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llmeval_setup_framework

Set up an LLM evaluation framework in a project directory. Supply an API key to enable evaluation configuration.

Instructions

Set up LLM evaluation framework

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
directoryYesProject directory
Behavior1/5

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

With no annotations, the description must disclose behavioral traits itself, but it only says "Set up." It does not mention whether files are created, whether the directory must already exist, whether the operation is destructive, whether repeated runs are safe, or how the api_key parameter is used.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded and contains no filler, making it easy to parse. However, it is under-specified: the single sentence conveys almost nothing beyond the tool name, so brevity comes at the expense of useful operational context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter setup tool with no annotations, no output schema, and one undocumented parameter, a single vague sentence is not enough. The agent would need to guess at side effects, api_key semantics, and the exact meaning of "framework setup."

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?

The schema documents only the directory parameter; api_key has no schema description. The tool description adds no meaning to either parameter, so an agent cannot infer what api_key is for or whether it is required for certain setup paths.

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 states a clear verb and resource: "Set up LLM evaluation framework." It separates this from sibling tools like llmeval_add_benchmarks and llmeval_generate_reports through the "setup" verb, even though it does not explicitly name those alternatives or detail what the framework setup includes.

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 guidance is provided about when to use this tool versus alternatives such as llmeval_add_benchmarks or llmeval_generate_reports. The verb "Set up" weakly implies first-time initialization, but there are no prerequisites, ordering hints, or exclusions.

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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