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create_test_case

Create a test case in the database for a company by providing conversation context and expected output, enabling AI voice agent testing.

Instructions

Create a new test case in the database for a specific company

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesTest case name
tool_mocksNoOptional tool call mocks for testing
company_nameYesCompany name in kebab-case (e.g., 'technical-life-care')
conversationYesFull conversation context for the test
expected_outputYesExpected AI response
expected_tool_callNoOptional expected tool call
Behavior2/5

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

With no annotations provided, the description carries full burden. It states 'Create ... in the database' which implies persistence, but it does not disclose whether the operation is idempotent, whether the company must already exist, what happens on duplicates, or any error behavior. Minimal behavioral detail beyond the obvious create action.

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, front-loaded sentence with no wasted words. It efficiently communicates the core action.

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

Completeness2/5

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

Given the complexity (6 parameters, nested objects, 4 required), the description is too sparse. It does not explain when to use this tool, what it returns, or any constraints beyond 'for a specific company'. The schema covers parameters, but the description fails to provide contextual completeness for a moderately complex tool.

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 schema descriptions cover 100% of the parameters, so the baseline is 3. The description adds nothing beyond schema: 'for a specific company' merely echoes the existing company_name parameter's schema description. No additional semantic value.

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 uses a specific verb ('Create') and identifies the resource ('test case') and context ('for a specific company'). It clearly distinguishes this creation tool from sibling tools like run_tests and list_test_cases, which serve different purposes.

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 gives no explicit guidance on when to use this tool versus alternatives. It merely states the action, leaving the agent to infer usage from the existence of sibling tools. There are no exclusions or alternative references.

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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