القائمة
Generate the App Store sales & downloads daily report for all live apps. Use when the user asks for a sales report, a revenue/downloads summary, daily numbers across their apps, or "跑日报".
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | sales-daily-report |
| description | Generate the App Store sales & downloads daily report for all live apps. Use when the user asks for a sales report, a revenue/downloads summary, daily numbers across their apps, or "跑日报". |
Run one sales & download report covering every live app, output as markdown.
Every step in this skill calls App Store Connect APIs. Before any other step, run:
python3 scripts/appmate_config.py check
If exit code ≠ 0, STOP. Do not invoke any other part of this skill, do not run scripts/sales_report.py. Tell the user AppMate credentials are not configured, show the precheck output verbatim, and tell them to invoke the appmate-setup skill. The downstream script also enforces this gate (exits 2 with the same message), but the explicit precheck saves you from spinning up the full 65-day fetch.
Pull ~65 days of daily reports from App Store Connect → aggregate across 5 time dimensions → totals + Top-3 apps + share + percentage change → markdown report.
| Item | Content |
|---|---|
| Trigger | python3 scripts/sales_report.py (0 args, 0 user intervention) |
| Input | data/apps_full.json (live-app list) + data/sales_cache.json (historical daily reports) |
| Output | stdout markdown + data/report.md file + Claude pastes the full markdown back into the conversation |
Zero. Fully automatic. The script generates the report → the file lands → Claude must paste the complete report into the conversation reply. It must not just say "saved to report.md" or post only a summary. The file is a side product; the conversation reply is the primary delivery.
| Dimension | Current range | Compared to |
|---|---|---|
| Yesterday | DATA_TODAY (most recent day with data) | the day before |
| Last 7 days | DATA_TODAY back 7 days | the prior 7 days |
| Last 30 days | DATA_TODAY back 30 days | the prior 30 days |
| This week | this Monday → DATA_TODAY | (shows "Data not yet published by Apple" if this week's data is not in yet) |
| This month | the 1st → DATA_TODAY | the entire previous month (not the same day range) |
data/sales_cache.json — missing dates are fetched from ASC /v1/salesReports; gzipped TSV is decoded and cached; failed dates are recorded as _error and retried next run; empty caches for the last 3 days are auto-refreshed (Apple data can be delayed).Rendered in the same language the user has been using in this conversation. Default to English; if the user has been writing in Chinese / Japanese / Spanish / etc., translate the template headers, labels and prose accordingly. App / SKU / country names stay in their original form. The script itself emits English strings — translate them on the fly when rendering back into the conversation reply if the user's language is not English.
**Yesterday ({MM-DD}) revenue ${X}** · this week ${X} · this month ${X}
If Apple has not published a range's data yet, that slot shows N/A and the per-dimension block prints > ⏳ Data not yet published by Apple.
## 🧮 Totals
### {dimension} ({range-compact})
- 💰 Revenue: **{current revenue}** · {↑↓ N%}
1. **{revenue}** ({share}%) · {↑↓ N%} · {app name}
2. **{revenue}** ({share}%) · {↑↓ N%} · {app name}
3. **{revenue}** ({share}%) · {↑↓ N%} · {app name}
- 📥 Downloads: **{current downloads}** · {↑↓ N%}
1. **{downloads}** ({share}%) · {↑↓ N%} · {app name}
2. **{downloads}** ({share}%) · {↑↓ N%} · {app name}
3. **{downloads}** ({share}%) · {↑↓ N%} · {app name}
> ⓘ Revenue is multi-currency, converted to USD via approximate FX (not finance-grade). Apple daily reports lag 1–2 days.
> This month compares against the **entire previous month**; last 7/30 days compare against the 7/30 days before that.
↑↓ N%.{rank}. **{value}** ({share}) · {change} · {app name}.Units × Developer Proceeds, converted to USD via a static 40+ currency FX table. This is an estimate (not accounting-grade — finance reconciliation uses /v1/financeReports), but cross-app relative comparison is reliable.Title is the IAP product name; Parent Identifier is the parent app's SKU. IAP units go to iap_units; IAP revenue is folded into the app's revenue_usd.Product Type Identifier): 1* / F1 / FI1 count as installs; 7* updates do not count; IA* IAP/subscription rows count toward revenue and iap_units but not downloads.# from the plugin repo root
python3 scripts/sales_report.py
No arguments. All logic runs automatically.
appmate-setup skill's ASC API credentials.aso-daily-report to investigate the ASO side, or aso-optimize to redo the metadata.Set up or troubleshoot AppMate plugin credentials and config. Use when the user wants to install, configure, or self-check AppMate, set up App Store Connect API access, or fix "config missing" errors from AppMate scripts.
Generate the ASO keyword-ranking daily report for the top-3 apps by downloads. Use when the user asks for an ASO daily report, ASO monitoring, keyword rank changes, or "跑 ASO 日报".
Deep ASO optimization for a single app — produce new App Store title, subtitle, and keyword strings. Use when the user wants to optimize or rewrite an app's ASO metadata, improve keyword rankings, run an ASO optimization pass for a specific app, or "跑 ASO 优化".
Identify the top 5-10 rivals outranking a single app on its own core keywords. Use when the user asks for competitor research, "找竞品" / "找对手" / "跑竞争对手分析", or invokes this competitor-research skill.
Generate prioritized feature recommendations for an app from reviews + competitor evidence. Use when the user wants feature ideas, product roadmap input, or "跑功能策划" for a specific app.
Generate a stage-diagnosed growth strategy for an app — a phase diagnosis plus 3-5 actionable strategies. Use when the user wants a growth plan, growth strategy, or "跑增长策略" for a specific app.