time-calibrate
Solidmeasure your real CC throughput against the time rule's matrix, using lore.db
AI & Automation 29 stars
7 forks Updated 2 days ago MIT
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<!-- tested with: claude code v2.1.122 -->
# /time-calibrate
re-measure your personal throughput and produce a diff report against the generic baseline in `plugins/cc/rules/time.md`.
## what to do when invoked
1. **check for `~/.claude/lore.db`** via `Bash`:
```bash
test -r "$HOME/.claude/lore.db" && echo present || echo absent
```
2. **if absent**, explain and stop:
- the calibration needs session history in `~/.claude/lore.db`.
- that database is built by the `lore` plugin from `~/.claude/projects/`.
- install via `/plugin install lore@anipotts`, run `/lore:graph`, then re-run `/time-calibrate`.
- do not fail loudly. one-screen message, no stack traces.
3. **if present**, resolve active effort (same precedence as `/time-estimate`) and current model, then run the calibration SQL via `Bash` + `sqlite3 -readonly`.
## calibration SQL
paste into `sqlite3 -readonly ~/.claude/lore.db <<SQL ... SQL` or use a heredoc. all queries are parameter-free and read-only.
```sql
-- A. session-length bucket distribution
SELECT
CASE
WHEN duration_wall_seconds < 300 THEN '1_under_5min'
WHEN duration_wall_seconds < 900 THEN '2_5to15'
WHEN duration_wall_seconds < 1800 THEN '3_15to30'
WHEN duration_wall_seconds < 3600 THEN '4_30to60'
WHEN duration_wall_seconds < 7200 THEN '5_60to120'
ELSE '6_over120'
END AS bucket,
COUNT(*) AS n,
ROUND(AVG(duration_wall_seconds)/60.0, 1) AS mean_wall_min,
ROUND(AVG(duration_active_seconds)/60.0, 1) AS...
Details
- Author
- anipotts
- Repository
- anipotts/claude-code-tips
- Created
- 7 months ago
- Last Updated
- 2 days ago
- Language
- Python
- License
- MIT
Integrates with
Bundled in these plugins
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