Skip to main content
Glama
avivsinai

langfuse-mcp

find_exceptions

Analyze exception patterns in Langfuse by grouping errors by file, function, or type to identify recurring issues in LLM applications.

Instructions

Get exception counts grouped by file path, function, or type.

Args:
    ctx: Context object containing lifespan context with Langfuse client
    age: Number of minutes to look back (positive integer, max 7 days/10080 minutes)
    group_by: How to group exceptions - "file" groups by filename, "function" groups by function name,
              or "type" groups by exception type

Returns:
    List of exception counts grouped by the specified category (file, function, or type)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageYesNumber of minutes to look back (positive integer, max 7 days/10080 minutes)
group_byNoHow to group exceptions - 'file' groups by filename, 'function' groups by function name, or 'type' groups by exception typefile

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses the time-window constraint ('age' parameter) and grouping behavior, but doesn't mention pagination, rate limits, authentication needs, or what happens with zero exceptions. It adequately describes the core behavior but lacks operational details.

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, Args, Returns) and front-loaded the core functionality. The Args section repeats schema information unnecessarily, but overall it's appropriately sized with minimal waste.

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?

Given 2 parameters with 100% schema coverage and an output schema exists (implied by Returns statement), the description provides adequate context. It explains what the tool does, parameters, and return format. For a read-only aggregation tool with good schema coverage, this is reasonably complete though could benefit from more behavioral context.

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

Parameters4/5

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

Schema description coverage is 100%, so the schema already documents both parameters completely. The description adds minimal value by repeating parameter explanations in the Args section. However, it does provide the return format context that helps understand parameter implications, justifying a score above baseline.

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 the tool's purpose with a specific verb ('Get') and resource ('exception counts'), and it distinguishes from siblings by specifying grouping capabilities. It differentiates from 'find_exceptions_in_file' by not being file-specific and from 'get_exception_details' by providing aggregated counts rather than detailed records.

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 implies usage context through the 'group_by' parameter explanation, suggesting when to use different grouping options. However, it doesn't explicitly state when to choose this tool over alternatives like 'get_exception_details' or 'find_exceptions_in_file', nor does it mention prerequisites or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/avivsinai/landfuse-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server