Viking Search Tuning

When to Use

Use this skill when the user wants an external agent to evaluate and tune text search similarity for an existing AI Search application and dataset.

This first version is for similarity tuning. It defaults to text-query/text-item judging, fixes mode=UserDefined, and tunes the user-defined recall strategy, recall weights, keyword match ratio, and max retrieved count. It can optionally use text+image LLM judging when visual relevance matters; image fields are taken only from GetAppDataConfig.ImageIndexFields. It does not tune rerank, personalization, hotness, boost/bury, sort rules, serving controls, or business operating rules.

Preconditions

• an application-id is available
• a dataset-id is preferred; if omitted, the CLI can try to infer a unique search dataset from the application
• Viking auth is configured with vs auth status
• LLM config is available through vs llm login, vs llm import-env, or VIKING_LLM_BASE_URL / VIKING_LLM_API_KEY / VIKING_LLM_MODEL when generating queries or using LLM relevance labels
• a query file with sourceItemIds can be evaluated with --label-source source-item for a fast first-pass silver-label run without LLM relevance judging
• the user understands that LLM relevance labels are silver labels and should be reviewed before high-risk production changes

Commands