Generate and execute SQL or code queries across databases, CSVs, and files.
npx skills add https://github.com/mlld-lang/mlld --skill mlld-query
Please help me install this Agent Skill. Skill: mlld:query Source: https://github.com/mlld-lang/mlld/tree/main/plugins/mlld/skills/query Command: npx skills add https://github.com/mlld-lang/mlld --skill mlld-query
Automates cross-source data analysis by letting an LLM write SQL or code to query data, then executes it locally with zero LLM tokens, and performs parallel deep research on the filtered results.
Ask a cross-source data question and let the skill generate and execute SQL or code queries across sources, then synthesize the results.
High-intent search queries and answers about installing and using this skill.
Cross-source data analysis is handled by letting an LLM write SQL or code to query databases and CSVs, then executing it locally without LLM tokens to filter and slice the combined results.
Yes, LLM-generated SQL queries local CSV files without spending tokens by executing the generated code deterministically on your machine, enabling fast data access and cross-tabulation.
Parallel deep research on filtered data results is orchestrated through a structured synthesis workflow that runs multiple investigations concurrently on the sliced outputs.
Cross-source data discovery enforces strict read-only access for database querying, ensuring that LLM-generated SQL only retrieves data without risking modifications to the source.
Cross-tabulation and slicing across logs and documents is achieved by exposing the schema to an LLM, which then writes the code to filter the sources and apply result limits.
Limitations of LLM-assisted query generation include enforced result limits on the filtered data and strict read-only access, meaning you cannot write data back to the queried sources.
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