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mcp-llm-eval

mcp-llm-eval

by berkayildi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

check_thresholds

Validate evaluation results against quality gate thresholds, returning pass or fail for each metric and the overall gate status.

Instructions

Check evaluation results against quality gate thresholds. Returns pass/fail per metric and overall gate status.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "results_path": "<results_path>",
      "thresholds": "<thresholds>"
    },
    "name": "check_thresholds"
  }
}

Input Schema

NameRequiredDescriptionDefault
thresholdsYesQuality gate thresholds.
results_pathYesPath to an evaluation results JSON file (summary).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.2

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that it returns pass/fail per metric and overall gate status, implying a read-only check, but does not explicitly state side effects or auth requirements.

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, concise sentence with no wasted words. It is front-loaded with the action and resource.

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?

The description covers the action and basic return format, but does not explain what 'overall gate status' entails or provide any example. Given no output schema, more detail on the return structure would improve completeness.

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% for both parameters, so the description adds no extra meaning beyond the schema. The description's context of 'checking against thresholds' is implicit in the schema's 'Quality gate thresholds' description.

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 it checks evaluation results against quality gate thresholds and returns pass/fail per metric and overall status. It uses a specific verb and resource, but does not differentiate from sibling tools like check_retrieval_drift or evaluate_rag_end_to_end, which also evaluate different aspects.

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?

No explicit guidance on when to use this tool versus alternatives. It implies usage when evaluation results are available, but lacks exclusions or references to siblings.

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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