Quant — Run Indicator Script

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond those: execution is server-side, the tool accepts arbitrary indicator scripts, and it returns computed values as JSON. It also clarifies that the input array must match the order of input.*() calls, which is a key runtime behavior. No contradiction with annotations.

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?

Three sentences, front-loaded with the core purpose and followed by the most important parameter formatting notes. Some redundancy exists because the period list and input example are identical to the schema descriptions, but the text remains compact and scannable without padding.

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 that accepts arbitrary scripts, the description covers the essentials: data scope, period values, input format, and return type. However, it omits details about script language/syntax, how output values map to input() calls, error behavior, or limits. With no output schema, the return description ('indicator/plot values as JSON') is sufficient but thin. Given the tool's complexity, a 3 reflects the clear gaps rather than a fully complete picture.

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 the structured schema already documents every parameter. The description repeats the period list and input-array example that are already in the schema, adding no new semantic nuance beyond what the schema provides. Baseline 3 is appropriate when the schema carries the full parameter documentation.

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 and resource: 'Run a quant indicator script against historical K-line data on the server' and clarifies the server-side execution and JSON return. This distinguishes it clearly from sibling data-retrieval tools like candlesticks or history_candlesticks_by_date; no other sibling appears to execute user-supplied scripts.

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?

The description explains what the tool does but never says when to choose it over alternatives or when not to use it. It does not reference siblings like candlesticks, history_candlesticks_by_date, or screener_search, leaving the agent to infer that quant_run is for custom scripted indicators. No preconditions or exclusions are given.

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