list_features

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

No annotations provided, so the description carries full burden. It correctly indicates the tool is read-only (lists, returns documentation) and mentions it covers all 22 feature extractors. It does not explicitly state safety or lack of side effects, but the purpose implies no mutations.

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 two sentences, front-loaded with the purpose ('List all available features'), and every word earns its place. No unnecessary details.

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 zero parameters, an output schema present, and the simple nature of listing, the description fully covers what the tool does. No gaps.

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 tool has 0 parameters and the schema coverage is 100% (empty schema). According to guidelines, baseline score for 0 parameters is 4. The description adds no parameter info because none exist.

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 lists all available features from the imagefeatures library and returns documentation with dimensions and use cases. This distinguishes it from siblings like extract_features (which extracts features) and analyze_image (which performs analysis).

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 discovering available features before extraction, but does not explicitly mention when to use or avoid this tool versus alternatives like extract_features or filter_by_vibe. Context with sibling tools helps but is not directly stated.

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