Perform schema-driven JSON transformations using composable jq scripts.
npx skills add https://github.com/skogai/marketplace --skill skogai-jq
Please help me install this Agent Skill. Skill: skogai-jq Source: https://github.com/skogai/marketplace/tree/main/skogai-jq Command: npx skills add https://github.com/skogai/marketplace --skill skogai-jq
This Skill solves the complexity of manipulating nested JSON structures, filtering large datasets, and ensuring data consistency across AI agent workflows by providing a standardized, testable library of jq transformations.
Use the skogai-jq skill to extract the user email field from the provided data.json file using the crud-get transformation.
High-intent search queries and answers about installing and using this skill.
Filter large JSON datasets with jq by chaining composable scripts through standard Unix pipes. This approach enables sequential array filtering and path operations to extract specific records from extensive nested API responses.
Extract specific fields from a large API response by piping the output of a get operation directly into a filter operation. This schema-driven transformation ensures data consistency and precise field extraction across AI agent workflows.
Yes, you need jq version 1.6 or higher to execute the transformation logic and verify data integrity. This version requirement ensures compatibility with the library of over 60 composable scripts used for JSON array processing.
You can chain multiple jq transformations together using standard Unix pipes to build complex data processing workflows. This composable pipeline architecture allows you to sequentially apply operations like get and filter to nested JSON structures.
JSON transformations fail on nested structures when operations lack a clear input and output schema contract. Using schema-driven transformations ensures predictable results and prevents data consistency errors across complex AI agent data processing tasks.
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