evaluation_scorecardGenerates a reusable scorecard structure for documenting AI-agent tests, offering a standardized framework to capture evaluation criteria and assess agent performance consistently.
Return a reusable scorecard structure for documenting AI-agent tests.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, which cover the safety profile. The description adds the clarifying context that this returns a reusable structure for documentation purposes. It does not contradict the annotations, but it does not reveal much beyond them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the action verb and resource. Every word earns its place, and there is no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with safety annotations, the description is reasonably complete. However, there is no output schema, so the description should more clearly explain what the 'scorecard structure' contains or how it relates to the sibling tools like score_agent_run. Without that, an agent may not fully understand the return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there are no parameter semantics to document. The description correctly implies a parameterless invocation by simply describing the action and output. Baseline of 4 for no-parameter tools is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Return') and a clear resource ('reusable scorecard structure for documenting AI-agent tests'). It conveys that this tool provides a template rather than performing scoring, which distinguishes it from siblings like score_agent_run and generate_test_plan, though it does not explicitly name them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied: call this when you need a reusable scorecard structure. However, there is no explicit guidance on when to prefer this over the sibling tools or any exclusions. It would benefit from stating that it returns a template rather than executing or scoring anything.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.