calibration-report

name	calibration-report
description	Summarize estimate accuracy from the assistant time log.
allowed-tools	Bash, Read

/calibration-report - Estimate Accuracy by Category

Read workspace/estimate-log/log.jsonl and summarize how well the assistant's estimates match actuals. Output a table per category showing median ratio, sample size, and a suggested inflation multiplier.

Input: $ARGUMENTS

Optional flags:

• --category <name> — restrict to one category (release, pr, build, ...)
• --since YYYY-MM-DD — only include entries with timestamp >= date
• --abandon-stale — mark pending entries older than 30 days as abandoned
• --show-misses — print the top 5 worst misses with surrounding text

Steps

1. Read the log

   LOG=workspace/estimate-log/log.jsonl
   [ -s "$LOG" ] || { echo "No estimates logged yet."; exit 0; }
   

2. Apply filters

   FILTERED=$(jq -c --arg cat "$CATEGORY" --arg since "$SINCE" '
     select(
       (($cat == "" or .category == $cat))
       and (($since == "" or .timestamp >= $since))
     )
   ' "$LOG")
   

3. Compute stats per category (only kind=="estimate" AND status=="completed")

   For each category:

   • n — count
   • median_ratio — median of actual / expected
   • p25 / p75 — quartiles
   • over_count — entries where ratio > 1.2
   • under_count — entries where ratio < 0.8
   • on_count — entries within ±20%
   • suggested_multiplier — round(median_ratio * 4) / 4 (rounded to 0.25)

   Use jq + simple awk math. For median, sort then pick middle.

4. Render report

   ESTIMATE CALIBRATION REPORT
   ===========================
   Window: <since> to <now>  |  Total entries: <n>  |  Completed: <c>  |  Pending: <p>
   
   Category    n   median_ratio   p25-p75      verdict-mix       suggest-multiply-by
   --------    --  ------------   ----------   ---------------   --------------------
   release     5   0.40           0.30-0.50    1on/0over/4under  0.5x  (you over-estimate by 2x)
   build       3   2.40           1.80-3.00    0on/3over/0under  2.5x  (you under-estimate by 2.5x)
   infra       4   1.10           0.90-1.30    3on/1over/0under  1.0x  (well calibrated)
   pr          2   0.55           0.50-0.60    0on/0over/2under  0.5x  (you over-estimate by 2x)
   ...
   

5. Show pending count + stale flagging

   Pending: 3 entries
   Stale (>30d, no /finish-estimate): 1
     est_abc1234   "..."   estimated 14 days ago
   Run /calibration-report --abandon-stale to clear them.
   

6. (Optional) --show-misses — print top 5 worst misses (completed entries with highest |log(ratio)|):

   Worst misses:
   1. est_xyz   release    expected 60 min, actual 5 min   12.0x over
      "going to take ~1 hr for the npm release of hq-cloud@5.7.1"
   2. ...
   

7. Recommendation block Highlight categories with n >= 3 and |log(median_ratio)| > log(1.5) — those are systematically wrong. Recommend the agent inflate future estimates in those categories by suggested_multiplier.

Implementation note

Pure jq + awk + bash. No Python, no installs. Keep it < 100 lines.

For median in awk:

{ a[NR] = $1 } END {
  asort(a)
  if (NR % 2) print a[(NR+1)/2]
  else print (a[NR/2] + a[NR/2+1]) / 2
}

(GNU awk has asort; BSD awk on macOS does too as of recent versions. Fall back to sort -n | awk if needed.)

Notes

• This report is read-only by default. Only --abandon-stale mutates the log.
• Suggested multipliers should be applied loosely — if the median says 2.5x but n=3, treat it as a rough heuristic, not a precise correction.
• The agent should consult this report (or read log.jsonl directly) when generating a new estimate in a high-bias category, and explicitly inflate.

See also

• /track-estimate — start tracking an estimate
• /finish-estimate — close one out