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create_test

Generate a YAML test case to define expected agent behavior. Specify query, expected tools, forbidden tools, and output checks to automatically validate agent responses.

Instructions

Create a new EvalView test case YAML file for an agent. Call this when the user asks to add a test, or when you want to capture expected agent behavior. After creating a test, call run_snapshot to establish the baseline. No YAML knowledge required — just describe the test. IMPORTANT: Automatically detect test_path by looking for a 'tests/evalview/' directory in the current project. If found, use it. Otherwise use 'tests'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesTest name (e.g. 'calculator-division', 'weather-lookup')
queryYesThe input query to send to the agent
min_scoreNoMinimum passing score 0-100 (default: 70)
test_pathNoDirectory to save the test file. Auto-detect: use 'tests/evalview/' if it exists in the project, otherwise 'tests'.
descriptionNoHuman-readable description of what this test covers
expected_toolsNoTool names the agent should call (e.g. ['calculator', 'search'])
forbidden_toolsNoTool names the agent must NEVER call. Any violation is an immediate hard-fail (score=0, passed=false) regardless of output quality. Use this for safety contracts — e.g. a read-only agent that must never call edit_file, bash, or write_file. Matching is case-insensitive: 'EditFile' catches 'edit_file'.
expected_output_containsNoStrings that must appear in the agent's output
Behavior3/5

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

With no annotations, the description carries the full burden. It explains the creation process, auto-detection of test_path, and the need to call run_snapshot. However, it does not disclose whether existing files are overwritten, any side effects, or required permissions, which is a gap for a creation tool.

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

Conciseness4/5

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

The description is front-loaded with the main purpose and usage. It is well-structured but could be slightly more concise; the test_path auto-detection detail could be integrated more tightly without losing clarity.

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 8 parameters, no output schema, and no annotations, the description covers creation workflow and post-action (run_snapshot). However, it lacks information on what happens if the test already exists (overwrite? abort?), which is crucial for agents. This omission weakens completeness.

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?

Schema coverage is 100%, baseline 3. Description adds significant value: it explains auto-detection logic for test_path and details the hard-fail semantics of forbidden_tools (case-insensitive, immediate failure). These clarifications go beyond the schema.

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 tool's function: 'Create a new EvalView test case YAML file for an agent.' It distinguishes from sibling tools like compare_agents, run_snapshot, and list_tests, which do not create tests.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use guidance: 'Call this when the user asks to add a test, or when you want to capture expected agent behavior.' Also provides workflow: 'After creating a test, call run_snapshot to establish the baseline.' Does not explicitly mention alternatives, but context is clear.

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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