export_data_uri

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the output format (Data URI) and a use case (image tags), it doesn't describe important behavioral aspects like whether this is a read-only operation, what happens with invalid input, if there are size limitations, or what the return value looks like. For a conversion tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 perfectly concise and front-loaded. The first sentence states the core functionality, and the second sentence in parentheses provides valuable additional context about use cases. Every word earns its place with zero waste or redundancy.

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 moderate complexity (conversion operation with one parameter), no annotations, and no output schema, the description provides adequate but incomplete context. It covers the what and a key use case but lacks information about behavioral traits, error handling, and return values. For a tool with no annotations or output schema, it should do more to compensate for these 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 input schema has 100% description coverage with a well-documented parameter ('encode' with enum values and default). The description doesn't add any parameter-specific information beyond what the schema provides. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 with a specific verb ('변환합니다' - converts) and resource ('SVG를 Data URI 형식으로' - SVG to Data URI format). It distinguishes itself from sibling tools like export_png and export_svg by specifying the output format (Data URI) and a key use case ('이미지 태그에 직접 사용 가능' - can be used directly in image tags).

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 clear context for when to use this tool: when you need to convert SVG to Data URI format for direct use in image tags. However, it doesn't explicitly state when NOT to use it or mention alternatives like export_png or export_svg for different export needs. The guidance is helpful but lacks explicit exclusions or comparisons.

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