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get_pipeline_trace

Retrieve the complete execution trace for a single Haystack query, including component spans, timing, and failure details. Use query_id to deep-dive into a specific pipeline run.

Instructions

Retrieves the Haystack pipeline run trace including all spans for a single search history record.

Returns the execution trace for one query: every component span with essential tags (excluding the component's input and output), timing, and failure details. Use this to deep-dive into a specific query run identified by its query_id (obtainable from list_pipeline_traces or list_pipeline_search_history).

For a targeted look at one span including the input and output at one component, use get_pipeline_trace_span_tags; for the logs, use get_pipeline_trace_logs. :param pipeline_name: Name of the pipeline. :param query_id: UUID of the search history query whose trace to retrieve. Obtain this from the query_id / search_history_id field of a list_pipeline_traces or list_pipeline_search_history response. :returns: The pipeline trace entry including all spans or an 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
query_idYes
pipeline_nameYes
Behavior4/5

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

With no annotations, the description carries the burden and discloses important behaviors: returns all spans, excludes component input/output, includes timing and failure details, and automatically stores output with an object ID. It clearly signals a read-like operation via 'Retrieves' and explains the side effect of storage.

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 longer than strictly necessary, with some redundancy (query_id source is mentioned twice). However, it is well-structured with a front-loaded purpose, clear param block, and separate usage guidance. Every major section earns its place.

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 absence of annotations and output schema, the description provides a comprehensive context: what is returned, what is excluded, error handling, object store integration, and how to reference the result. It covers the tool's role in the broader workflow and directs users to related tools when needed.

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?

Schema coverage is 0% (no descriptions in properties), but the description fully explains both parameters. pipeline_name is simply 'Name of the pipeline,' and query_id is given a detailed definition with instructions to obtain it from the query_id/search_history_id field of list_pipeline_traces or list_pipeline_search_history responses.

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 opens with a specific verb and resource: 'Retrieves the Haystack pipeline run trace including all spans for a single search history record.' It clearly differentiates from sibling tools by focusing on the full trace for a single query, and mentions alternatives for other granularities.

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

Usage Guidelines5/5

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

Explicitly states when to use ('Use this to deep-dive into a specific query run') and how to obtain required identifiers ('obtainable from list_pipeline_traces or list_pipeline_search_history'). It also provides concrete alternatives: 'For a targeted look at one span... use get_pipeline_trace_span_tags; for the logs, use get_pipeline_trace_logs.'

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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