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Get Started Free →Show your personal model-quality trend card (failure rate, edit churn, tokens/task by model version)
.claude/skills/karanb192-receipts/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 644% | 0% |
| case-16 | ✗→✓ | ▲ Improved | -30% | 0% |
| case-20 | ✗→✓ | ▲ Improved | -55% | 0% |
| case-04 | ✓→✗ | ▼ Worse | -43% | 0% |
!node "${CLAUDE_SKILL_DIR}/../../nerf-receipts.js" --render 2>/dev/null || node "${CLAUDE_PLUGIN_ROOT}/nerf-receipts.js" --render
The card above is your own per-session flight recorder, aggregated across your recent Claude Code sessions and keyed by model id and Claude Code version — failure rate, edit churn, and tokens per task, each with a sparkline. It is recorded quietly in the background by the nerf-receipts hooks as you work.
Briefly interpret it for the user: call out the headline averages, and if a ⚠ shift line is present, restate which metric moved, by how much, and across which model change — that is the receipt that a quality shift is real, not a vibe. If the card says data is still accumulating, tell them to keep working and check back after a few more sessions. Keep it short and do not re-run any commands.
Other measured skills in the registry, with their headline benchmark lift.