compare_strings

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

With no annotations, the description must fully disclose behavior. It describes fuzzy matching and strategies but omits details like case sensitivity, how threshold is applied, normalization effects, or output shape. The output schema exists but is not referenced.

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 short and uses bullet points for strategies and args, which is clear. However, it redundantly lists arg names that are already in the schema, wasting space that could be used for additional guidance. A more concise and informative approach would be preferred.

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 5 parameters, no annotations, and an output schema, the description should cover return values and typical usage. It does not mention the output format (a score? a boolean?) or provide examples, leaving significant gaps for the agent.

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 description coverage is 0%, so the description must add meaning. It lists parameter names but provides no semantic details: e.g., what each 'profile' does, valid threshold range, strategy definitions. This barely adds value beyond the schema.

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 'Compare two strings using fuzzy matching' and lists specific strategies, making the tool's purpose explicit. It distinguishes itself from siblings like 'normalize_text' and 'find_best_matches' by focusing on pairwise comparison with multiple algorithms.

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?

No guidance on when to use this tool vs. alternatives (e.g., 'find_best_matches' or 'explain_match'). While strategies are listed, there is no explanation of which strategy suits what scenario, leaving the agent to guess.

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