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

With no annotations provided, the description carries the full burden. It discloses the embedding model ('multilingual-e5-small'), the matching method ('cosine similarity'), and language preference. However, it does not mention pagination, what happens with k=0, or output format, leaving some behavioral gaps.

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?

Two sentences, no filler. The purpose is front-loaded, and every sentence adds value. Highly concise and well-structured.

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?

The tool is low complexity with 2 params, but no output schema exists. The description does not explain the return format (e.g., list of tenders with scores), which would help completeness. Adequate but could be improved with output details.

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% with descriptions for both parameters. The tool description adds context about the embedding and matching process, but this is general, not parameter-specific. For the 'k' parameter, no extra meaning is added beyond the schema's default note. Baseline 3 is appropriate.

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 verb ('Search') and resource ('tenders by text query'), and distinguishes from siblings by specifying the use of 'multilingual-e5-small' embedding and cosine similarity. This technical detail helps differentiate it from other search or match tools.

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 a language hint ('German text works best') but does not explicitly state when to use this tool versus alternatives like 'match_tenders'. No exclusion criteria or context for optimal use are given, so usage guidance is implied rather than explicit.

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