query_index

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

With no annotations provided, the description carries the full disclosure burden — and it excels. It reveals output format/location (CSV to file_path), data source routing by symbol prefix, latency behavior (~10s for CSI), coverage limits (min only ~8 trading days for Shenzhen/Shanghai via Tencent), and error behavior (clear error + supplement guidance when minute coverage is exceeded). This is exemplary disclosure of behavioral traits.

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?

Three dense sentences with the purpose and output format front-loaded before the data-source caveats. No wasted words — every clause (latency, coverage, error behavior) earns its place. It could arguably benefit from paragraph separation for scannability, but for a single-block description it is efficiently packed.

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 6-parameter tool with no output schema, the description is thorough: it covers purpose, output destination/format, data source selection rules, latency, coverage limits, and failure behavior. Since output is written to a CSV file at file_path, a return-value description is unnecessary. The main gap is the absence of explicit sibling differentiation, which is a usage-guidelines concern rather than a completeness one.

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. The description adds genuine value beyond the schema: it explains that symbol prefix determines the data source (000xxx/399xxx vs 930xxx/950xxx) and that period=min is restricted to Shanghai/Shenzhen indices — semantics not present in the parameter descriptions. This elevates it above the baseline.

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+resource ('Query China indices') that clearly identifies the tool's domain. The resource type (indices) distinguishes it from most siblings (bonds, stocks, futures, ETFs, options, FX), though it does not explicitly name the closest alternative (query_stock) which could also fetch index-like data.

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 valuable usage context: data source routing by symbol prefix (000xxx/399xxx via Sina, 930xxx/950xxx via official site), the ~10s latency caveat for CSI series, and the period=min constraint (~8 trading days coverage, clear error + supplement guidance). However, it never explicitly names sibling alternatives or states when to prefer this tool over query_stock/query_yfinance — usage guidance is implied via data-source constraints rather than explicit tool selection rules.

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