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

With no annotations, the description carries the full burden and does so well: it discloses the two modes and their constraints, that portfolio intervals are limited by preset batches, that inv_vol requires portfolio mode plus institutional tier, that it is a paid tool with tiers (¥29.9+ Standard, Pro+ for portfolio/batch) and separate daily quota checkable via ashare_usage. It stops short of stating latency/expected runtime or failure behavior, which keeps it below 5.

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 trigger phrases are front-loaded, and the ⚠️ blocks make the high-risk constraints (mode/code pairing, tier requirement, cost) scannable. It is dense and emoji-heavy, but essentially every warning carries decision-relevant information, so little is wasted.

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?

An output schema exists, so return values need not be explained. For an 8-parameter, paid, mode-dependent tool, the description covers everything blocking a correct call: the mode/code pairing, weighting availability, prerequisite lookup via ashare_strategies, quota/pricing gating, and the batch alternative.

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% and the schema descriptions already state the mode=single/code dependency, the inv_vol restriction, and the include_equity data-volume tradeoff, so the description mostly restates structured data. It does consolidate the cross-parameter conditional logic into a usable decision framing, but adds little meaning that the schema does not already carry — baseline 3 is appropriate.

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?

Opens with a specific verb+resource ('量化回测：按策略跑历史收益') plus the concrete outputs (收益/最大回撤/交易次数/净值曲线), so the agent knows exactly what comes back. It explicitly differentiates from siblings by naming ashare_backtest_batch and ashare_strategies as the tools for multi-target runs and strategy discovery.

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 direct user-phrase triggers ('回测一下/这个策略收益如何/买卖点效果/最大回撤') that select this tool, and explicit exclusions routing to ashare_strategies (to see strategy lists) and ashare_backtest_batch (multi-target × multi-strategy). Nothing about tool selection is left to inference.

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