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langfuse-mcp-java

find_exceptions

find_exceptions
Destructive

Filter Langfuse traces to identify and debug production errors by retrieving only ERROR-level traces for analysis.

Instructions

Returns only traces whose level field equals ERROR.

Filtering is performed on the server before the response is returned — the result set contains error traces only, never a mix of levels.

Useful for surfacing pipeline failures and debugging production errors. Both time range parameters are optional. Omit them to search across all time. Pagination works the same way as fetch_traces.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYesPage number, 1-based. Omit to use default (1).
limitYesResults per page. Omit to use default (20).
fromTimestampYesStart of time range in ISO-8601 format, e.g. 2025-06-01T00:00:00Z. Omit to search from the beginning of the project.
toTimestampYesEnd of time range in ISO-8601 format, e.g. 2025-06-30T23:59:59Z. Omit to search up to the current time.
Behavior2/5

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

Annotations indicate destructiveHint=true and readOnlyHint=false, but the description only describes read behavior ('Returns', 'Filtering'), failing to disclose what gets destroyed or modified. It does add valuable behavioral context about server-side filtering guarantees ('Filtering is performed on the server...never a mix of levels'), but the omission of destructive behavior given the annotation is a critical gap.

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 four sentences front-loaded by purpose, followed by behavioral guarantees, use cases, and parameter guidance. Every sentence adds distinct value. However, the sentence about optional parameters propagates misinformation given the schema's required array.

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 destructive annotation and the read-oriented description, the definition lacks necessary completeness. The parameter optionality contradiction and unexplained destructive behavior leave critical gaps. Without an output schema, the description adequately explains the return concept (error traces) but fails to resolve safety concerns raised by the annotations.

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

Parameters2/5

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

While the input schema has 100% description coverage, the description contradicts the schema regarding parameter optionality: it states 'Both time range parameters are optional. Omit them...', but the schema marks fromTimestamp and toTimestamp as required. This contradiction creates ambiguity about whether the tool can be called without time bounds.

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 precise, specific verb and resource ('Returns only traces whose level field equals ERROR') that clearly distinguishes this from siblings like fetch_traces (general traces) and get_error_count (likely numeric counts). It identifies the exact filter criteria (level=ERROR) and scope.

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

Usage Guidelines3/5

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

The description provides contextual usage ('Useful for surfacing pipeline failures and debugging production errors') and references sibling fetch_traces for pagination behavior, helping users understand the relationship. However, it lacks explicit guidance on when NOT to use this vs. alternatives like get_exception_details or find_exceptions_in_file, and doesn't address the destructive annotation implication.

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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