台灣各加油站品牌（台灣中油、台塑石化等）目前的加油優惠與信用卡回饋整理，附截止日；以官方公告為準。
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "get_fuel_promos"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries the full burden. It does disclose two useful behavioral traits: the output is a per-brand compilation including expiry dates, and the data is non-authoritative / may lag official announcements. It says nothing about update cadence, data source, or completeness, which limits it to a middling score.
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?
A single compact sentence that front-loads the resource (fuel promotions by brand) and appends the two most decision-relevant qualifiers (expiry dates, official-announcement caveat). Nothing is wasted and nothing is buried.
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?
For a zero-parameter read tool with no output schema, the description adequately conveys the return content (brand, discount, credit-card rebate, expiry date) and the reliability caveat. It would be fully complete if it named get_fuel_prices as the complementary tool for raw prices.
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?
The tool takes zero parameters, so per the rubric the baseline is 4. There is no parameter semantics to explain, and the description correctly spends no effort on inputs.
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?
States a specific resource with concrete scope: current fuel discount promotions and credit-card rebates across Taiwanese gas station brands (CPC, Formosa Petrochemical), with expiry dates. It is clear what the tool returns, but it never explicitly distinguishes itself from the sibling get_fuel_prices, which an agent could easily confuse it with.
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?
There is no when-to-use, when-not, or alternative-routing guidance at all. The closest thing to guidance is the freshness caveat ('subject to official announcements'), which is a disclaimer rather than a usage rule, so the agent must infer that this is the promotions tool and get_fuel_prices is the price tool.
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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