JSON Processor

JSON query, validate, diff, transform, format, flatten, and stats toolkit with a jq-like interface. Uses Python stdlib only — no external dependencies. Use when Codex needs to: (1) Query JSON with JSONPath expressions ($.key[*].sub), (2) Validate JSON against a schema, (3) Diff two JSON files for changes, (4) Transform JSON with jq-like expressions, (5) Pretty-print or flatten deeply nested JSON, (6) Analyze JSON structure statistics.

JSON Processor (json-processor)

Query, validate, diff, transform, and analyze JSON — all with Python stdlib.

Quick start

bash

# Query
python3 skills/json-processor/scripts/json_processor.py query data.json "$.store.book[*].title"

# Validate
python3 skills/json-processor/scripts/json_processor.py validate data.json --schema schema.json

# Diff
python3 skills/json-processor/scripts/json_processor.py diff old.json new.json

# Transform (jq-like)
python3 skills/json-processor/scripts/json_processor.py transform data.json --jq '{names: .[].name}'

# Pretty-print
python3 skills/json-processor/scripts/json_processor.py format data.json --indent 2

# Flatten nested JSON
python3 skills/json-processor/scripts/json_processor.py flatten data.json

# Stats
python3 skills/json-processor/scripts/json_processor.py stats data.json

Commands

query — JSONPath-style query

bash

python3 json_processor.py query data.json "$.store.book[*].title"
python3 json_processor.py query data.json "$.store.bicycle.color"
python3 json_processor.py query data.json "$[0].name"

Supports: $.key, .key.sub, [0], [*], mixed like .store.book[*].title

validate — JSON Schema validation

bash

python3 json_processor.py validate data.json --schema schema.json

Conforms to JSON Schema draft-07 subset: type, enum, pattern, min/maxLength, min/maximum, required, properties, items, additionalProperties.

diff — Recursive JSON diff

bash

python3 json_processor.py diff old.json new.json

Output:

text

📋 Differences (3):
  $.name: "Old App" → "New App"
  $.version: added → "2.0.0"
  $.features[1]: "logging" → "telemetry"

transform — jq-like transform

bash

python3 json_processor.py transform data.json --jq '.name'
python3 json_processor.py transform data.json --jq '{persons: .[].name}'
python3 json_processor.py transform data.json --jq '.[].items[0]'

format — Pretty-print JSON

bash

python3 json_processor.py format data.json
python3 json_processor.py format data.json --indent 4 --sort-keys
python3 json_processor.py format data.json --compact
python3 json_processor.py format data.json --output pretty.json
cat data.json | python3 json_processor.py format -

flatten — Flatten nested JSON to dot-notation

bash

python3 json_processor.py flatten data.json
# {"user.name": "Alice", "user.age": 30, "tags[0]": "admin"}

stats — JSON structure statistics

bash

python3 json_processor.py stats data.json
# 📊 JSON Statistics
#   Total nodes:     142
#   Max depth:       5
#   Types:           dict: 28, list: 6, str: 80, int: 22, bool: 6
#   Top keys:        name: 15, id: 15, type: 12

Requirements

• Python 3.6+ (stdlib only — no pip install needed)
• No external dependencies
• Works on Linux, macOS, Windows