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usage

Show what sharp costs in tokens and what it delivered, to judge its return on investment. Reads exact usage from local session transcripts; private to this machine.

معلومات المصدر

المستودع
pipeshub-ai/sharp
آخر نشاط في المصدر
١٥ أكتوبر ٢٠٢٦ في ١٩:٤٦
لغة SKILL.md المكتشفة
الإنجليزية
النجوم
٤
التفرعات
٠

خيارات التثبيت

يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.

مراجعة ملفات المصدر

اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.

عرض SKILL.md

SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
usage
description
Show what sharp costs in tokens and what it delivered, to judge its return on investment. Reads exact usage from local session transcripts; private to this machine.
argument-hint
[days, default 30]
disable-model-invocation
true
allowed-tools
Bash(node ~/.sharp/bin/sharp.mjs *)
# /sharp:usage: cost and return Measured locally over the last 30 days (if `$ARGUMENTS` names a different number of days, re-run `node ~/.sharp/bin/sharp.mjs tokens <days>`): ```! node ~/.sharp/bin/sharp.mjs tokens 30 2>/dev/null || echo "{}" ``` Write a short report (12 lines or fewer) in plain words: 1. **What sharp cost:** the notes it added (as a share of all tokens) and the extra replies it asked for, such as change summaries (tokens and share). Add the overall overhead share. Show dollars only if prices are set; otherwise say how to set them in one line. 2. **Learning you chose:** tokens spent in `/sharp:` commands. This is time you chose to invest, not overhead. 3. **What it delivered:** irreversible actions stopped for your decision, decisions recorded and looked back on, lessons saved, past lessons brought back when relevant, and how often practised lessons were applied correctly. 4. **One line of judgment:** is the overhead small relative to what it delivered? If overhead is high and value low, suggest a concrete setting change (for example `/sharp:mode light` or `#ship`). If fewer than 10 turns were measured, say the numbers are too early to judge. Never invent numbers that aren't in the data. ## How to write - Plain words. Define "token" once (a small chunk of text the AI reads or writes; cost scales with tokens). - Never mention hooks or other internals.
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