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.
29 lines
1.2 KiB
Markdown
29 lines
1.2 KiB
Markdown
# Task 5: Calibrate token estimates
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**Plan**: reusable-impact-tooling
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**Status**: DONE (hook now extracts actual token counts from transcript usage fields; falls back to heuristic; weights cache reads at 10% for energy estimates)
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**Deliverable**: Updated estimation logic in `pre-compact-snapshot.sh`
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## What to do
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1. The current heuristic uses 4 bytes per token. Claude's tokenizer
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(based on BPE) averages ~3.5-4.5 bytes per token for English prose
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but varies for code, JSON, and non-English text. The transcript is
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mostly JSON with embedded code and English text.
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2. Estimate a better ratio by:
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- Sampling a known transcript and comparing byte count to the token
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count reported in API responses (if available in the transcript).
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- If API token counts are present in the transcript JSON, use them
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directly instead of estimating.
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3. The output token ratio (currently fixed at 5% of transcript) is also
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rough. Check if the transcript contains `usage` fields with actual
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output token counts.
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4. Update the script with improved heuristics or direct extraction.
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## Done when
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- Token estimates are within ~20% of actual (if verifiable) or use
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actual counts from the transcript when available.
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