find_best_matches

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only lists parameters without explaining side effects, permissions, or output behavior beyond ranking. Critical traits like read-only or mutation status are absent.

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 concise and structured as a docstring with a clear one-line summary. It lists parameters efficiently without extraneous text, though the parameter descriptions are too terse.

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 complexity (6 parameters, enums) and the presence of an output schema, the description omits crucial context such as how ranking works, how threshold and strategy interact, and when to use specific profiles. Sibling tools are not referenced for complementary use.

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%, yet the description adds minimal meaning beyond parameter names (e.g., 'profile: Normalization profile' is vague). It does not explain enum options (e.g., what 'product' profile does) or the effect of strategy choices, failing to compensate for missing schema descriptions.

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 'Find and rank candidate strings most similar to a query,' which is a specific verb+resource. It differentiates the tool from siblings like compare_strings (comparison) and normalize_text (normalization) by focusing on similarity ranking.

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 no guidance on when to use this tool versus alternatives like compare_strings or explain_match. There is no mention of prerequisites or exclusions, leaving the agent without context for appropriate use.

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