text_homoglyph

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

No annotations exist, so the description must fully disclose behavior. It explains detection of non-ASCII characters resembling ASCII letters, but does not describe the output format (e.g., list of found characters, locations) or any side effects. This leaves ambiguity about what the agent can expect after invocation.

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 concise sentences that front-load the core purpose and provide an example. Every word adds value with no 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?

While the tool is simple with one parameter, the description omits what the output looks like (e.g., list, counts, or boolean). Given no output schema, this gap reduces completeness for an agent needing to handle results.

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% coverage with a single parameter 'text' described as 'Text to analyze'. The description adds no additional meaning beyond the schema; it only restates that the tool operates on text. Baseline 3 applies due to high schema coverage.

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 uses a specific verb 'Detect' and resource 'Unicode homoglyph substitutions in text', with clear examples (Cyrillic a vs Latin a). It distinguishes itself from siblings like text_detect or text_unicode_analysis by focusing on homoglyphs.

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 states what the tool does but gives no explicit guidance on when to use it versus alternatives, nor any exclude conditions. Usage is implied but not clearly demarcated against sibling tools.

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