stock_zh_index_daily_tx

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

Annotations already declare readOnly/idempotent/openWorld, so the bar is lower, and the description adds genuinely useful behavioral context: all data is forward-adjusted (前复权) and adjustment conventions differ across providers and must not be mixed. It does not cover rate limits or response shape beyond the DataFrame return, but the key data-integrity caveat is disclosed.

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?

Purpose and source note are front-loaded, followed by param docs. The reST-style param/type lines add information rather than pure duplication, though the structure is a docstring dump rather than tightly optimized prose.

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?

All three parameters are documented with format and default semantics, the return type is given as pandas.DataFrame, and the data-adjustment caveat is present. Given annotations and the simple 3-param shape, this is essentially complete for correct invocation.

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 0%, so the description carries the load and does so well: it explains symbol requires a market-prefixed code, and that empty start_date means earliest available while empty end_date means today, plus the YYYYMMDD format. This compensates for the undocumented schema.

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+resource+source: daily-frequency historical data for stocks or indices from Tencent Securities, with custom date ranges. It also explicitly frames itself relative to the sibling stock_zh_index_daily (Sina), noting it fills gaps where Sina data is missing, so the agent can tell the two apart without opening schemas.

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 clearly states when to reach for this tool (as a complement when Sina index data is incomplete) and adds a usage caveat about not mixing adjustment methods across sites. It lacks an explicit 'when not to use' rule, but the routing context is clear.

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