stock_add_stock

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds the data source URL and return type (pandas.DataFrame), which provides some context beyond the annotations. However, it does not disclose any potential quirks, output details, or limitations, so it's adequate but not rich.

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 brief and well-structured as a docstring, with a title, source URL, parameter, and return sections. It avoids unnecessary verbosity. The only minor redundancy is that the title line duplicates the annotation title, but this is not a significant waste.

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 read-only tool with no output schema, the description is adequate: it explains what data it returns, the parameter meaning, and the return type. However, it does not describe the returned DataFrame's columns, how the output is structured, or any caveats about data availability. Given the simple nature, this is minimally sufficient but leaves room for improvement.

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 schema has one parameter 'symbol' with 0% schema description coverage, so the description must compensate. It documents ':param symbol: 股票代码' (stock code) and ':type symbol: str', which adds essential meaning. The URL also contains an example stock code (600004), providing an implicit format hint. Yet it lacks explicit details on code format, prefix conventions, or examples, leaving some ambiguity.

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 the purpose via the title '新浪财经-发行与分配-增发' (Sina Finance - Issuance and Distribution - Additional Issuance) and the return doc '返回增发详情' (return additional issuance details), clearly indicating it retrieves additional stock issuance data for a given symbol. However, it does not distinguish itself from the many sibling stock-related tools beyond its specific sub-type, so it's clear but not fully differentiated.

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 provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or related tools. Only parameters and return type are given, with no contextual usage advice.

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