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Swanand33

mcp-llm-behave

by Swanand33

list_builtin_behaviors

Retrieve the catalog of built-in behavioral checks to identify available semantic similarity metrics for offline LLM output testing without API calls.

Instructions

Return the catalog of built-in behavioral checks available in llm-behave.

Returns: list of dicts, each with 'name', 'method', and 'description' keys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It discloses the return format (list of dicts with 'name', 'method', 'description') adequately, but does not mention behavioral traits like read-only nature, performance, or error behavior.

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?

Two sentences, zero waste. The purpose is stated first, followed by concise return structure. Ideal length and structure for a simple tool.

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?

Given zero parameters and an existing output schema, the description provides the return keys. However, it lacks usage context (e.g., when to list vs. run tests) and does not cover edge cases or failure modes. Adequate but not complete.

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?

The input schema has 0 parameters with 100% coverage. The description adds no parameter info because none exists, which is appropriate. Baseline of 4 for zero-parameter tools.

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 verb 'Return' and the resource 'catalog of built-in behavioral checks.' It immediately differentiates from sibling tools 'compare_outputs' and 'run_behavior_test' which involve executing or comparing tests rather than listing.

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?

No explicit when-to-use or when-not-to-use guidance is provided. While the zero-parameter signature implies it is a simple retrieval tool, the description does not mention it as a prerequisite for other tools or give any context for decision-making.

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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