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avivsinai

langfuse-mcp

find_low_confidence_route_decisions

Identify route decisions with low confidence or marked as uncallable to debug routing failures and optimize decision logic.

Instructions

Find route decisions that are low-confidence or explicitly uncallable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageNoNumber of minutes to look back (positive integer, max 7 days/10080 minutes)
pageNoPage number for pagination (starts at 1)
limitNoMaximum number of matching route decisions to return
providerNoOptional route-decision metadata provider filter
trace_idNoOptional Langfuse trace ID filter
session_idNoOptional route-decision metadata session_id filter
output_modeNoControls the output format and action. 'compact' (default): Returns a summarized JSON object optimized for direct agent consumption. 'full_json_string': Returns the complete, raw JSON data serialized as a string. 'full_json_file': Returns a summarized JSON object AND saves the complete data to a file.compact
router_nameNoOptional route-decision metadata router_name filter
capability_idNoOptional route-decision metadata capability_id filter
max_confidenceNoReturn route decisions with confidence at or below this value
include_uncallableNoAlso return decisions with metadata callable=false

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only states what it finds, not that it is a read-only query, how results are returned, or any side effects. Minimal disclosure.

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?

A single, well-formed sentence of nine words that captures the tool's core function with no unnecessary information. Perfectly concise.

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 the existence of an output schema and full parameter descriptions, the short description combined with the schema provides sufficient context for a straightforward filtered query. It could mention that results are a list, but overall 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 covers 100% of parameters with detailed descriptions, so the tool description adds no extra param meaning. The description's brief mention of 'low-confidence' aligns with the 'max_confidence' parameter, but no additional insight is provided. Baseline 3 is appropriate.

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 specifies the verb 'find' and the resource 'route decisions' with qualifiers 'low-confidence or explicitly uncallable'. This distinguishes it from sibling tool 'find_route_decisions', though it could explicitly contrast the two.

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 like 'find_route_decisions' or 'find_exceptions'. No context on prerequisites or filters beyond the name.

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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