helper_featureCollection

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by specifying: input must be valid JSON strings, coordinate order is [longitude, latitude] in WGS84, it depends on Turf.js and Node.js environment, and exceptions are raised for JavaScript execution failures, timeouts, or malformed input. However, it doesn't mention performance characteristics, rate limits, or authentication requirements.

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-structured with clear sections (Args, Returns, Raises, Example, Notes), but it's quite lengthy. Some information could be more concise - for example, the example section includes Python code that may not be necessary. The core purpose is stated upfront, but the overall length could be reduced while maintaining clarity.

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 has 2 parameters, no annotations, 0% schema description coverage, but has an output schema, the description provides substantial context. It thoroughly documents parameters, return format, exceptions, and dependencies. The main gap is lack of comparison with sibling tools, but otherwise it's quite complete for a transformation tool.

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 schema description coverage is 0%, so the description must fully compensate. It provides excellent parameter documentation: 'features' is explained as a JSON string array of GeoJSON features with a detailed example; 'options' is documented as an optional JSON string with specific fields (bbox, id) and examples. This goes far beyond what the bare schema provides.

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: '将多个地理特征组合成一个特征集合' (combine multiple geographic features into a feature collection). It specifies the verb ('组合' - combine) and resource ('地理特征' - geographic features). However, it doesn't explicitly differentiate from sibling tools like 'feature_conversion_combine' or 'aggregation_collect', which appear to have similar aggregation functions.

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 provides minimal usage guidance. It mentions that feature collections are useful for '批量处理和管理多个地理对象' (batch processing and managing multiple geographic objects), but doesn't specify when to use this tool versus alternatives like 'feature_conversion_combine' or 'aggregation_collect'. No explicit when-not-to-use scenarios or prerequisites are provided.

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