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generate_atf_tests

Generate ATF test cases for ServiceNow artifacts including business rules, script includes, REST APIs, forms, and table validations. Returns ready-to-import test suite JSON.

Instructions

Generate ATF (Automated Test Framework) test cases for ServiceNow artifacts.

Supported test targets: business_rule — positive, negative, and field-change trigger tests script_include — unit tests per method (happy path + null/invalid input) scripted_rest — auth, validation, and custom scenario tests form — Client Script / UI Policy field behaviour tests table — mandatory field, uniqueness, and basic CRUD smoke tests

Returns ATF test suite JSON with steps ready to import + deploy instructions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_typeYes
nameYesName of the artifact under test
tableNoTable name (required for BR, form, table tests)
trigger_conditionsNo
field_changesNo
expected_outcomesNo
methodsNo
api_pathNo
verbNo
required_paramsNo
test_casesNo
scenariosNo
mandatory_fieldsNo
unique_fieldsNo
Behavior5/5

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

No annotations provided, but the description clearly states the tool returns ATF test suite JSON with steps and deploy instructions, implying no side effects (generation only). No contradictions or missing behavioral traits for a generation tool of this nature.

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 concise: a one-line purpose followed by a bulleted list of targets. No extraneous words, front-loaded, and well-structured for quick parsing.

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?

Despite good purpose clarity, the description lacks detail on many parameters (e.g., trigger_conditions, field_changes, expected_outcomes), the exact format of the returned JSON, or deployment instructions. For a complex tool with 14 parameters and nested objects, this is insufficient for an agent to use correctly.

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?

Schema description coverage is only 14% (2/14 parameters documented). The description adds value by explaining target_type meanings and conditional requirement for 'table', but omits semantics for many parameters like trigger_conditions, field_changes, expected_outcomes, methods, etc. Partially compensates but not fully.

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 generates ATF test cases for ServiceNow artifacts, lists five specific target types with their test generation focus (e.g., 'business_rule — positive, negative, and field-change trigger tests'), and distinguishes itself from sibling tools like 'analyze_for_testing' or 'create_test_plan' which are more analytical or planning-oriented.

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?

The description provides context on what tests each target type generates, implying usage scenarios (e.g., business rule tests for trigger conditions), but does not explicitly state when to use this tool versus alternatives like 'analyze_for_testing' or indicate when not to use it. This is a minor gap.

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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