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data-processing

Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data.

DeepseekModel Curated skill Quality Good · 64 v1.0.0

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name data-processing description Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data. license MIT compatibility Requires jq and yq CLI tools. Install: brew install jq yq (macOS). allowed-tools Bash Read metadata {"author":"claude-mods"} Data Processing Query, filter, and transform structured data (JSON, YAML, TOML) efficiently from the command line. Tools Tool Command Use For jq jq '.key' file.json JSON processing yq yq '.key' file.yaml YAML/TOML processing jq Essentials # Extract single field jq '.name' package.json # Extract nested field jq '.scripts.build' package.json # Extract from array jq '.dependencies[0]' package.json # Extract multiple fields jq '{name, version}' package.json # Navigate deeply nested jq '.data.users[0].profile.email' response.json # Filter by condition jq '.users[] | select(.active == true)' data.json # Transform each element jq '.users | map({id, name})' data.json # Count elements jq '.users | length' data.json # Raw string output jq -r '.name' package.json yq Essentials # Extract field yq '.name' config.yaml # Extract nested yq '.services.web.image' docker-compose.yml # List all keys yq 'keys' config.yaml # List all service names (Docker Compose) yq '.services | keys' docker-compose.yml # Get container images (K8s) yq '.spec.template.spec.containers[].image' deployment.yaml # Update value (in-place) yq -i '.version = "2.0.0"' config.yaml # TOML to JSON yq -p toml -o json '.' config.toml Quick Reference Task jq yq Get field jq '.key' yq '.key' Array element jq '.[0]' yq '.[0]' Filter array jq '.[] | select(.x)' yq '.[] | select(.x)' Transform jq 'map(.x)' yq 'map(.x)' Count jq 'length' yq 'length' Keys jq 'keys' yq 'keys' Pretty print jq '.' yq '.' Compact jq -c yq -o json -I0 Raw output jq -r yq -r In-place edit - yq -i When to Use Reading package.json dependencies Parsing Docker Compose configurations Analyzing Kubernetes manifests Processing GitHub Actions workflows Extracting data from API responses Filtering large JSON datasets Config file manipulation Data format conversion Additional Resources For complete pattern libraries, load: ./references/jq-patterns.md - Arrays, filtering, transformation, aggregation, output formatting ./references/yq-patterns.md - Docker Compose, K8s, GitHub Actions, TOML, YAML modification ./references/config-files.md - package.json, tsconfig, eslint/prettier patterns
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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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