find_similar_elements

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

No annotations are provided, so the description carries the full burden. It mentions the tool 'returns elements with similarity scores and relationships,' which gives some behavioral context, but lacks details on permissions, rate limits, error handling, or whether it's a read-only operation. For a tool with no annotations, this is insufficient.

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 front-loaded, with two sentences that efficiently cover the tool's purpose and return values. There is no wasted verbiage, though it could be slightly more structured by separating usage guidelines.

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 no annotations and no output schema, the description is moderately complete. It explains the tool's purpose and return format, but lacks details on behavioral traits, error cases, and usage context. For a tool with 4 parameters and no structured safety hints, it should do more to compensate.

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 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond what the schema provides, such as explaining how 'element_name' is used in similarity calculations or the impact of 'threshold'. Baseline 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'Find elements that are semantically similar to a given element using NLP scoring (Jaccard similarity and Shannon entropy).' It specifies the verb ('find'), resource ('elements'), and methodology ('NLP scoring'), but does not explicitly differentiate from sibling tools like 'search_all' or 'search_collection' that might also find elements.

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. It does not mention any prerequisites, exclusions, or compare it to sibling tools such as 'search_all' or 'get_element_relationships', leaving the agent with no context for tool selection.

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