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 provenance (self-made), stance (neutral reference), content structure (includes breakdown), and a policy decision around not redistributing CNN data. It does not mention output format or update cadence, but for a zero-parameter read-only data tool this is reasonably transparent.

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 core content is front-loaded and compact, and the CNN exclusion is material enough to keep. The English restatement partially repeats the Chinese text, making it slightly less tight than a 5, but the overall description remains short and scannable.

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 tool with no output schema, the description covers what the tool returns (a composite score with sub-items), its scope (Taiwan only), and a key exclusion (no CNN F&G). It could say more about the output range or its relationship to taiwan_market_overview, but it is sufficient for an agent to select and invoke it 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 has no parameters, so schema description coverage is trivially 100%. Per the rubric, a 0-parameter tool gets a baseline of 4; the description adds no parameter detail because none is needed.

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 identifies the resource: Taiwan market sentiment as a self-made, neutral composite score with sub-items. It also states what the tool is not (US CNN Fear & Greed). It lacks an explicit verb like 'returns' and does not contrast with overlapping siblings such as taiwan_market_overview, but the core purpose is unambiguous.

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 a clear when-to-use signal (Taiwan market sentiment) and an explicit when-not signal (CNN F&G data), pointing to /us-sentiment as the alternative. It does not discuss when to prefer this over sibling tools like taiwan_market_overview or business_climate, but the main routing decision is resolved.

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