Generate traceable SQL queries from PMContext metric definitions and natural language questions.
npx skills add https://github.com/Wcof/PMSkill --skill pm-sql
Please help me install this Agent Skill. Skill: pm-sql Source: https://github.com/Wcof/PMSkill/tree/main/skills/delivery/pm-sql Command: npx skills add https://github.com/Wcof/PMSkill --skill pm-sql
This Skill helps turn a product or business question into production-ready SQL that matches the metric definitions in PMContext instead of guessing the logic. It reduces the common risk of writing a query that runs successfully but answers the wrong business question because the retention, user segment, or KPI definition is inconsistent.
Ask the pm-sql skill to read PMContext and your schema, explain the query logic for your business question, then generate the correct SQL with performance notes and validation checks for your target database dialect.
High-intent search queries and answers about installing and using this skill.
To generate SQL from natural language, the Skill translates business questions into plain-language logic, aligns it with PMContext metric definitions, and then constructs schema-aware SQL. This ensures queries match agreed business logic before execution.
Yes, this approach supports BigQuery, PostgreSQL, MySQL, and Snowflake dialects. It adapts the SQL output to the specific target database while flagging dialect ambiguities or missing schema information during generation.
Ensure KPI computation SQL matches business definitions by reading metric definitions and global constraints from PMContext. The Skill traces generated queries back to these explicit metric sources to prevent inconsistent reporting.
The best way to write retention analysis SQL is to validate the query logic in natural language first. The Skill explains cohort and user segment logic before generating SQL, ensuring stakeholders verify the approach.
Yes, you can get performance optimization and validation guidance. The Skill suggests indexes, partitions, or materialized views and includes validation scripts to check query results against the target database.
SQL returns wrong metrics when retention, user segment, or KPI definitions are inconsistent. This Skill solves that by applying schema-aware query construction and explicit metric-source traceability from PMContext.
peterquielExtract PostgreSQL table definitions, columns, constraints, and indexes from a local database-schema.sql file.
koya-altQuery and modify records from connected services and data warehouses.
WcofDecompose PMContext into one qualitative Objective and three measurable Key Results.
kevinlinGenerate dialect-aware SQL queries from natural-language descriptions.
