每个工具配一个示例提示。把任意一个粘贴到一个全新的代理会话里,看看这个工具能做什么。
Six prompt patterns that turn vague questions into tight answers.
诚实的答案不是某一款产品，而是一套组合：选一个你已经在用的智能体，给它只读的银行数据访问权限，然后用大白话问钱的问题。
The most common error in agent-generated spending summaries is counting both the card swipes and the checking payment that covers them. One sentence of prompt fixes it.
Bank data labels a rent payment to your landlord the same way it labels moving money to savings: a transfer. Here's how to teach your agent which transfers count as real spending.
Merchants rename billing descriptors constantly, so one subscription can show up as two or three different merchants in your transaction history. Here's the three-signal recipe for catching a rename with an agent.
夏天电费翻倍,冬天燃气费翻三倍。这里是 12 个月的提示词模式,能让你的 agent 不再把谎言当成年度均值。
All 29 AI apps that can connect to a remote MCP server in 2026, in one list: auth method, config file, and a setup guide for each. Nobody else maintains this well, so we do.
Track monthly rent, confirm it posted, spot unexpected fees. Two prompts to start.
Monthly grocery spend, across every store, split between in-person and delivery.
Every recurring charge, ranked by cost. Find the ones you forgot about.
Income minus expenses, top income sources, top expense categories, net number.
What percent of your take-home pay is staying in accounts instead of being spent.
Overdrafts, ATM fees, interest charges, foreign transaction fees, monthly maintenance.
Direct deposits from employers, pay cadence, YTD gross, any unexpected changes.
For LLC owners and freelancers: estimated tax math, when to send, how much.
What percent of your portfolio is in each position, sector, or asset class.
Dividend income received, which positions pay, YTD dividend yield.
Monthly fuel spend, across every gas station, to track commuting costs.
Every Amazon charge, across Prime, Whole Foods, digital purchases, AWS.
The classic latte-math question, now answered with real data.
Dining-out spend, split from groceries, across in-person and delivery.
Rideshare spending, across Uber + Lyft + taxis, monthly trend.