quant_analyze_setup

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description need not reiterate safety. It adds value by disclosing that it fetches daily and intraday data, and that it returns an error string for missing data or unknown methods. This goes beyond the 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?

The description is compact and front-loaded with the core purpose. It uses bullet-style Args and Returns sections without unnecessary words. Every sentence contributes to understanding.

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?

Given the tool's complexity (one parameter, single operation), the description covers purpose, data fetching, dispatch, return format, and error conditions. Combined with thorough schema and annotations, it is fully sufficient for an agent to invoke correctly.

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?

The description includes an Args section summarizing the three parameters, which mirrors the schema descriptions. With schema descriptions already present for all properties, the description adds minimal extra meaning (e.g., noting defaults). The context signal 'Schema description coverage: 0%' is contradictory to the actual schema; based on actual content, the description does not significantly improve understanding beyond the schema.

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 begins with a specific verb+resource: 'Run a registered method on a ticker to produce a trade setup.' It clearly distinguishes from siblings like quant_describe_method (which describes methods) and quant_backtest_method (which backtests). The tool's focus on a single ticker and registered method is unambiguous.

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 implies usage for generating a trade setup for a specific ticker and mentions feeding the result to quant_score_decision, suggesting a pipeline. However, it does not explicitly state when not to use this tool versus alternatives like quant_detect_regime or quant_compute_indicators, so no exclusions are given.

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