找台灣電商目前的優惠：今天跌到歷史新低的商品、折扣最深的商品，或某品類的最低價。使用者問「今天有什麼好康／降價」「有什麼便宜的○○」時使用。
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | 優惠類型：lowest（跌到歷史新低，預設）｜discount（折扣最深） | |
| limit | No | 回傳筆數，預設 15，最多 30 | |
| category | No | 可選，指定品類看該品類最低價，例如「氣炸鍋」「藍牙喇叭」 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It explains what the tool does (find deals) but does not disclose data freshness, source limitations, rate limits, or any side effects. For a read-only tool, this is moderate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a concise paragraph that front-loads purpose and then gives usage guidance. Every sentence is informative with no wasted words. It could be slightly more structured but is effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers tool purpose, parameters, and usage context adequately. However, it does not describe the return format or any error/edge case behavior, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions. The description adds value by indicating defaults (type='lowest', limit=15) and providing usage examples (e.g., category for specific items). This goes beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds deals (historical lows, deepest discounts, category lowest price). It specifies the domain (Taiwan e-commerce) and resource (deals). However, it does not explicitly differentiate from sibling tools like category_price_range or compare_prices.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use: when the user asks about daily deals/discounts or cheap items. This provides clear usage context but omits when not to use or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools have clearly distinct purposes, such as price comparison vs. price history vs. store safety. However, there is some overlap between compare_prices, cross_channel_gaps, and price_match_check, which all involve comparing prices across channels. The descriptions help differentiate them, but ambiguity remains for agents.
Tool names use snake_case but vary in structure: some start with verbs (compare_prices, find_deals), others with nouns (category_price_range, price_match_check). There is no strict verb_noun pattern, and 'should_i_buy_now' is a full phrase, breaking consistency.
17 tools cover a wide range of e-commerce assistance tasks without being overwhelming. The count is appropriate for the domain, though a few tools (e.g., price_match_check vs. should_i_buy_now) could potentially be merged without losing functionality.
The tool set covers most common user needs in Taiwanese e-commerce: product search, price comparison, historical trends, deals, store safety, tech detection, and currency conversion. Missing operations include user-specific features (e.g., watchlist) but the core lifecycle is well-represented.
