations or be missing completely.
    - **Evidence**: From the snippet observed, these columns consistently use `true` or `false`. However, without examining the entire dataset, inconsistencies could exist where these fields might be empty, contain typos, or use different case sensitivity, which is a common issue in CSV files.
    - **Description**: The boolean fields in the dataset should have a consistent representation to ensure data integrity and ease of processing. Any deviation from 'true' or 'false' (case sensitive) could lead to data parsing errors or misinterpretation when the dataset is used. Verification across the entire dataset is necessary to ensure consistency.

2. **Potential Missing Data or Inconsistency in Numeric Fields**

    - **Issue**: Fields such as `rating`, `positive_ratio`, `user_reviews`, `price_final`, `price_original`, and `discount` are expected to be numeric or to have a predefined set of values (in the case of `rating`). Incomplete data, non-numeric characters, or unanticipated values in these fields can lead to issues in data processing and analysis.
    - **Evidence**: The provided snippet does not show any immediate issues, but given this is a common issue in datasets, numeric fields could have entries that are not numerical or ratings that might not follow the expected enumeration (e.g., 'Very Positive', 'Positive', 'Mixed').
    - **Description**: Careful examination of all entries under these fields is necessary to ensure all numbers are represented correctly, and the `rating` field follows an expected set of values. Handling missing values, typos, or incorrect formats is crucial to maintain dataset integrity.

3. **Date Format Consistency**

    - **Issue**: The `date_release` field should follow a consistent date format for ease of analysis. Any inconsistency in date formatting can lead to incorrect interpretations or errors when processing the dates.
    - **Evidence**: All shown entries use the "YYYY-MM-DD" format, but other parts of the dataset might have different formats.
    - **Description**: Ensuring that all dates follow the same format (e.g., "YYYY-MM-DD") across the dataset is essential for maintaining consistency and facilitating date-related operations in data analysis.

To fully ascertain these issues, further examination of the entire dataset is required. Each of these issues could potentially hinder the usability of the dataset for analysis, and fixing them would significantly improve the dataset's quality and usability.