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Summarize estimate accuracy from the assistant time log.
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实测评分 未实测
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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: $ARGUMENTS
Optional flags:
--category <name> — restrict to one category (release, pr, build, ...)--since YYYY-MM-DD — only include entries with timestamp >= date--abandon-stale — mark pending entries older than 30 days as abandoned--show-misses — print the top 5 worst misses with surrounding textRead the log
LOG=workspace/estimate-log/log.jsonl
[ -s "$LOG" ] || { echo "No estimates logged yet."; exit 0; }
Apply filters
FILTERED=$(jq -c --arg cat "$CATEGORY" --arg since "$SINCE" '
select(
(($cat == "" or .category == $cat))
and (($since == "" or .timestamp >= $since))
)
' "$LOG")
Compute stats per category (only kind=="estimate" AND status=="completed")
For each category:
n — countmedian_ratio — median of actual / expectedp25 / p75 — quartilesover_count — entries where ratio > 1.2under_count — entries where ratio < 0.8on_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.
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)
...
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.
(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. ...
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.
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.)
--abandon-stale mutates the log.2.5x but n=3, treat it as a rough heuristic, not a precise correction.log.jsonl directly) when generating a new estimate in a high-bias category, and explicitly inflate./track-estimate — start tracking an estimate/finish-estimate — close one out还没有评价。欢迎分享你的使用感受。
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Accept HQ membership invites from a magic link or raw token.
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Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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Generate dark ASCII banner graphics for HQ and social launch assets.
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Compare approaches to best-in-class prior art, merge existing work, verify cruft removal, and recommend the most durable design before PRD work.
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