claude
0543a43816
CC0-licensed methodology for estimating the environmental and social costs of AI conversations (20+ categories), plus a reusable toolkit for automated impact tracking in Claude Code sessions.
137 lines
5.3 KiB
Bash
Executable file
137 lines
5.3 KiB
Bash
Executable file
#!/usr/bin/env bash
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#
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# pre-compact-snapshot.sh — Snapshot impact metrics before context compaction.
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#
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# Runs as a PreCompact hook. Reads the conversation transcript, extracts
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# actual token counts when available (falls back to heuristic estimates),
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# and appends a timestamped entry to the impact log.
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#
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# Input: JSON on stdin with fields: trigger, session_id, transcript_path, cwd
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# Output: nothing on stdout (hook succeeds silently). Logs to impact-log.jsonl.
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set -euo pipefail
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HOOK_INPUT=$(cat)
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PROJECT_DIR="${CLAUDE_PROJECT_DIR:-$(echo "$HOOK_INPUT" | jq -r '.cwd')}"
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TRANSCRIPT_PATH=$(echo "$HOOK_INPUT" | jq -r '.transcript_path')
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SESSION_ID=$(echo "$HOOK_INPUT" | jq -r '.session_id')
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TRIGGER=$(echo "$HOOK_INPUT" | jq -r '.trigger')
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TIMESTAMP=$(date -u +"%Y-%m-%dT%H:%M:%SZ")
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LOG_DIR="$PROJECT_DIR/.claude/impact"
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LOG_FILE="$LOG_DIR/impact-log.jsonl"
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mkdir -p "$LOG_DIR"
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# --- Extract or estimate metrics from transcript ---
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if [ -f "$TRANSCRIPT_PATH" ]; then
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TRANSCRIPT_BYTES=$(wc -c < "$TRANSCRIPT_PATH")
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TRANSCRIPT_LINES=$(wc -l < "$TRANSCRIPT_PATH")
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# Count tool uses
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TOOL_USES=$(grep -c '"tool_use"' "$TRANSCRIPT_PATH" 2>/dev/null || echo 0)
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# Try to extract actual token counts from usage fields in the transcript.
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# The transcript contains .message.usage with input_tokens,
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# cache_creation_input_tokens, cache_read_input_tokens, output_tokens.
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USAGE_DATA=$(python3 -c "
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import json, sys
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input_tokens = 0
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cache_creation = 0
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cache_read = 0
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output_tokens = 0
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turns = 0
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with open(sys.argv[1]) as f:
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for line in f:
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try:
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d = json.loads(line.strip())
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u = d.get('message', {}).get('usage')
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if u and 'input_tokens' in u:
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turns += 1
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input_tokens += u.get('input_tokens', 0)
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cache_creation += u.get('cache_creation_input_tokens', 0)
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cache_read += u.get('cache_read_input_tokens', 0)
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output_tokens += u.get('output_tokens', 0)
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except Exception:
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pass
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# Print as tab-separated for easy shell parsing
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print(f'{turns}\t{input_tokens}\t{cache_creation}\t{cache_read}\t{output_tokens}')
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" "$TRANSCRIPT_PATH" 2>/dev/null || echo "")
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if [ -n "$USAGE_DATA" ] && [ "$(echo "$USAGE_DATA" | cut -f1)" -gt 0 ] 2>/dev/null; then
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# Actual token counts available
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TOKEN_SOURCE="actual"
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ASSISTANT_TURNS=$(echo "$USAGE_DATA" | cut -f1)
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INPUT_TOKENS=$(echo "$USAGE_DATA" | cut -f2)
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CACHE_CREATION=$(echo "$USAGE_DATA" | cut -f3)
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CACHE_READ=$(echo "$USAGE_DATA" | cut -f4)
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OUTPUT_TOKENS=$(echo "$USAGE_DATA" | cut -f5)
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# Cumulative input = all tokens that went through the model.
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# Cache reads are cheaper (~10-20% of full compute), so we weight them.
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# Full-cost tokens: input_tokens + cache_creation_input_tokens
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# Reduced-cost tokens: cache_read_input_tokens (weight at 0.1x for energy)
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FULL_COST_INPUT=$(( INPUT_TOKENS + CACHE_CREATION ))
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CACHE_READ_EFFECTIVE=$(( CACHE_READ / 10 ))
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CUMULATIVE_INPUT=$(( FULL_COST_INPUT + CACHE_READ_EFFECTIVE ))
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# Also track raw total for the log
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CUMULATIVE_INPUT_RAW=$(( INPUT_TOKENS + CACHE_CREATION + CACHE_READ ))
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else
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# Fallback: heuristic estimation
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TOKEN_SOURCE="heuristic"
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ESTIMATED_TOKENS=$((TRANSCRIPT_BYTES / 4))
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ASSISTANT_TURNS=$(grep -c '"role":\s*"assistant"' "$TRANSCRIPT_PATH" 2>/dev/null || echo 0)
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if [ "$ASSISTANT_TURNS" -gt 0 ]; then
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AVG_CONTEXT=$((ESTIMATED_TOKENS / 2))
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CUMULATIVE_INPUT=$((AVG_CONTEXT * ASSISTANT_TURNS))
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else
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CUMULATIVE_INPUT=$ESTIMATED_TOKENS
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fi
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CUMULATIVE_INPUT_RAW=$CUMULATIVE_INPUT
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OUTPUT_TOKENS=$((ESTIMATED_TOKENS / 20))
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CACHE_CREATION=0
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CACHE_READ=0
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INPUT_TOKENS=0
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fi
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# --- Cost estimates ---
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# Energy: 0.003 Wh per 1K input tokens, 0.015 Wh per 1K output tokens, PUE 1.2
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# Using integer arithmetic in centiwatt-hours to avoid bc dependency
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INPUT_CWH=$(( CUMULATIVE_INPUT * 3 / 10000 )) # 0.003 Wh/1K = 3 cWh/10K
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OUTPUT_CWH=$(( OUTPUT_TOKENS * 15 / 10000 )) # 0.015 Wh/1K = 15 cWh/10K
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ENERGY_CWH=$(( (INPUT_CWH + OUTPUT_CWH) * 12 / 10 )) # PUE 1.2
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ENERGY_WH=$(( ENERGY_CWH / 100 ))
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# CO2: 325g/kWh -> 0.325g/Wh -> 325 mg/Wh
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CO2_MG=$(( ENERGY_WH * 325 ))
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CO2_G=$(( CO2_MG / 1000 ))
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# Financial: $15/M input, $75/M output (in cents)
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# Use effective cumulative input (cache-weighted) for cost too
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COST_INPUT_CENTS=$(( CUMULATIVE_INPUT * 15 / 10000 )) # $15/M = 1.5c/100K
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COST_OUTPUT_CENTS=$(( OUTPUT_TOKENS * 75 / 10000 ))
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COST_CENTS=$(( COST_INPUT_CENTS + COST_OUTPUT_CENTS ))
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else
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TRANSCRIPT_BYTES=0
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TRANSCRIPT_LINES=0
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ASSISTANT_TURNS=0
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TOOL_USES=0
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CUMULATIVE_INPUT=0
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CUMULATIVE_INPUT_RAW=0
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OUTPUT_TOKENS=0
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CACHE_CREATION=0
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CACHE_READ=0
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ENERGY_WH=0
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CO2_G=0
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COST_CENTS=0
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TOKEN_SOURCE="none"
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fi
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# --- Write log entry ---
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cat >> "$LOG_FILE" <<EOF
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{"timestamp":"$TIMESTAMP","session_id":"$SESSION_ID","trigger":"$TRIGGER","token_source":"$TOKEN_SOURCE","transcript_bytes":$TRANSCRIPT_BYTES,"transcript_lines":$TRANSCRIPT_LINES,"assistant_turns":$ASSISTANT_TURNS,"tool_uses":$TOOL_USES,"cumulative_input_tokens":$CUMULATIVE_INPUT,"cumulative_input_raw":$CUMULATIVE_INPUT_RAW,"cache_creation_tokens":$CACHE_CREATION,"cache_read_tokens":$CACHE_READ,"output_tokens":$OUTPUT_TOKENS,"energy_wh":$ENERGY_WH,"co2_g":$CO2_G,"cost_cents":$COST_CENTS}
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EOF
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exit 0
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