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list_pipeline_search_history

Retrieve paginated search history for a specific pipeline, including queries, answers, and metadata. Filter results by date, query, or other fields to analyze past searches.

Instructions

Retrieves search history for a specific pipeline with pagination.

Returns past searches run with the given pipeline (query, answer, pipeline used, and more). Use the after parameter with next_cursor from the response to fetch the next page. :param pipeline_name: Name of the pipeline to get search history for. :param limit: Maximum number of entries to return per page. :param after: The cursor to fetch the next page of results. If there are more results to fetch, the cursor will appear as next_cursor on the response. :param query_filter: An OData filter expression to narrow down results. Supported fields: query, client_source_path, pipeline_version_id, answer, api_key, created_at, created_by, tags/tag_id, feedbacks, feedbacks/score, feedbacks/comment, feedbacks/bookmarked, session_id, search_session_id, feedbacks/result_id, request/filters, request/params, duration. Example: "created_at ge 2024-01-01T00:00:00Z" or "query eq 'my search'". :returns: Paginated list of search history entries or error message.

The output is automatically stored and can be referenced in other functions. Returns a formatted preview with an object ID (e.g., @obj_123). Use the object store tools in combination with the object ID to view nested properties of the object. Use the returned object ID to pass this result to other functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipeline_nameYes
limitNo
afterNo
query_filterNo
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that output is automatically stored and can be referenced with object IDs, and explains pagination with 'after' and 'next_cursor'. However, it does not discuss authentication, rate limits, or error handling for missing pipelines.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with a summary, parameter list, and output handling explanation. It is slightly lengthy but well-organized with clear separations. Each sentence adds value, though some redundancy exists (e.g., duplicate explanation of 'after' in parameter and body).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 4 parameters and no output schema, the description covers pagination, filtering, output storage, and object ID usage. It misses error scenarios and permission requirements but is otherwise complete for typical usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates excellently. It explains each parameter in detail: pipeline_name (required), limit (default 10), after (cursor for pagination), and query_filter (supported fields and examples). This adds significant value beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves search history for a specific pipeline, which is a distinct resource. It specifies the verb 'retrieves' and outlines what is returned (query, answer, pipeline used, etc.). This differentiates it from siblings like 'list_search_history' which likely retrieves history across all pipelines.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides pagination instructions and mentions using object store tools for nested properties, but it does not explicitly guide when to use this tool versus alternatives like 'list_search_history' or 'search_pipeline'. No direct when/when-not guidance is given.

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

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