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. It does disclose a non-obvious default (unfiltered calls prioritize AI-theme stocks) and that results are announcement subjects (主旨), not full text. It says nothing about permissions, result ordering beyond the default, or pagination behavior, leaving meaningful gaps for a no-annotation tool.

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 sentence that front-loads the resource, then the data source, then the filtering behavior. Every clause earns its place with no filler, though the parenthetical source code is more for provenance than for invocation.

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 two-parameter, no-annotation read tool with no output schema, the description covers the resource, source, filtering, and default behavior, and clarifies that the returned data is headline subjects. What remains missing (return shape details, auth) is minor for this tool class.

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%, so the baseline is 3, but the description adds real meaning beyond the schema by clarifying that `code` is optional and defining what happens when it is omitted — the schema only labels it '股票代號' with no optionality semantics. The `limit` bounds are left to the schema, which already documents them.

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 (台股上市公司每日重大訊息主旨) and even names the upstream data source (證交所 t187ap04_L), which clearly distinguishes it from sibling tools like get_tw_dividend or get_tw_market_quotes. It is not tautological and an agent can identify the target data without opening the schema.

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 clause '可依代號篩選；不填則 AI 題材股優先' gives a usage hint and the default behavior when the filter is omitted, which is genuinely useful. However, it never states when to prefer this tool over alternatives (e.g. general stock news vs. theme tools), so usage is only implied.

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