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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds real context beyond that: it returns structured cards where each number carries a source (interface + field), narrative.traces document the formula conventions, and it explicitly does not make return predictions, plus the '(cost: free)' tag. Missing only auth or data-freshness details.

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?

A single compact block that front-loads the metric list, then the return structure, then the scope exclusion and cost. Every clause carries information; the bracketed 【行情】 prefix and the trailing cost tag are minor overhead but not wasteful.

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?

With no parameters and no output schema, the description carries the burden of describing the return value, and it does so: structured cards, per-number source attribution, narrative.traces formulas, and an explicit no-prediction boundary. An agent has enough to call it and to set expectations for the result.

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?

Zero input parameters, which sets the baseline at 4. The schema is empty and fully covered, and the description correctly spends no words on parameter behavior, instead describing the shape of the result.

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 uses a specific verb ('解释' / explain) tied to a concrete resource set: per-position notional value, unrealized PnL, leverage, account exposure, daily PnL, margin usage, and circuit-breaker status. This distinguishes it from raw-data siblings such as platform_positions and platform_account_overview, since it promises sourced, formula-annotated explanations. It stops short of naming those siblings explicitly.

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?

Usage is implied: ask when the user wants their holdings and account risk explained rather than merely listed. The scope exclusion '不做收益预测' (does not do return predictions) is a useful boundary, but no alternative tool is named and no prerequisites are stated, leaving the agent to infer when to prefer platform_positions or platform_account_overview.

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