deduplicate_strings

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: using Jina embeddings and submodular optimization for semantic deduplication, returning top-k results, and automatically determining optimal k if not provided. However, it doesn't mention performance characteristics like computational complexity or rate limits.

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 perfectly structured and concise: three sentences that each earn their place. The first states the core functionality, the second provides usage guidelines, and the third lists specific applications. No wasted words, front-loaded with essential information.

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?

For a tool with no annotations and no output schema, the description provides good context about what the tool does and when to use it. However, it doesn't describe the return format or what 'semantically unique' means in practice. Given the complexity of semantic deduplication, more detail about the output would be helpful.

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 already documents both parameters thoroughly. The description adds some context about the 'k' parameter's automatic optimization behavior, but doesn't provide additional semantic meaning beyond what's in the schema descriptions. This meets the baseline for 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 clearly states the tool's purpose with specific verbs ('get top-k semantically unique strings') and resources ('from a list using Jina embeddings and submodular optimization'). It distinguishes itself from siblings like deduplicate_images by focusing on strings rather than images, and from other tools by its semantic deduplication approach.

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 explicitly states when to use this tool ('when you have many similar strings and want to select the most diverse subset that covers the semantic space') and provides three specific use cases ('removing duplicates, selecting representative samples, or finding diverse content'). It differentiates from siblings by not overlapping with their domains (e.g., images, web search).

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