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langfuse_get_session

Retrieve detailed session data with metrics and aggregated information from Langfuse observability for debugging AI agent runs, comparing sessions, and analyzing LLM usage patterns.

Instructions

[Langfuse] Get a specific session with its metrics and aggregated data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesThe session ID to fetch
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool fetches data ('Get'), implying a read-only operation, but doesn't clarify permissions, error handling, rate limits, or what happens if the session_id is invalid. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads key information: the tool name context ('[Langfuse]'), action, resource, and data scope. There is no wasted verbiage, making it highly concise and well-structured for quick comprehension.

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

Completeness3/5

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

Given the tool's simplicity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage context, behavioral traits, and output expectations. For a read operation with no annotations, it should provide more guidance on errors or data format to be fully complete.

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

Parameters3/5

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

The input schema has 100% description coverage, with the single parameter 'session_id' documented as 'The session ID to fetch'. The description adds no additional parameter semantics beyond this, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the heavy lifting.

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

Purpose4/5

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

The description clearly states the action ('Get') and resource ('a specific session'), and specifies the data included ('with its metrics and aggregated data'). It distinguishes from sibling tools like 'langfuse_list_sessions' by focusing on retrieval of a single session. However, it doesn't explicitly differentiate from other 'get_session' variants in the sibling list, which slightly limits specificity.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid session_id), exclusions, or comparisons to sibling tools like 'langfuse_search_sessions' or 'langfuse_list_sessions', leaving the agent to infer usage context from the tool name alone.

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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