get_technical_indicators

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable context: results are null when not warmed up, supported plans include Free/Light/Standard/Premium, API fallback on cache miss, and the specific bb20 ±2σ convention. This goes beyond what the annotations alone provide.

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 description is well-organized into sections (usage, alternatives, supported indicators, plans, arguments) and is front-loaded with a clear summary. Slight redundancy exists ('All plans' repeated in the first line and later in [Supported plans]), but it remains efficient and scannable.

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?

The description is complete for a 5-parameter tool: it covers purpose, when to use, alternatives, parameter semantics, plan limitations, and edge-case behavior (null when not warmed up). An output schema exists, so returning detailed return values is not required, and the description still provides enough context for reliable 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?

Despite 0% schema description coverage, the description thoroughly explains every parameter: code is required, date overrides date_from/date_to, date formats are specified, range boundaries are inclusive, and indicators has a documented default list. This fully compensates for the missing schema descriptions.

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 clearly identifies the tool's action ('Compute technical indicators') and its target resource ('a single stock'), naming specific indicators (SMA, Bollinger Bands, RSI). It also differentiates from siblings by directing charting queries to get_candlestick_data and VWAP pressure to compare_close_vs_vwap.

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 explicitly states when to use the tool ('Use for SMA・移動平均・ボリンジャーバンド・RSI queries on a specific stock') and names alternative tools for other use cases. It also clarifies supported plans and API fallback behavior, giving clear context for selection.

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