search_research_data

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

With no annotations, the description carries the burden of behavioral disclosure. It does reveal that the search uses semantic similarity (not keyword matching), and the term 'saved research data' implies a read-only operation. However, it does not state whether results are ordered by relevance, whether topic is required, or any limitations. The description gives some behavioral context but not rich detail.

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 one concise sentence followed by a simple list of parameter definitions. It is front-loaded with the main action and avoids redundancy or filler. Every line serves a purpose.

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 a straightforward search operation with an output schema available, so return values do not need to be explained. The description covers the main purpose, the search method, and all parameters. The lack of explicit usage scenarios is a minor gap, but overall the description is sufficient for a tool of this complexity.

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?

The Args section in the description explicitly defines each of the three parameters: query as the search query, topic as the topic database to search in, and max_results as the maximum number of results. Since the schema itself provides no descriptions for these fields (coverage 0%), this textual description adds essential meaning and compensates for the schema gap.

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 opens with a clear action statement: 'Search through saved research data using semantic similarity.' It specifies the operation (search), the resource (saved research data), and the method (semantic similarity), clearly distinguishing it from sibling tools like save_research_data or delete_research_topic.

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?

There is no explicit guidance on when to choose this tool over alternatives. The verb 'search' implies a use case for finding saved research data, but no direct comparison with sibling tools or exclusions is provided. This is implied usage rather than explicit direction.

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