list_search_history

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

With no annotations, the description provides good behavioral details: pagination via cursor, OData filter syntax, and the fact that output is stored with a retrievable object ID. It does not cover rate limits or potential errors beyond 'error message', but the core behaviors are disclosed.

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 structured with a clear opening, parameter definitions, and return value explanation. It is slightly verbose but well-organized. The use of bullet points and examples helps readability.

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 output schema, the description adequately explains the return value: paginated list stored as an object, with an object ID for further use. Parameter descriptions are thorough, covering pagination, filtering, and usage. The tool's purpose and behavior are completely covered.

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 description fully explains each parameter: limit with default, after cursor mechanics, and query_filter with supported fields and an example. Since the input schema has no descriptions (0% coverage), the description adds critical meaning, making the tool usable.

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 retrieves search history for a deepset workspace and enumerates the kinds of data returned (queries, answers, prompts, etc.). It is specific about the resource (search history) and the action (retrieves/list), which distinguishes it from sibling tools like search_pipeline or list_pipelines.

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 says 'Use this to inspect what users have searched for, analyze usage, or debug pipeline behavior,' providing clear use cases. However, it does not mention when not to use it or compare to similar tools like list_pipeline_search_history, leaving some ambiguity in tool selection.

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