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jq-json-processing

jq-json-processing

github.com/laurigatesData & databases59234 installsUpdated 1d ago
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About jq-json-processing

A jq-focused skill for people processing JSON in command-line pipelines. It covers querying, filtering, transforming, validating, and troubleshooting JSON, with practical patterns and examples.

Key features

  1. 01Query and filter JSON
  2. 02Transform and combine structures
  3. 03Validate JSON syntax and structure
  4. 04Extract fields and navigate nested data
  5. 05Handle nulls and missing keys
  6. 06Troubleshoot errors and slow queries

Use cases

  1. 01Inspect API responses from curl or gh
  2. 02Filter records in shell pipelines
  3. 03Extract configuration values from JSON
  4. 04Analyze nested data and logs

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/laurigates/claude-plugins --skill jq-json-processing

After installing, type/jq-json-processingin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

evals.json
references/
common-patterns.md
troubleshooting.md

Details

From the project README

jq JSON Processing

Expert knowledge for processing, querying, and transforming JSON data using jq, the lightweight and flexible command-line JSON processor.

When to Use This Skill

Use this skill when...Use yq-yaml-processing instead when...
Extracting or filtering fields in JSON inputWorking with YAML files (Kubernetes, GH Actions, Helm)
Parsing gh, curl, or kubectl -o json responsesEditing YAML in place while preserving comments
CI pipelines on minimal images (jq is universally installed)Converting YAML → JSON before processing
Use this skill when...Use nushell-data-processing instead when...
One-off pipeline transforms that fit in a single expressionMulti-step transforms that span JSON, YAML, CSV, and TOML
Stdin-piped JSON from another commandAggregations, group-by, or visual table exploration

Core Expertise

JSON Operations

  • Query and filter JSON with path expressions
  • Transform JSON structure and shape
  • Combine, merge, and split JSON data
  • Validate JSON syntax and structure

Data Extraction

  • Extract specific fields from JSON objects
  • Filter arrays based on conditions
  • Navigate nested JSON structures
  • Handle null values and missing keys

Essential Commands

Basic Querying
# Pretty-print JSON
jq '.' file.json

# Extract specific field
jq '.fieldName' file.json

# Extract nested field
jq '.user.email' file.json

# Extract array element
jq '.[0]' file.json
jq '.items[2]' file.json
Array Operations
# Get array length
jq '.items | length' file.json

# Map over array
jq '.items | map(.name)' file.json

# Filter array
jq '.items[] | select(.active == true)' file.json
jq '.users[] | select(.age > 18)' file.json

# Sort array
jq '.items | sort_by(.name)' file.json
jq '.items | sort_by(.date) | reverse' file.json

# Get first/last elements
jq '.items | first' file.json
jq '.items | last' file.json

# Unique values
jq '.tags | unique' file.json
Object Operations
# Get all keys
jq 'keys' file.json
jq '.config | keys' file.json

# Get all values
jq '.[] | values' file.json

# Select specific fields
jq '{name, email}' file.json
jq '{name: .fullName, id: .userId}' file.json

# Add field
jq '. + {newField: "value"}' file.json

# Delete field
jq 'del(.password)' file.json

# Merge objects
jq '. * {updated: true}' file.json
Filtering and Conditions
# Select with conditions
jq 'select(.status == "active")' file.json
jq '.[] | select(.price < 100)' file.json

# Multiple conditions (AND)
jq '.[] | select(.active and .verified)' file.json
jq '.[] | select(.age > 18 and .country == "US")' file.json

# Multiple conditions (OR)
jq '.[] | select(.type == "admin" or .type == "moderator")' file.json

# Exists / has field
jq '.[] | select(has("email"))' file.json
jq 'select(.optional != null)' file.json

# Not condition
jq '.[] | select(.status != "deleted")' file.json
String Operations
# String interpolation
jq '"Hello, \(.name)"' file.json

# Convert to string
jq '.id | tostring' file.json

# String contains
jq '.[] | select(.email | contains("@gmail.com"))' file.json

# String starts/ends with
jq '.[] | select(.name | startswith("A"))' file.json
jq '.[] | select(.file | endswith(".json"))' file.json

# Split string
jq '.path | split("/")' file.json

# Join array to string
jq '.tags | join(", ")' file.json

# Lowercase/uppercase
jq '.name | ascii_downcase' file.json
jq '.name | ascii_upcase' file.json
Pipes and Composition
# Chain operations
jq '.items | map(.name) | sort | unique' file.json

# Multiple filters
jq '.users[] | select(.active) | select(.age > 18) | .email' file.json

# Group by
jq 'group_by(.category)' file.json
jq 'group_by(.status) | map({status: .[0].status, count: length})' file.json
Output Formatting
# Compact output (no pretty-print)
jq -c '.' file.json

# Raw output (no quotes for strings)
jq -r '.message' file.json
jq -r '.items[] | .name' file.json

# Output as tab-separated values
jq -r '.[] | [.name, .age, .email] | @tsv' file.json

# Output as CSV
jq -r '.[] | [.name, .age, .email] | @csv' file.json

# Output as JSON array on one line
jq -c '[.items[]]' file.json
Input/Output Options
# Read from stdin
cat file.json | jq '.items'
curl -s https://api.example.com/data | jq '.results'

# Multiple input files
jq -s '.' file1.json file2.json  # Slurp into array

# Write to file
jq '.filtered' input.json > output.json

# In-place edit (use sponge from moreutils)
jq '.updated = true' file.json | sponge file.json
Advanced Patterns
# Recursive descent
jq '.. | .email? // empty' file.json

# Reduce (sum, accumulate)
jq '[.items[].price] | add' file.json
jq 'reduce .items[] as $item (0; . + $item.price)' file.json

# Variable assignment
jq '.items[] | . as $item | $item.name + " - " + ($item.price | tostring)' file.json

# Conditional (if-then-else)
jq '.items[] | if .price > 100 then "expensive" else "affordable" end' file.json
jq 'if .error then .error else .data end' file.json

# Try-catch for error handling
jq '.items[] | try .field catch "not found"' file.json

# Flatten nested arrays
jq '.items | flatten' file.json
jq '.items | flatten(1)' file.json  # Flatten one level
Real-World Examples
# Extract all emails from nested structure
jq '.. | .email? // empty' users.json

# Get unique list of all tags across items
jq '[.items[].tags[]] | unique' data.json

# Count items by status
jq 'group_by(.status) | map({status: .[0].status, count: length})' items.json

# Transform API response to simple list
jq '.results[] | {id, name: .full_name, active: .is_active}' response.json

# Filter GitHub workflow runs (recent failures)
gh run list --json status,conclusion,name,createdAt | \
  jq '.[] | select(.conclusion == "failure") | {name, createdAt}'

# Extract package.json dependencies with versions
jq '.dependencies | to_entries | map("\(.key)@\(.value)")' package.json

# Merge two JSON files
jq -s '.[0] * .[1]' base.json override.json

# Create summary from log data
jq 'group_by(.level) | map({level: .[0].level, count: length, samples: [.[].message][:3]})' logs.json

Best Practices

Query Construction

  • Start simple, build complexity incrementally
  • Test filters on small datasets first
  • Use -c flag for compact output in scripts
  • Use -r flag for raw strings (no quotes)

Performance

  • Use select() early in pipeline to reduce data
  • Use targeted queries with specific paths for large files
  • Stream large JSON with --stream flag
  • Consider jq -c for faster processing

Error Handling

  • Use ? operator for optional access: .field?
  • Use // empty to filter out nulls/errors
  • Use try-catch for graceful error handling
  • Check for field existence with has("field")

Readability

  • Break complex queries into multiple steps
  • Use variables with as $var for clarity
  • Add comments in shell scripts
  • Format multi-line jq programs for readability

Common Patterns

For task-shaped recipes (API response processing, config extraction/merge, log analysis, CSV ↔ JSON transformation), open references/common-patterns.md.

Troubleshooting

When jq reports a parse error, returns nothing, raises a type error, or is slow on a large file, open references/troubleshooting.md.

Integration with Other Tools

# With curl (API calls)
curl -s "https://api.github.com/users/octocat" | jq '.name, .bio'

# With gh CLI (GitHub operations)
gh api repos/owner/repo/issues | jq '.[] | {number, title, state}'

# With find (batch processing)
find . -name "package.json" -exec jq '.version' {} \;

# With xargs (parallel processing)
cat urls.txt | xargs -I {} curl -s {} | jq '.data'

# With yq (YAML to JSON conversion)
yq eval -o=json file.yaml | jq '.specific.field'

Quick Reference

Operators
  • .field - Access field
  • .[] - Iterate array/object
  • | - Pipe (chain operations)
  • , - Multiple outputs
  • ? - Optional (suppress errors)
  • // - Alternative operator (default value)
Functions
  • keys, values - Object keys/values
  • length - Array/object/string length
  • map(), select() - Array operations
  • sort, sort_by() - Sorting
  • group_by() - Grouping
  • unique - Remove duplicates
  • add - Sum numbers or concatenate
  • has() - Check field existence
  • type - Get value type
Type Conversions
  • tostring, tonumber - Convert types
  • @csv, @tsv, @json - Format output
  • split(), join() - String/array conversion

Installation

# macOS (Homebrew)
brew install jq

# Ubuntu/Debian
sudo apt-get install jq

# Verify installation
jq --version

Resources

Comments

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