pandora/web/.agents/skills/caveman-stats

caveman-stats

Real session token receipts. No AI estimation.

What it does

Reads the current Claude Code session log directly and reports actual input/output token usage plus estimated savings versus a non-caveman baseline. Numbers come from the JSONL session log on disk — the model itself does not compute or estimate them. Output is injected by the caveman-mode-tracker hook, which intercepts /caveman-stats and returns the formatted stats as a blocked-decision reason.

Output also includes an Est. rule overhead and Est. net line whenever the savings figure above them is unambiguous (a single benchmarked mode with a known turn count — no guessing across mixed or unattributed spans). Overhead estimates the per-turn INPUT-token cost of the rules the skill injects every turn — default 1,250 tokens/turn, override with CAVEMAN_RULE_OVERHEAD_TOKENS if you've measured your own setup. Net is savings minus that overhead. On short, terse replies this can go negative — caveman's OUTPUT savings don't clear its INPUT cost — and the line says so directly instead of hiding it behind a gross-savings number. Background: docs/HONEST-NUMBERS.md.

Each run also writes a lifetime-savings suffix file used by the statusline badge (⛏ 12.4k). That badge stays a gross-savings figure on purpose — it is a glanceable summary, not a full accounting; run /caveman-stats for the net picture.

How to invoke

/caveman-stats

Example output

Session: 47 turns
Input:   12,304 tokens
Output:   3,891 tokens (caveman)
Baseline: 11,247 tokens (estimated without caveman)
Saved:    7,356 tokens (~65%)
Est. rule overhead: 58,750 (input, ~1,250/turn over 47 turns)
Est. net: -51,394 (caveman cost more than it saved for this workload — consider turning it off)

(Numbers above are illustrative — see docs/HONEST-NUMBERS.md for why short, terse-reply sessions tend to land net-negative even at a healthy output-savings percentage.)

See also

• SKILL.md — hook contract and mechanics
• Caveman README — repo overview