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

Beyond the readOnly/idempotent annotations, it discloses the automatic walk-back to the nearest prior trading day on non-trading dates, the one-day publication lag, the keyless Eastmoney source, and the universe size (~128 boards). These are the operational traits an agent needs and none are in the structured fields.

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 capability and key differentiator are front-loaded, and the query examples are useful routing cues. It is on the long side, with some near-duplication of the ranking metric across the parenthetical and the closing clauses, but no sentence is filler.

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 tool with no output schema, the description covers the returned fields (order-size net inflow breakdown, change %, leading stock), the source, the date-fallback behavior, and the metric definition. Nothing an agent needs to call it correctly or interpret results is missing.

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 100%, so all four parameters are already documented with enums and ranges; baseline is 3. The description reinforces the default sort metric and the date fallback but adds no syntax, format, or edge-case detail beyond what the schema states.

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 and resource ('ranks Eastmoney's ~128 industry boards by main-capital net inflow') plus what payload comes back (order-size breakdown, change %, top stock). It explicitly distinguishes itself from china-exchange-data's ashares_sector_flows and positions itself as the sector counterpart to ashares_capital_flow, so an agent can separate it from siblings without opening a 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?

Gives concrete triggering queries ('今日行业资金流向排名', 'which industry sectors had the biggest net capital inflow today') and names the alternative tool with the exact metric difference (official turnover ranking vs vendor-computed net inflow). It also explains the date fallback rule for weekends/holidays and publication lag, which is the main misuse trap.

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