gemini-json-parsing
Gemini JSON Parsing
🚨 MANDATORY: Invoke gemini-cli-docs First
STOP - Before providing ANY response about Gemini JSON output:
- INVOKE
gemini-cli-docsskill- QUERY for the specific output format topic
- BASE all responses EXCLUSIVELY on official documentation loaded
Overview
Skill for parsing Gemini CLI's structured output formats. Essential for integration workflows where Claude needs to process Gemini's responses programmatically.
When to Use This Skill
Keywords: parse gemini output, json output, stream json, gemini stats, token usage, jq parsing, gemini response
Use this skill when:
- Extracting responses from Gemini JSON output
- Analyzing token usage and costs
- Parsing tool call statistics
- Handling errors from Gemini CLI
- Building automation pipelines
Output Formats
Standard JSON (--output-format json)
Single JSON object returned after completion:
{
"response": "The main AI-generated content",
"stats": {
"models": {
"gemini-2.5-pro": {
"api": {
"totalRequests": 2,
"totalErrors": 0,
"totalLatencyMs": 5053
},
"tokens": {
"prompt": 24939,
"candidates": 20,
"total": 25113,
"cached": 21263,
"thoughts": 154,
"tool": 0
}
}
},
"tools": {
"totalCalls": 1,
"totalSuccess": 1,
"totalFail": 0,
"totalDurationMs": 1881,
"totalDecisions": {
"accept": 0,
"reject": 0,
"modify": 0,
"auto_accept": 1
},
"byName": {
"google_web_search": {
"count": 1,
"success": 1,
"fail": 0,
"durationMs": 1881
}
}
},
"files": {
"totalLinesAdded": 0,
"totalLinesRemoved": 0
}
},
"error": {
"type": "ApiError",
"message": "Error description",
"code": 500
}
}
Stream JSON (--output-format stream-json)
Newline-delimited JSON (JSONL) with real-time events:
| Event Type | Description | Fields |
|---|---|---|
init |
Session start | session_id, model, timestamp |
message |
User/assistant messages | role, content, timestamp |
tool_use |
Tool call requests | tool_name, tool_id, parameters |
tool_result |
Tool execution results | tool_id, status, output |
error |
Non-fatal errors | type, message |
result |
Final outcome | status, stats |
Example stream:
{"type":"init","timestamp":"2025-10-10T12:00:00.000Z","session_id":"abc123","model":"gemini-2.5-flash"}
{"type":"message","role":"user","content":"List files","timestamp":"2025-10-10T12:00:01.000Z"}
{"type":"tool_use","tool_name":"Bash","tool_id":"bash-123","parameters":{"command":"ls -la"}}
{"type":"tool_result","tool_id":"bash-123","status":"success","output":"file1.txt\nfile2.txt"}
{"type":"message","role":"assistant","content":"Here are the files...","delta":true}
{"type":"result","status":"success","stats":{"total_tokens":250}}
Common Extraction Patterns
Extract Response Text
# Get main response
gemini "query" --output-format json | jq -r '.response'
# With error handling
result=$(gemini "query" --output-format json)
if echo "$result" | jq -e '.error' > /dev/null 2>&1; then
echo "Error: $(echo "$result" | jq -r '.error.message')"
else
echo "$result" | jq -r '.response'
fi
Token Statistics
# Total tokens used
echo "$result" | jq '.stats.models | to_entries | map(.value.tokens.total) | add'
# Cached tokens (cost savings)
echo "$result" | jq '.stats.models | to_entries | map(.value.tokens.cached) | add'
# Billable tokens
total=$(echo "$result" | jq '.stats.models | to_entries | map(.value.tokens.total) | add')
cached=$(echo "$result" | jq '.stats.models | to_entries | map(.value.tokens.cached) | add')
echo "Billable: $((total - cached))"
# Tokens by model
echo "$result" | jq '.stats.models | to_entries[] | "\(.key): \(.value.tokens.total) tokens"'
Tool Call Analysis
# Total tool calls
echo "$result" | jq '.stats.tools.totalCalls'
# List tools used
echo "$result" | jq -r '.stats.tools.byName | keys | join(", ")'
# Tool success rate
total=$(echo "$result" | jq '.stats.tools.totalCalls')
success=$(echo "$result" | jq '.stats.tools.totalSuccess')
echo "Success rate: $((success * 100 / total))%"
# Detailed tool stats
echo "$result" | jq '.stats.tools.byName | to_entries[] | "\(.key): \(.value.count) calls, \(.value.durationMs)ms"'
Model Usage
# List models used
echo "$result" | jq -r '.stats.models | keys | join(", ")'
# Model latency
echo "$result" | jq '.stats.models | to_entries[] | "\(.key): \(.value.api.totalLatencyMs)ms"'
# Request counts
echo "$result" | jq '.stats.models | to_entries[] | "\(.key): \(.value.api.totalRequests) requests"'
Error Handling
# Check for errors
if echo "$result" | jq -e '.error' > /dev/null 2>&1; then
error_type=$(echo "$result" | jq -r '.error.type // "Unknown"')
error_msg=$(echo "$result" | jq -r '.error.message // "No message"')
error_code=$(echo "$result" | jq -r '.error.code // "N/A"')
echo "Error [$error_type]: $error_msg (code: $error_code)"
exit 1
fi
File Modifications
# Lines changed
echo "$result" | jq '"Added: \(.stats.files.totalLinesAdded), Removed: \(.stats.files.totalLinesRemoved)"'
Stream Processing
Filter by Event Type
# Get only tool results
gemini --output-format stream-json -p "query" | jq -r 'select(.type == "tool_result")'
# Get only errors
gemini --output-format stream-json -p "query" | jq -r 'select(.type == "error")'
# Get assistant messages
gemini --output-format stream-json -p "query" | jq -r 'select(.type == "message" and .role == "assistant") | .content'
Real-time Monitoring
# Watch tool calls as they happen
gemini --output-format stream-json -p "analyze code" | while read line; do
type=$(echo "$line" | jq -r '.type')
case "$type" in
tool_use)
tool=$(echo "$line" | jq -r '.tool_name')
echo "[TOOL] Calling: $tool"
;;
tool_result)
status=$(echo "$line" | jq -r '.status')
echo "[RESULT] Status: $status"
;;
error)
msg=$(echo "$line" | jq -r '.message')
echo "[ERROR] $msg"
;;
esac
done
Quick Reference
| What | jq Command |
|---|---|
| Response text | .response |
| Total tokens | .stats.models | to_entries | map(.value.tokens.total) | add |
| Cached tokens | .stats.models | to_entries | map(.value.tokens.cached) | add |
| Tool calls | .stats.tools.totalCalls |
| Tools used | .stats.tools.byName | keys | join(", ") |
| Models used | .stats.models | keys | join(", ") |
| Error message | .error.message // "none" |
| Error type | .error.type // "none" |
| Lines added | .stats.files.totalLinesAdded |
| Lines removed | .stats.files.totalLinesRemoved |
| Total latency | .stats.models | to_entries | map(.value.api.totalLatencyMs) | add |
Complete Example
#!/bin/bash
# Analyze code and report stats
result=$(cat src/main.ts | gemini "Review this code for security issues" --output-format json)
# Check for errors
if echo "$result" | jq -e '.error' > /dev/null 2>&1; then
echo "Error: $(echo "$result" | jq -r '.error.message')"
exit 1
fi
# Extract response
echo "=== Security Review ==="
echo "$result" | jq -r '.response'
# Report stats
echo ""
echo "=== Stats ==="
total=$(echo "$result" | jq '.stats.models | to_entries | map(.value.tokens.total) | add // 0')
cached=$(echo "$result" | jq '.stats.models | to_entries | map(.value.tokens.cached) | add // 0')
models=$(echo "$result" | jq -r '.stats.models | keys | join(", ") | if . == "" then "none" else . end')
tools=$(echo "$result" | jq '.stats.tools.totalCalls // 0')
echo "Tokens: $total (cached: $cached)"
echo "Models: $models"
echo "Tool calls: $tools"
Test Scenarios
Scenario 1: Extract Response
Query: "How do I extract the response from Gemini JSON output?" Expected Behavior:
- Skill activates on "parse gemini output" or "json output"
- Provides jq extraction pattern
Success Criteria: User receives
.responseextraction command
Scenario 2: Token Usage Analysis
Query: "How do I track token usage from Gemini CLI?" Expected Behavior:
- Skill activates on "token usage" or "gemini stats"
- Provides stats extraction patterns Success Criteria: User receives token calculation jq commands
Scenario 3: Stream Processing
Query: "How do I process Gemini CLI stream-json output?" Expected Behavior:
- Skill activates on "stream json"
- Provides JSONL processing patterns Success Criteria: User receives real-time stream processing example
References
Query gemini-cli-docs for official documentation on:
- "json output format"
- "stream-json output"
- "headless mode"
Version History
- v1.1.0 (2025-12-01): Added Test Scenarios section
- v1.0.0 (2025-11-25): Initial release
More from melodic-software/claude-code-plugins
design-thinking
Design Thinking methodology for human-centered innovation. Covers the 5-phase IDEO/Stanford d.school approach (Empathize, Define, Ideate, Prototype, Test) with workshop facilitation and exercise templates.
190plantuml-syntax
Authoritative reference for PlantUML diagram syntax. Provides UML and non-UML diagram types, syntax patterns, examples, and setup guidance for generating accurate PlantUML diagrams.
161system-prompt-engineering
Design effective system prompts for custom agents. Use when creating agent system prompts, defining agent identity and rules, or designing high-impact prompts that shape agent behavior.
141architecture-documentation
Generate architecture documents using templates with diagram integration. Use for creating C4 diagrams, viewpoint documents, and technical overviews.
126data-modeling
Data modeling with Entity-Relationship Diagrams (ERDs), data dictionaries, and conceptual/logical/physical models. Documents data structures, relationships, and attributes.
101resume-optimization
Resume structure, achievement bullet formulas, ATS optimization, and job-targeted tailoring for software engineers. Use when reviewing resumes, crafting achievement bullets, extracting keywords from job descriptions, or tailoring content for specific roles.
93