search_pipeline_with_params

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

Since no annotations are provided, the description carries the full burden. It discloses key behaviors: it checks if the pipeline is deployed before executing, stores results in an object store for later reference, and returns a formatted preview with an object ID. It also notes potential error messages. This level of detail helps an AI agent understand side effects and output format, though it does not mention rate limits or authentication needs.

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 verbose and contains redundancy, e.g., the first two sentences both state the same idea: 'Searches using a pipeline with params.' and 'Uses the specified pipeline to perform a search...'. It also includes a docstring-style parameter list that could be integrated more succinctly. While it is clearly structured, it could be tighter.

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 the lack of output schema and low schema coverage, the description provides comprehensive context: it explains the pre-execution check, the return format (error messages or object ID preview), and the object store integration. It also hints at using object store tools to view nested properties. This covers the essential aspects needed for an AI agent to use the tool effectively.

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?

With 0% schema description coverage, the description compensates well. It defines each parameter: pipeline_name ('Name of the pipeline to use'), query ('The search query to execute'), and params ('parameters to customize the search'). For params, it adds that arbitrary parameters are allowed and that filters can be specified under the 'filters' key, with a link to the Haystack filter syntax. This adds significant value beyond the bare schema.

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: 'Searches using a pipeline with params.' It specifies the verb 'searches' and the resource 'pipeline with params', making the function distinct. However, it does not explicitly differentiate from sibling tools like search_pipeline and search_pipeline_with_filters, which could confuse an AI agent when selecting among them.

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 explicit guidance on when to use this tool versus alternatives. It does not mention conditions for choosing this tool over search_pipeline or search_pipeline_with_filters, nor does it explain any prerequisites. The only implicit hint is the mention of arbitrary params, but this is not framed as a usage criterion.

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