台灣加密貨幣資料

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It usefully discloses the data source and the critical limitation that a negative result does not guarantee safety, but it does not state whether the operation is read-only, what return format to expect, or any permissions or rate limits.

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?

Two sentences with zero waste. The purpose is front-loaded, followed by the essential caveat, and every phrase earns its place.

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 simple one-parameter lookup, the description covers the source list and the important false-negative caveat. It does not explain the return shape, but no output schema exists, so this is a minor gap rather than a blocking omission.

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 description coverage is 100%, so the schema already defines the single url parameter and gives an example. The description echoes '網址或網域' but adds no syntax or meaning beyond what the schema provides, making the baseline 3 appropriate.

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 states a specific verb and resource: comparing a URL or domain against the Taiwan National Police Agency 165 list of suspended scam websites. It clearly communicates the scope and decision being made, and the sibling tools are unrelated, so no sibling confusion exists.

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?

It provides clear context for when to use the tool: to determine whether a URL or domain appears on the official scam list. The caveat '查無不代表安全' gives important usage interpretation, though it does not explicitly state when not to use the tool or name alternatives, which are not needed for these unrelated siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden, and it does state what is produced (basic tax amount under the AMT plus the additional amount payable in NT$), which tells the agent this is a deterministic computation. However, it omits key behavioral assumptions: applicable tax year, the NT$6.7M exemption threshold treatment, and how crypto gains are valued/converted.

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, front-loaded sentence that names the calculation, the scope (Taiwan individual overseas income + overseas crypto gains), and the returned figures. Nothing is padded or redundant.

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?

There is no output schema, so the description usefully names the two outputs, and the inputs are fully documented. What is missing is the framing a tax calculation needs — tax year/version of the rules, threshold mechanics, and valuation basis for crypto — which leaves real ambiguity for an agent invoking it.

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 description coverage is 100%, so all four inputs including their NT$ units are already documented. The description only indirectly maps onto the inputs via the phrase 'overseas income including crypto gains', adding no format or edge-case detail beyond the schema; baseline 3 is appropriate.

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 verb (試算/estimate) and a well-defined resource: Taiwan individual overseas income under the alternative minimum tax regime, explicitly noting that overseas exchange crypto gains are included. This is unmistakably distinct from the sibling utilities (scam-domain check, USDT/TWD premium, VASP registry).

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 gives no when-to-use or when-not-to-use conditions, no prerequisites, and no alternatives — the agent must infer the scenario entirely. The siblings are unrelated enough that routing confusion is unlikely, but that is the only mitigating factor.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It discloses the data sources (BitoPro, MAX), the reference rate (international USD/TWD mid-rate), and that daily historical records are returned. However, it does not mention read-only nature, authentication, rate limits, or whether the two exchanges are reported separately.

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 single, front-loaded sentence with no wasted clauses. It directly states the subject, scope, and outputs.

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 a simple tool with one optional parameter and no output schema, the description adequately covers what is returned (latest premium percentage and daily historical records) and the source exchanges. Minor gaps remain around return shape and whether each exchange is reported separately, but the core call context is present.

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 description coverage is 100% for the single 'days' parameter, and the description adds no additional meaning about that parameter. Per the rubric, when schema coverage is high, a baseline of 3 is appropriate.

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 names a specific verb (取得/get) and a well-defined resource: USDT premium on BitoPro and MAX relative to the international USD/TWD mid-rate, plus latest premium percentage and daily history. The scope and outputs are unambiguous and no sibling tool overlaps this function.

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 never states when to use this tool, when not to use it, or what alternatives exist. It only describes the data returned, leaving usage context entirely to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. The verb 列出 clearly implies a read-only operation with no side effects, which is helpful, but the description does not mention data freshness, source, or any access requirements. It lacks deeper behavioral context beyond the obvious read semantics.

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 single, dense sentence with no filler, and the core resource and scope are front-loaded. The parenthetical list of returned fields is efficient and earns its place.

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?

With no output schema and no annotations, the description does a good job of enumerating the returned data (company, tax ID, brand, service type, and platform fees). It could be more complete by noting the return format or update cadence, but it is sufficient for an agent to call the tool correctly.

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 parameter semantics are not applicable. The baseline for zero-parameter tools is 4, and the description appropriately focuses on the returned data instead of input arguments.

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 states a specific verb (列出) and a specific resource (台灣金管會公告完成洗錢防制登記的虛擬資產服務業者), and it enumerates the returned fields. It is easily distinguishable from siblings like check_scam_domain, estimate_overseas_crypto_tax, and get_usdt_twd_premium.

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 implies usage by stating what it lists, but it does not explicitly say when to use this tool versus alternatives or name any exclusions. For a zero-parameter retrieval tool, this is minimum viable but leaves the agent to infer the context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.