bollinger_scan

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: it scans a whole exchange, works with crypto and stocks, and returns a structured error envelope on any failure. It also clarifies the canonical name to avoid tool confusion. This adds significant transparency beyond annotations without contradiction.

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 with a clear intro, differentiation note, example, argument descriptions, and return behavior. Every sentence adds value, and despite the length, it remains focused and front-loaded with the core purpose. No redundancy or filler.

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 (4 parameters, multiple exchange categories, thresholds, sibling relationships), the description fully covers purpose, usage, parameters, return types, and error behavior. The presence of an output schema does not require explaining return values, but the description does so anyway, making it self-contained.

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 has 0% description coverage, so the description carries the full burden and excels. It explains each parameter: exchange lists supported venues for crypto/stocks, timeframe enumerates valid values with typical squeeze thresholds, bbw_threshold defines the filter meaning and default, limit specifies maximum rows. An example call further clarifies usage.

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 states the tool's purpose: 'Scan for assets with low Bollinger Band Width (squeeze detection).' It specifies the resource (assets), the action (scan), and explicitly differentiates from a sibling tool: 'For the Bollinger read of ONE symbol, call coin_analysis instead.' This is a specific verb+resource+scope with clear sibling distinction.

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?

Provides explicit when-to-use guidance: scans a whole exchange for squeezes, not a single symbol. It names the alternative tool for single-symbol analysis ('coin_analysis'). Also supplies typical threshold values per timeframe, giving concrete usage context. This goes beyond minimal guidance.

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