131 lines
4.0 KiB
Markdown
131 lines
4.0 KiB
Markdown
# Telemetry Report Skill
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Track agent activity and report to telemetry system for meta-learning.
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## Report Agent Invocation
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Note: The actual telemetry collection happens automatically via hooks (SubagentStop hook).
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This skill provides utility functions for commands to access telemetry data.
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```bash
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# Read current session's agent invocations
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# The SubagentStop hook automatically records agent names to session state
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if [ -n "$SESSION_ID" ]; then
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SESSION_FILE="plugins/psd-claude-coding-system/meta/.session_state_${SESSION_ID}"
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if [ -f "$SESSION_FILE" ]; then
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AGENTS_INVOKED=$(grep "^AGENTS=" "$SESSION_FILE" | cut -d= -f2)
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echo "Agents invoked this session: $AGENTS_INVOKED"
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fi
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fi
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```
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## Query Telemetry for Patterns
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```bash
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# Check which agents work well together
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# Useful for meta-learning and optimization
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TELEMETRY_FILE="plugins/psd-claude-coding-system/meta/telemetry.json"
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if [ -f "$TELEMETRY_FILE" ] && command -v jq &> /dev/null; then
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# Find most common agent combinations for /work command
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echo "=== Most Common Agent Combinations for /work ==="
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jq -r '.executions[] | select(.command == "work") | .agents_invoked | join(",")' "$TELEMETRY_FILE" \
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| sort | uniq -c | sort -rn | head -5
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# Find average duration by command
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echo -e "\n=== Average Duration by Command ==="
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jq -r '.executions | group_by(.command) | map({command: .[0].command, avg_duration: (map(.duration_ms) | add / length)}) | .[]' "$TELEMETRY_FILE"
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# Find commands with highest success rate
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echo -e "\n=== Success Rates by Command ==="
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jq -r '.executions | group_by(.command) | map({command: .[0].command, success_rate: ((map(select(.success == true)) | length) / length * 100)}) | .[]' "$TELEMETRY_FILE"
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fi
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```
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## Track Parallel Execution
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```bash
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# When invoking multiple agents in parallel, track the pattern
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if [ -n "$SESSION_ID" ]; then
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SESSION_FILE="plugins/psd-claude-coding-system/meta/.session_state_${SESSION_ID}"
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# Mark that this session used parallel execution
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echo "PARALLEL=true" >> "$SESSION_FILE"
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# Track which agents ran in parallel
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echo "PARALLEL_GROUP=$AGENT_LIST" >> "$SESSION_FILE"
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# The Stop hook will read these and add to telemetry.json
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fi
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```
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## Get Recommendations from History
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```bash
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# Based on current issue/context, get recommendations for which agents to invoke
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if [ -f "$TELEMETRY_FILE" ] && command -v jq &> /dev/null; then
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# For similar issues (by keyword), what agents were successful?
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KEYWORDS=$(echo "$ISSUE_TITLE" | tr '[:upper:]' '[:lower:]')
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echo "=== Recommended Agents Based on Similar Issues ==="
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# This is a placeholder - real implementation would use more sophisticated matching
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jq -r ".executions[] | select(.success == true) | select(.command == \"work\") | .agents_invoked[]" "$TELEMETRY_FILE" \
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| sort | uniq -c | sort -rn | head -3
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fi
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```
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## Report Command Metrics
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```bash
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# At end of command execution, report key metrics for telemetry
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echo "=== Command Execution Metrics ==="
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echo "Command: $COMMAND_NAME"
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echo "Duration: ${DURATION_MS}ms"
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echo "Agents Invoked: $AGENTS_INVOKED"
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echo "Files Modified: $FILES_MODIFIED"
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echo "Tests Run: $TESTS_RUN"
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echo "Success: $SUCCESS"
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# These metrics are automatically captured by the Stop hook
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# which reads from session state and writes to telemetry.json
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```
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## Usage
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### In Commands
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```bash
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# At start of command
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SESSION_ID="${RANDOM}_${RANDOM}" # Generated by Claude Code
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COMMAND_NAME="work"
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START_TIME=$(date +%s%3N)
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# During execution, agents are invoked
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# SubagentStop hook automatically tracks them
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# At end of command (Stop hook does this automatically)
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END_TIME=$(date +%s%3N)
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DURATION_MS=$((END_TIME - START_TIME))
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# Stop hook reads session state and updates telemetry.json with:
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# - command name
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# - duration
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# - agents invoked
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# - success/failure
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# - parallel execution (if applicable)
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```
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### For Meta-Learning
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```bash
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# Meta-learning commands can query telemetry for insights
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# Include Query Telemetry for Patterns section
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# Include Get Recommendations from History section
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```
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