text_unicode_analysis

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

No annotations are provided, so the description carries full burden. It effectively discloses the tool's behavior (categorization, entropy analysis, script mixing detection). While it doesn't explicitly state non-destructiveness or requirements, the analysis nature is clear.

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?

A single, well-structured sentence that front-loads the core purpose ('Full Unicode character distribution analysis') and lists key features concisely. No wasted words.

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?

With no output schema, the description should ideally mention the return format. It describes the analysis types but omits what the output looks like (e.g., a report, percentages). For a simple tool with one input, it's adequate but not fully complete.

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 coverage is 100% with parameter 'text' described as 'Text to analyze'. The description adds context about the analysis but does not provide additional parameter-specific details beyond the schema, so baseline 3 is appropriate.

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 performs 'Full Unicode character distribution analysis' with specific actions: categorizes by script block, entropy analysis, and script mixing detection. It distinguishes itself from sibling text analysis tools like text_homoglyph or text_detect.

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 Unicode analysis but does not explicitly state when to use this tool vs alternatives like text_homoglyph or text_detect. No when-not or alternative guidance is provided.

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