Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/fredchu/claude-dotfiles/earnings-setupnpx skills add fredchu/claude-dotfiles --skill earnings-setupgit clone --depth 1 https://github.com/fredchu/claude-dotfilesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/fredchu/claude-dotfiles/earnings-setup)<a href="https://agentmods.dev/skills/fredchu/claude-dotfiles/earnings-setup"><img src="https://agentmods.dev/badge/skills/fredchu/claude-dotfiles/earnings-setup.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.00717 |
| Opus 5 | $0.00037 | $0.00358 |
| Sonnet 5 | $0.00015 | $0.00143 |
| Haiku 4.5 | $0.00007 | $0.00072 |
Grade A, and why
earnings-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Earnings Setup — 財報追蹤自動化設定
檔案路徑
- 腳本目錄:
/Users/fredchu/Documents/For_Claude/scripts/earnings-autopilot/ - Ticker 清單:
/Users/fredchu/Documents/For_Claude/inbox/earnings/tickers.csv - 狀態目錄:
/Users/fredchu/Documents/For_Claude/scripts/earnings-autopilot/state/ - ical CLI:
/Users/fredchu/bin/ical
流程
Step 1: 讀取 Ticker 清單
cat /Users/fredchu/Documents/For_Claude/inbox/earnings/tickers.csv
解析 CSV（逗號分隔），取得所有 ticker symbols。 如果用戶指定特定 ticker，只處理那些。
Step 2: 查詢財報日期
對每支 ticker 執行：
python3 /Users/fredchu/Documents/For_Claude/scripts/earnings-autopilot/fetch_earnings_date.py TICKER
收集結果，分類：
- 可排程（60 天內）
- 太遠（> 60 天）— 列出但不自動排程
- 查詢失敗 — 列出供用戶處理
向用戶報告結果表格，確認要排程哪些。
Step 3: 建行事曆事件
對確認的 ticker，用 ical CLI 建事件：
/Users/fredchu/bin/ical add --title "NVDA 盤後財報" --date "2026-05-28" --calendar "個人" --allday
- 標題格式：
{TICKER} {盤前/盤後/未知} 財報 - 時間：如果知道 AMC/BMO 就標註，否則標「未知」
- 全天事件
Step 4: 建立 Cron 輪詢排程
/Users/fredchu/Documents/For_Claude/scripts/earnings-autopilot/cron_manager.sh add TICKER Q{N}_{YEAR} YYYY-MM-DD
Step 5: 建立狀態檔
確認 state/{TICKER}_{QUARTER}.json 已建立（poll_transcript.sh 會自動建立）。
Step 6: 報告
向用戶彙整報告：
- 已排程的 ticker + 財報日期 + cron 排程
- 太遠的 ticker（建議下次再設定）
- 失敗的 ticker
注意事項
- 距離 > 60 天的 ticker 列出並詢問用戶，不自動排程
- yfinance 需要安裝：
pip install yfinance - 每次只處理下一次財報，不排程更遠的未來
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 75 lines · 75 tokens per session scan A dcdce4e4e593
earnings-setup is a skill published in the GitHub repository fredchu/claude-dotfiles (2 stars, last pushed 22d ago), licensed MIT. It adds 75 tokens to every session and 717 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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