ef7cdd899e
Major addition: Complete agent evaluation framework with production-ready template. ## Added - **Resource Evaluation**: nao framework (score 3/5) - Identified critical gap: agent evaluation not documented - Technical challenge adjusted score 2/5 → 3/5 - All claims fact-checked (TypeScript 58.9%, Python 38.5%) - **Guide Section**: Agent Evaluation (guide/agent-evaluation.md, ~3K tokens) - Metrics: response quality, tool usage, performance, satisfaction - Patterns: logging hooks, unit tests, A/B testing, feedback loops - Example: analytics agent with built-in metrics - Tools: nao framework reference, Claude Code hooks integration - **AI Ecosystem**: Section 8.2 Domain-Specific Agent Frameworks - nao (Analytics Agents): Database-agnostic, built-in evaluation - Transposable patterns: context builder, evaluation hooks, DB integrations - **Template**: Analytics Agent with Evaluation (5 files, ~1K lines) - README: setup, usage, troubleshooting - Agent: SQL generator with evaluation criteria, safety rules - Hook: automated metrics logging (safety, performance, errors) - Script: analysis with stats, safety reports, recommendations - Report template: monthly evaluation format ## Changed - Agent Evaluation Guide: updated template references, verified links - Landing Site: templates count 110 → 114 - Version: 3.23.5 → 3.24.0 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
103 lines
3.2 KiB
Bash
103 lines
3.2 KiB
Bash
#!/bin/bash
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# Post-response hook for analytics agent metrics collection
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# Triggered after each agent response to log quality, performance, and safety metrics
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#
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# Setup:
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# 1. Copy to .claude/hooks/post-response-metrics.sh
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# 2. chmod +x .claude/hooks/post-response-metrics.sh
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# 3. Add to .claude/settings.json hooks.postToolUse configuration
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# 4. mkdir -p .claude/logs
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set -euo pipefail
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# Configuration
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LOG_FILE="${CLAUDE_LOGS_DIR:-.claude/logs}/analytics-metrics.jsonl"
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AGENT_NAME="analytics-agent"
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# Ensure log directory exists
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mkdir -p "$(dirname "$LOG_FILE")"
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# Extract agent ID from environment (if available)
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# Note: This assumes Claude Code exposes agent context via environment variables
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# Adjust based on actual Claude Code hook environment
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CURRENT_AGENT="${CLAUDE_AGENT_NAME:-unknown}"
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# Only log if this is the analytics agent
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if [ "$CURRENT_AGENT" != "$AGENT_NAME" ]; then
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exit 0
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fi
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# Extract SQL query from response
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# This is a simplified pattern - adjust based on actual response format
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QUERY=$(echo "$CLAUDE_RESPONSE" | grep -oP '```sql\s*\K[^`]+' | head -1 || echo "")
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# If no query found, skip logging
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if [ -z "$QUERY" ]; then
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exit 0
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fi
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# Safety check: Detect destructive operations
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if echo "$QUERY" | grep -iE '\b(DELETE|DROP|TRUNCATE|ALTER)\b' > /dev/null; then
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SAFETY="FAIL"
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SAFETY_REASON="Contains destructive operation (DELETE/DROP/TRUNCATE/ALTER)"
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else
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SAFETY="PASS"
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SAFETY_REASON=""
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fi
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# Check for UPDATE without WHERE (dangerous)
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if echo "$QUERY" | grep -iE '\bUPDATE\b' | grep -ivE '\bWHERE\b' > /dev/null; then
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SAFETY="FAIL"
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SAFETY_REASON="UPDATE without WHERE clause"
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fi
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# Performance measurement (requires database connection)
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# TODO: Configure database credentials
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# Uncomment and configure if you want actual execution time measurement
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#
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# DB_HOST="${DB_HOST:-localhost}"
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# DB_USER="${DB_USER:-readonly_user}"
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# DB_NAME="${DB_NAME:-analytics_db}"
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#
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# EXEC_TIME=$( (time psql -h "$DB_HOST" -U "$DB_USER" -d "$DB_NAME" -c "$QUERY" > /dev/null 2>&1) 2>&1 | grep real | awk '{print $2}')
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#
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# For now, set as null (requires database setup)
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EXEC_TIME="null"
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ROW_COUNT="null"
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ERROR="null"
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# Build JSON log entry
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# Using jq for proper JSON escaping (fallback to basic escaping if jq not available)
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if command -v jq > /dev/null 2>&1; then
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LOG_ENTRY=$(jq -n \
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--arg timestamp "$(date -Iseconds)" \
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--arg query "$QUERY" \
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--arg exec_time "$EXEC_TIME" \
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--arg safety "$SAFETY" \
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--arg safety_reason "$SAFETY_REASON" \
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--arg row_count "$ROW_COUNT" \
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--arg error "$ERROR" \
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'{
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timestamp: $timestamp,
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query: $query,
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exec_time: $exec_time,
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safety: $safety,
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safety_reason: $safety_reason,
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row_count: $row_count,
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error: $error
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}')
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else
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# Fallback: Basic JSON (may need escaping for special characters)
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LOG_ENTRY="{\"timestamp\":\"$(date -Iseconds)\",\"query\":\"${QUERY//\"/\\\"}\",\"exec_time\":$EXEC_TIME,\"safety\":\"$SAFETY\",\"safety_reason\":\"$SAFETY_REASON\",\"row_count\":$ROW_COUNT,\"error\":$ERROR}"
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fi
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# Append to log file
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echo "$LOG_ENTRY" >> "$LOG_FILE"
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# Optional: Alert on safety failures
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if [ "$SAFETY" = "FAIL" ]; then
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echo "⚠️ SAFETY CHECK FAILED: $SAFETY_REASON" >&2
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echo "Query: $QUERY" >&2
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fi
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exit 0
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