fuzzy_search

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

With no annotations, the description must disclose behavior fully. It notes that exact matches come before fuzzy matches, which is helpful, but omits details on performance, authorization needs, or behavior on no matches. Adequate but not thorough.

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 extremely concise, using two sentences to convey purpose, examples, and ordering of results. No wasted words, and key information is front-loaded.

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?

Missing output schema, so description should compensate by specifying return format. It mentions 'returns exact matches first, then fuzzy matches' but does not describe what those matches look like (e.g., document IDs, scores, content). Leaves gaps for an 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 coverage is 100%, so baseline is 3. The description adds examples for the query and explains similarity_threshold, but does not enhance understanding of max_results or tags beyond the schema. Meets minimal expectations.

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 states fuzzy string matching with typo tolerance and gives concrete examples, making the purpose clear. However, it does not explicitly differentiate from sibling search tools like semantic_search or hybrid_search, which reduces clarity in distinguishing when to use this tool.

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 use when typos are expected but provides no explicit guidance on when to use versus alternatives, nor does it mention when not to use. No prerequisite or context for selection is given.

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