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list_search_history

Retrieve search history from a deepset workspace to analyze user queries, pipeline performance, and feedback. Filter and paginate results for targeted inspection.

Instructions

Retrieves search history for the configured deepset workspace.

Returns past searches run in the workspace, including queries, answers, prompts, feedback, and metadata. Use this to inspect what users have searched for, analyze usage, or debug pipeline behavior.

Each entry includes:

  • request.query — the search query text

  • time / created_at — when the search ran

  • duration — how long it took (seconds)

  • status — 'success' or 'failed'

  • pipeline.name — which pipeline handled the query

  • response — the list of search results

  • feedback, labels, note — user annotations

Use the after parameter with the next_cursor value from the previous response to fetch the next page. :param limit: Maximum number of entries to return per page (default 10, max 1000). :param after: ISO-8601 timestamp cursor to fetch entries older than this point. Pass the value from next_cursor on the previous 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, labels, status, note. Example: "created_at ge 2024-01-01T00:00:00Z" or "query eq 'my search'". :param sort_field: Field to sort results by. One of: created_at, query, duration, feedbacks/score. Defaults to created_at. :param sort_order: Sort direction — ASC (oldest first) or DESC (newest first). Defaults to DESC. :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
afterNo
limitNo
sort_fieldNocreated_at
sort_orderNoDESC
query_filterNo
Behavior4/5

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

With no annotations, the description covers pagination, output storage, object ID referencing, and entry structure. It does not mention rate limits or auth but adequately communicates read-only behavior.

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 well-structured with clear sections (purpose, uses, entry fields, params, output). It is slightly verbose but each sentence adds value; could be more concise.

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

Completeness5/5

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

Given the complexity (5 params, no annotations, no output schema), the description is remarkably complete: it explains pagination, output format, object ID usage, and parameter details thoroughly.

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?

Despite 0% schema description coverage, the description provides comprehensive parameter docs: limit, after, query_filter with examples, sort_field, sort_order with defaults and enumerations, adding significant value beyond 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 the configured deepset workspace, listing past searches with detailed fields. It distinguishes itself from sibling tools like list_pipeline_search_history by focusing on workspace-level history.

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

Usage Guidelines4/5

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

The description provides usage scenarios (inspect searches, analyze usage, debug) and pagination guidance. However, it does not explicitly contrast with similar tools or state when not to use it.

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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