
response-analyzer
by nguyenthienthanh
Aura Frog — AI-powered structured development plugin for Claude Code Turn Claude Code into a full-fledged dev platform: Aura Frog brings 24 specialized agents, a 9-phase TDD workflow, built-in quality gates and 70+ commands so your team doesn’t need to manually draft prompts — just call the right command and follow guided instructions.
SKILL.md
name: response-analyzer description: "MCP Response Analyzer pattern - Write large responses to temp files, load summaries into context" autoInvoke: false priority: medium triggers:
- "large response"
- "analyze output"
- "response:save" allowed-tools: Read, Write, Bash
MCP Response Analyzer
Priority: MEDIUM - Use for large outputs Version: 1.0.0
Purpose
Reduce context bloat by:
- Writing large responses to
/tmp/aura-frog/ - Loading only summaries into conversation context
- Referencing full data only when needed
When to Use
triggers[5]{scenario,threshold,action}:
Command output,>100 lines,Save to temp + summarize
API response,>5KB,Save JSON + extract key fields
File search results,>50 files,Save list + show top 10
Test output,>50 lines,Save full + summarize pass/fail
Build output,>100 lines,Save full + show errors only
Temp Directory Structure
/tmp/aura-frog/
├── responses/
│ ├── cmd-{timestamp}.txt # Command outputs
│ ├── api-{timestamp}.json # API responses
│ └── search-{timestamp}.txt # Search results
├── summaries/
│ └── summary-{timestamp}.md # Generated summaries
└── session/
└── {session-id}/ # Session-specific data
Usage Patterns
Pattern 1: Large Command Output
Before (bloats context):
npm test
# 500 lines of output loaded into context
After (optimized):
# Run and save
npm test > /tmp/aura-frog/responses/test-$(date +%s).txt 2>&1
# Load summary only
echo "Test Results Summary:"
grep -E "(PASS|FAIL|Tests:|Suites:)" /tmp/aura-frog/responses/test-*.txt | tail -10
Pattern 2: API Response Analysis
Before:
curl https://api.example.com/users
# Large JSON response in context
After:
# Save full response
curl https://api.example.com/users > /tmp/aura-frog/responses/api-$(date +%s).json
# Extract summary
jq '{total: .data | length, first_3: .data[:3] | map(.name)}' /tmp/aura-frog/responses/api-*.json
Pattern 3: File Search Results
Before:
find . -name "*.ts"
# 200+ files listed in context
After:
# Save full list
find . -name "*.ts" > /tmp/aura-frog/responses/search-$(date +%s).txt
# Show summary
echo "Found $(wc -l < /tmp/aura-frog/responses/search-*.txt) TypeScript files"
echo "Sample:"
head -10 /tmp/aura-frog/responses/search-*.txt
Commands
Save Response
# Save command output
bash scripts/response-save.sh "npm test" "test-results"
# Output:
# Saved to: /tmp/aura-frog/responses/test-results-1234567890.txt
# Summary: 150 tests, 148 passed, 2 failed
Load Summary
# Get summary of saved response
bash scripts/response-summary.sh test-results-1234567890
# Output:
# File: test-results-1234567890.txt
# Size: 45KB
# Lines: 500
# Key findings: 2 failed tests in auth.test.ts
Reference Full Data
# When full data needed
cat /tmp/aura-frog/responses/test-results-1234567890.txt
Integration with Workflow
workflow_integration[4]{phase,use_case,pattern}:
Phase 5a (Tests),Save test output,Pattern 1
Phase 6 (Review),Save linter output,Pattern 1
Phase 7 (Verify),Save coverage report,Pattern 1
Any,Large API responses,Pattern 2
Cleanup
# Auto-cleanup old files (run daily)
find /tmp/aura-frog -mtime +1 -delete
# Manual cleanup
rm -rf /tmp/aura-frog/responses/*
Token Savings
savings[4]{scenario,without,with,saved}:
500-line test output,~2000 tokens,~100 tokens,95%
Large JSON response,~5000 tokens,~200 tokens,96%
200 file search,~800 tokens,~100 tokens,87%
Build log,~3000 tokens,~150 tokens,95%
Best Practices
- Always summarize first - Load full data only if needed
- Use timestamps - Prevent file collisions
- Clean up regularly - Don't let temp grow
- Reference by ID - "See test-results-1234567890 for full output"
Note: This pattern is especially useful during TDD phases where test output can be verbose.
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 100以上
1ヶ月以内に更新
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
Reviews coming soon

