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langfuse_list_scores

Filter and retrieve evaluation scores from AI agent sessions to analyze performance, debug runs, and track LLM usage patterns.

Instructions

[Langfuse] List scores/evaluations with filters. Scores are attached to traces or observations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results per page (default: 50)
pageNoPage number (1-indexed, default: 1)
nameNoFilter by score name
user_idNoFilter by user ID
trace_idNoFilter by trace ID
from_timestampNoFilter scores created after this timestamp
to_timestampNoFilter scores created before this timestamp
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that scores are attached to traces or observations, adding some context, but fails to describe key behaviors such as pagination handling (implied by limit/page parameters), rate limits, authentication needs, or what the output looks like. This is inadequate for a list tool with 7 parameters.

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 the core action ('List scores/evaluations') and includes essential context ('with filters', 'attached to traces or observations'). There is zero waste, making it appropriately sized and well-structured.

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

Completeness2/5

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

Given the complexity of a list tool with 7 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, output format, and usage guidelines, making it insufficient for an agent to fully understand how to invoke and interpret results from this tool.

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?

Schema description coverage is 100%, so the schema fully documents all 7 parameters. The description adds no additional meaning beyond what the schema provides, such as explaining relationships between filters or usage examples. Baseline 3 is appropriate as the schema does 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 verb ('List') and resource ('scores/evaluations') with the context of filtering, making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'langfuse_get_score' or 'langfuse_search_sessions', which might handle similar data but with different operations or scopes.

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 mentions 'with filters' but provides no guidance on when to use this tool versus alternatives like 'langfuse_search_sessions' or 'langfuse_list_traces'. It lacks explicit when/when-not instructions or prerequisites, leaving usage context implied at best.

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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