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generate_bdd_template

Creates a BDD test template for new test cases, providing a structured starting point with a given test case name and optional description.

Instructions

Generate a BDD test template that can be used as a starting point for creating new BDD-style test cases.

Args: test_case_name: Name of the test case test_description: Description for the BDD feature (recommended)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
test_case_nameYes
test_descriptionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesSummary of what was generated
feature_templateYesContent for test.feature with Gherkin Background and Scenario sections
test_py_templateYesContent for test.py with BDD boilerplate (source, setupHooks, etc.)
step_definitions_templateYesContent for step definitions Python file
Behavior2/5

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It states that a template is generated but does not specify whether this creates a file, returns the template, or modifies any state. There is no mention of side effects, authentication needs, or output format. The tool likely is read-only, but this is not confirmed.

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 extremely concise—two lines plus a simple arg list. Every word serves a purpose, with no fluff or repetition. It is well-structured and front-loads the purpose statement, making it easy to scan.

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 the tool has 2 parameters, no annotations, and an output schema (not visible), the description is adequate but not thorough. It covers purpose and basic param semantics but lacks usage context, behavioral details, and output explanation. For a simple template generator, this may be minimally viable but has clear gaps.

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 0%, so the description must compensate. It provides brief but clear meanings for both parameters: 'Name of the test case' and 'Description for the BDD feature (recommended).' The inclusion of '(recommended)' for test_description adds nuance. However, it lacks details like expected format, length limits, or relationships between parameters.

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 clearly states that the tool generates a BDD test template as a starting point for BDD-style test cases. It uses a specific verb ('Generate') and resource ('BDD test template'), distinguishing it from sibling tools like 'generate_test_template' (generic) and 'create_test_case' (actual creation). However, it could more explicitly differentiate usage scenarios.

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 mentions the tool 'can be used as a starting point for creating new BDD-style test cases,' but provides no guidance on when to use it vs. alternatives like 'generate_test_template' or 'create_test_case.' There are no when-not-to use instructions, explicit context, 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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