write-query Skill
Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc. Published by anthropics in knowledge-work-plugins.
Decision snapshot
Is this a fit?
Database workflows, Deployment, Data analysis, Writing
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Copy skill directory
22 days ago · Apache-2.0 license
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What is write-query Skill?
Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc. Published by anthropics in knowledge-work-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Database workflows
- Deployment
- Data analysis
- Writing
- Database workflows use cases
Declared skill metadata
- Source file: data/skills/write-query/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use write-query Skill
- Use it for database workflows.
- Use it for deployment.
- Use it for data analysis.
- Use it for writing.
Built with
Editorial notes
Source
- Creator: anthropics
- Repository: anthropics/knowledge-work-plugins
- Skill file: data/skills/write-query/SKILL.md
What it does
Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc.
Skill instructions
/write-query - Write Optimized SQL If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md. Write a SQL query from a natural language description, optimized for your specific SQL dialect and following best practices. Usage /write-query <description of what data you need Workflow 1. Understand the Request Parse the user's description to identify: - Output columns: What fields should the result include? - Filters: What conditions limit the data (time ranges, segments, statuses)? - Aggregations: Are there GROUP BY operations, counts, sums, averages? - Joins: Does this require combining multiple tables? - Ordering: How should results be sorted? - Limits: Is there a top-N or sample requirement? 2. Determine SQL Dialect If the user's SQL dialect is not already known, ask which they use: - PostgreSQL (including Aurora, RDS, Supabase, Neon) - Snowflake - BigQuery (Google Cloud) - Redshift (Amazon) - Databricks SQL - MySQL (including Aurora MySQL, Planet
Verified compatibility and discovery
Frequently asked questions
What is write-query?
write-query is a open-source AI agent skill with Copy skill directory. Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a.
Who is write-query best for?
write-query is best for reusing agent instructions, scripts, and references, database workflows, deployment workflows, data analysis workflows.
How do I install write-query?
Install or run write-query using Copy skill directory. Check write-query for the latest setup command.
Is write-query actively maintained?
write-query may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.